CN111684235A

CN111684235A - Temperature data processing method and device, distance measuring system and mobile terminal

Info

Publication number: CN111684235A
Application number: CN201980005007.3A
Authority: CN
Inventors: 王闯; 刘祯
Original assignee: SZ DJI Technology Co Ltd
Current assignee: SZ DJI Technology Co Ltd
Priority date: 2019-01-09
Filing date: 2019-01-09
Publication date: 2020-09-18
Also published as: WO2020142962A1

Abstract

A temperature data processing method comprises the following steps: (S11) acquiring a plurality of temperatures detected by a plurality of temperature sensors (110); (S12) determining whether there is abnormal data in the plurality of temperatures; (S13) when there is abnormal data among the plurality of temperatures, determining confidence data of the abnormal data based on the preset temperature data. The application also discloses a temperature data processing device (10), a ranging system (100) and a mobile terminal (1000).

Description

Temperature data processing method and device, distance measuring system and mobile terminal

Technical Field

The present disclosure relates to the field of temperature data processing, and in particular, to a temperature data processing method, a temperature data processing apparatus, a ranging system, and a mobile terminal.

Background

The related art generally performs scanning and distance measurement by a laser ranging system to acquire three-dimensional information of a surrounding scene to realize three-dimensional reconstruction. However, in actual use, the performance of many critical devices inside the laser ranging system can be affected by temperature. Therefore, it is necessary to acquire the current temperature of the key device of the system as accurately as possible and compensate the working parameters and the measurement results to ensure the stable performance of the laser ranging system. However, the difference between the heating model and the heat dissipation model at each position in the laser ranging system is large, so that a plurality of temperature sensors are generally required to perform distributed measurement. Because each sensor has a certain failure probability, if a certain temperature sensor fails suddenly during operation, so that the acquired temperature is wrong, the processing measures based on the wrong temperature value are likely to bring wrong compensation, and even damage the device or the ranging system.

Disclosure of Invention

The embodiment of the application provides a temperature data processing method, a temperature data processing device, a distance measuring system and a mobile terminal.

The temperature data processing method of the embodiment of the application comprises the following steps:

acquiring a plurality of temperatures detected by a plurality of temperature sensors;

determining whether there is anomalous data in the plurality of temperatures;

and when the abnormal data exist in the plurality of temperatures, determining confidence data of the abnormal data according to preset temperature data.

The temperature data processing device of the embodiment of the application comprises a processor and a memory, wherein the memory stores one or more programs, and the processor is used for acquiring a plurality of temperatures detected by a plurality of temperature sensors; and for determining whether there is anomalous data in the plurality of temperatures; and when the abnormal data exist in the plurality of temperatures, determining confidence data of the abnormal data according to preset temperature data.

The distance measuring system of the embodiment of the application comprises a plurality of temperature sensors arranged in the distance measuring system and the temperature data processing device.

The mobile terminal of the embodiment of the application comprises the ranging system.

According to the temperature data processing method, the temperature data processing device, the distance measuring system and the mobile terminal, confidence data of abnormal data are determined according to the preset temperature data, accuracy of identifying the abnormal data is improved, and meanwhile accuracy of temperature compensation can be guaranteed through the confidence data after the abnormal data appear.

Additional aspects and advantages of embodiments of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of embodiments of the present application.

Drawings

The above and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:

fig. 1 is a schematic flow chart of a temperature data processing method according to an embodiment of the present application;

FIG. 2 is a block schematic diagram of a ranging system according to an embodiment of the present application;

FIG. 3 is a schematic diagram of the relationship between the laser power and the current of a semiconductor laser at different temperatures;

FIG. 4 is a graph showing signal amplification versus temperature for an avalanche photodiode at different temperatures;

FIG. 5 is a schematic diagram of preset temperature data of a temperature data processing method according to an embodiment of the present application;

FIG. 6 is a schematic flow chart of a temperature data processing method according to another embodiment of the present application;

FIG. 7 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 8 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 9 is a schematic flow chart diagram of a temperature data processing method according to another embodiment of the present application;

FIG. 10 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 11 is a schematic flow chart illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 12 is a block schematic diagram of a ranging system according to another embodiment of the present application;

FIG. 13 is a schematic flow chart diagram of a temperature data processing method according to another embodiment of the present application;

FIG. 14 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 15 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 16 is a schematic flow chart diagram illustrating a temperature data processing method according to another embodiment of the present application;

FIG. 17 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 18 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 19 is a schematic flow chart diagram of a temperature data processing method according to another embodiment of the present application;

FIG. 20 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 21 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 22 is a schematic flow chart diagram of a temperature data processing method according to another embodiment of the present application;

FIG. 23 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 24 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 25 is a schematic flow chart diagram of a temperature data processing method according to another embodiment of the present application;

FIG. 26 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 27 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 28 is a schematic flow chart diagram illustrating a temperature data processing method according to another embodiment of the present application;

FIG. 29 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 30 is a schematic flow chart diagram illustrating a temperature data processing method according to yet another embodiment of the present application;

FIG. 31 is a schematic flow chart diagram illustrating a temperature data processing method according to another embodiment of the present application;

fig. 32 is a schematic configuration diagram of a mobile terminal according to an embodiment of the present application.

Description of the main element symbols:

mobile terminal 1000, laser ranging system 100, temperature sensor 110, temperature data processing device 10, memory 101, processor 102, laser transmitter 120, receiver 130, ambient temperature sensor 200.

Detailed Description

Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative and are only for the purpose of explaining the present application and are not to be construed as limiting the present application.

In the description of the present application, it is to be understood that the terms "first", "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present application, "a plurality" means two or more unless specifically limited otherwise.

In the description of the present application, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; may be mechanically connected, may be electrically connected or may be in communication with each other; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as appropriate.

The following disclosure provides many different embodiments or examples for implementing different features of the application. In order to simplify the disclosure of the present application, specific example components and arrangements are described below. Of course, they are merely examples and are not intended to limit the present application. Moreover, the present application may repeat reference numerals and/or letters in the various examples, such repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. In addition, examples of various specific processes and materials are provided herein, but one of ordinary skill in the art may recognize applications of other processes and/or use of other materials.

Referring to fig. 1, a temperature data processing method is provided in an embodiment of the present disclosure. The temperature data processing method of the embodiment of the application comprises the following steps:

step S11: acquiring a plurality of temperatures detected by a plurality of temperature sensors 110;

step S12: determining whether there is abnormal data in the plurality of temperatures;

step S13: and when abnormal data exist in the plurality of temperatures, determining confidence data of the abnormal data according to preset temperature data.

The temperature data processing method according to the embodiment of the present application may be applied to a system or an apparatus that acquires temperature data using a plurality of temperature sensors, such as the distance measuring system 100 and a home appliance.

Referring to fig. 2, in the embodiment of the present application, a temperature data processing method applied to the ranging system 100 is illustrated and described as an example. Note that this does not represent a limitation to the application scenario of the temperature data processing method.

The distance measuring system 100 according to the embodiment of the present application includes a plurality of temperature sensors 110 and a temperature data processing device 10 provided inside the distance measuring system 100.

The temperature data processing device 10 comprises a memory 101 and a processor 102, wherein the memory 101 stores one or more programs, and the processor 102 is used for executing the one or more programs to realize the temperature data processing method. That is, the processor 102 is configured to execute step S11: acquiring a plurality of temperatures detected by a plurality of temperature sensors 110; step S12: determining whether there is abnormal data in the plurality of temperatures; step S13: and when abnormal data exist in the plurality of temperatures, determining confidence data of the abnormal data according to preset temperature data.

It can be understood that the abnormal data in the present application is the uncertain temperature data among a plurality of temperatures, and the confidence data is the data with higher confidence, i.e. the confident temperature data.

According to the temperature data processing method, the temperature data processing device 10 and the ranging system 100, confidence data of abnormal data are determined according to preset temperature data, accuracy of identifying the abnormal data is improved, and meanwhile accuracy of temperature compensation can be guaranteed through the confidence data after the abnormal data appear.

Specifically, in the example of fig. 2, the ranging system 100 is a laser ranging system 100, the laser ranging system 100 including a laser transmitter 120 and a receiver 130. The laser ranging system 100 is a sensing system that uses a laser transmitter 120 to transmit laser and a receiver 130 to receive laser reflected from the environment, and then performs scanning and distance measurement to obtain three-dimensional information in the surrounding scene. The basic principle of the laser ranging system 100 is to actively emit laser pulses to a detected object, capture a laser echo signal, and calculate the distance of the detected object according to the time difference between the emission and the reception of the laser; obtaining angle information of the measured object based on the known emission direction of the laser; through high-frequency emission and reception, the distance and angle information of massive detection points, namely point clouds, can be obtained, and three-dimensional information of surrounding scenes can be reconstructed based on the point clouds.

In practical use, since the performance of many critical devices inside the laser ranging system 100 is affected by temperature, it is necessary to obtain the current temperature of the critical devices of the system as accurately as possible and compensate the working parameters and the measurement results to ensure the stable performance of the system.

Devices that may be affected by temperature in laser ranging system 100 include lasers, receivers, and other electronics. It is understood that the ranging system 100 may be other types of ranging systems, such as an ultrasonic ranging system. Alternatively, the temperature data processing device 10 may be applied to other electrical systems. These electrical systems require temperature detection of system components and corresponding operation based on the results of the temperature detection.

Referring to fig. 3, in general, the output power of the laser emitter decreases with increasing temperature. This is mainly caused by two reasons: first, the threshold current Ith of the laser increases with increasing temperature; second, the external quantum efficiency η d decreases with increasing temperature. Fig. 3 is a schematic diagram of the relationship between laser power and current at different temperatures of a semiconductor laser transmitter.

Referring to fig. 4, the receiver generally includes a Photodiode (PIN), an Avalanche Photodiode (APD), a Silicon photomultiplier (SiPM), and a Single Photon Avalanche Diode (SPAD). FIG. 4 is a graph of signal amplification versus temperature for an APD at different temperatures.

In addition, the performance parameters of electronic devices such as resistors, capacitors, inductors, digital/analog chips, and the like are affected by temperature to a different degree, so that the finally received laser echo signal and the calculated distance and direction information have a certain degree of coupling relationship with temperature. In addition, the power consumption and the lifetime of the system can also be affected by temperature.

The solution to the above problem requires accurate acquisition of the current temperature of the laser ranging system 100 and enabling specific processing measures depending on the temperature. However, since the heat generation/dissipation models vary widely at various locations within the system, distributed measurements are typically required using multiple temperature sensors 110. Since each sensor has a certain probability of failure, if a temperature sensor 110 fails suddenly during operation, resulting in an error in the collected temperature, the processing based on the erroneous temperature value is likely to cause an erroneous compensation, even damage to the device or the ranging system 100.

In the temperature data processing method and the ranging system 100 according to the embodiment of the present application, since the confidence data of the abnormal data is determined according to the preset temperature data, not only the accuracy of identifying the abnormal data can be improved, but also the accuracy of temperature compensation can be ensured through the confidence data after the abnormal data occurs, so that the safety of the ranging system 100 is improved, and the ranging system 100 can continue to work normally after the abnormal data occurs.

In step S11, a plurality of temperature sensors 110 may be disposed at locations within the ranging system 100 where temperature detection is required. The number of temperature sensors 110 may be 2, 3, 5, or other numbers. The specific locations and the specific number of the temperature sensors 110 are not limited herein.

In step S12, it is determined whether there is any abnormal data among the plurality of temperatures, which is temperature data indicating whether there is any abnormality among the plurality of temperatures collected by the plurality of temperature sensors. When one of the plurality of temperatures is abnormal, the abnormal data is considered to exist in the plurality of temperatures. It is to be understood that when there is abnormal data in a plurality of temperatures, one or more of the plurality of temperatures may be abnormal, or all of the plurality of data may be abnormal. In addition, after determining whether there is abnormal data in the plurality of temperatures, the normal data may be formed into an effective temperature data set, and after determining confidence data of the abnormal data, the confidence data may be added to the effective temperature data set.

In step S13, the preset temperature data may be stored in the memory 101 in advance. Further, the preset temperature data may be calibrated by simulating actual use conditions through experiments, and stored in the memory 101 or other storage medium of the ranging system 100 before the ranging system 100 is shipped.

Referring to fig. 5, in one example, the ambient temperature is T0, and the laser ranging system 100 has 5 temperature sensors 110, which are: temperature sensor TS1, temperature sensor TS2, temperature sensor TS3, temperature sensor TS4 and temperature sensor TS5, the temperature values measured by 5 temperature sensors 110 are T1, T2, T3, T4 and T5, respectively, and temperature rise TRi ═ Ti-T0 of the ith sensor is defined, where i ═ 1, 2, 3, 4, 5. The 5 temperature sensors 110 are respectively distributed at five positions of P1, P2, P3, P4 and P5, and the heat generation amount of the five positions is P1> P2> P3> P4> P5 in sequence. Since the above-mentioned positions can be thermally conducted by metal heat conduction or air convection, the temperature of each temperature sensor 110 tends to a thermal equilibrium state when the ambient temperature T0 tends to be stable. Through thermodynamic simulation or experimental tests, historical data of the 5 temperature sensors 110 are recorded in a range from the lowest temperature to the highest temperature that the ranging system 100 is allowed to operate, so that a curve as shown in fig. 5 can be obtained, and data corresponding to the curve shown in fig. 5 can be used as preset temperature data.

Referring to fig. 6, in some embodiments, the temperature data processing method further includes:

step S16: and performing temperature compensation according to the normal data and the confidence data in the plurality of temperatures.

In some embodiments, the processor 102 is configured to perform temperature compensation based on the normal data and the confidence data in the plurality of temperatures.

Thus, the ranging system 100 can be ensured to continue to work normally after abnormal data occurs. It is understood that the temperature compensation may be performed according to a plurality of temperatures when there is no abnormal data among the plurality of temperatures. When there is abnormal data in a plurality of temperatures, since the confidence data of the abnormal data is determined according to the preset temperature data in step S13, the confidence data may be used to replace the role of the abnormal data in the temperature compensation process, that is, the temperature compensation is performed according to the normal data and the confidence data in the plurality of temperatures, so as to ensure the normal operation of the distance measuring system 100.

Specifically, the normal data and the confidence data can be brought into a preset calculation model to obtain data required by temperature compensation so as to realize temperature compensation; other components of ranging system 100 may also be adjusted based on the normal data and the confidence data. The specific manner in which temperature compensation is performed based on normal data and confidence data is not limited herein.

Referring to fig. 7, in some embodiments, before step S16, the method for processing temperature data further includes:

step S14: checking whether the confidence data is normal; when the confidence data is normal, the step of performing temperature compensation according to the normal data and the confidence data in a plurality of temperatures is carried out;

step S15: and when the confidence data is abnormal, performing temperature compensation according to normal data in a plurality of temperatures.

In some embodiments, the processor 102 is configured to verify that the confidence data is normal; and a step for performing temperature compensation according to normal data and confidence data in a plurality of temperatures when the confidence data is normal; and the temperature compensation module is used for performing temperature compensation according to normal data in a plurality of temperatures when the confidence data are abnormal.

Thus, the reliability of confidence data is ensured, and the normal operation of temperature compensation is further ensured. It is understood that the confidence data of the abnormal data determined according to the preset temperature data in step S13 may be abnormal due to various reasons such as loss or failure of the preset temperature data. In the embodiment of the present application, by checking whether the confidence data is normal or not, the reliability of the confidence data can be ensured, thereby further ensuring the rationality of the temperature compensation, and further preventing the distance measuring system 100 from being damaged due to the unreasonable temperature compensation performed according to the abnormal confidence data.

Referring to fig. 8, in some embodiments, step S14 includes:

step S142: determining whether the confidence data is normal based on normal data in a plurality of temperatures.

In some embodiments, the processor 102 is configured to determine whether the confidence data is normal based on normal data in a plurality of temperatures.

Thus, the checking whether the trusted data is normal or not is realized. In the embodiment of the present application, the determination method for checking whether the confidence data is normal is consistent with the determination method for determining whether there is abnormal data in a plurality of temperatures. It is to be understood that the determination method for verifying whether the confidence data is normal may not be consistent with the determination method for determining whether there is abnormal data in a plurality of temperatures. Alternatively, the judgment method for checking whether the confidence data is normal is one or more of a plurality of judgment methods for determining whether there is abnormal data in a plurality of temperatures. The determination method for determining whether there is abnormal data in a plurality of temperatures is described in detail later.

Referring to fig. 9, in some embodiments, the temperature data processing method further includes:

step S17: and adjusting the temperature in the detection range of the temperature sensor 110 corresponding to the abnormal data according to the confidence data.

In some embodiments, the processor 102 is configured to adjust the temperature within the detection range of the temperature sensor 110 corresponding to the abnormal data based on the confidence data.

Thus, the application of the trusted data is realized. It is to be appreciated that the confidence data can be indicative of a current temperature within the detection range of the temperature sensor 110 to which the anomaly data corresponds.

Adjusting the temperature in the detection range of the temperature sensor 110 corresponding to the abnormal data according to the confidence data may be determining whether the temperature in the detection range of the temperature sensor 110 corresponding to the abnormal data is within a temperature interval of normal operation according to the confidence data, and when the confidence data is greater than an expected temperature interval of normal operation, the processor 102 may send a heat dissipation control signal to a heat dissipation component (e.g., a fan) corresponding to the detection range, so as to reduce the temperature in the detection range of the temperature sensor 110 corresponding to the abnormal data to the temperature interval of normal operation. When the confidence data is less than the expected temperature interval for normal operation, the processor 102 may send a heating control signal to the heating component corresponding to the detection range to raise the temperature within the detection range of the temperature sensor 110 corresponding to the abnormal data to the temperature interval for normal operation. In this way, the temperature within the detection range of the temperature sensor 110 corresponding to the abnormal data is adjusted, so as to ensure the normal operation of the distance measuring system 100.

Referring to fig. 10, in some embodiments, the preset temperature data includes a first corresponding relationship between the ambient temperature and the standard temperature rise of each temperature sensor 110, and the temperature data processing method includes:

step S131: acquiring the current environment temperature;

step S13 includes:

step S132: determining the standard temperature rise of the temperature sensor 110 corresponding to the abnormal data according to the current environment temperature and the first corresponding relation;

step S133: confidence data is determined based on the current ambient temperature and the standard temperature rise of the temperature sensor 110 corresponding to the abnormal data.

In some embodiments, the processor 102 is configured to obtain a current ambient temperature; and a standard temperature rise of the temperature sensor 110 for determining the correspondence of the abnormal data according to the current ambient temperature and the first correspondence; and for determining confidence data based on the current ambient temperature and the standard temperature rise of the temperature sensor 110 corresponding to the anomaly data.

Therefore, confidence data of the abnormal data are determined according to the preset temperature data. Specifically, the first correspondence of ambient temperature to the standard temperature rise of each temperature sensor 110 may be stored in a table format in the memory 101 or other storage medium. In step S132, the first mapping table of the temperature sensor 110 corresponding to the abnormal data may be searched according to the current ambient temperature, so as to determine the standard temperature rise of the temperature sensor 110 corresponding to the abnormal data.

In addition, the confidence data in step S133 may be realized by the following formula:

T_x＝T₀+TR_x；

wherein, T₀At ambient temperature, TR_xStandard temperature rise, T, of the temperature sensor 110 for abnormal data_xIs confidence data of abnormal data.

It can be understood that the difference between the temperature detected by the temperature sensor 110 during normal operation and the ambient temperature is the standard temperature rise of the temperature sensor 110. Therefore, the sum of the current ambient temperature and the standard temperature rise of the temperature sensor 110 corresponding to the abnormal data at the current ambient temperature can be used as the actual temperature that the temperature sensor 110 corresponding to the abnormal data should detect, i.e. the confidence data.

In the example shown in fig. 10, step S131 follows step S12 and precedes step S132. It is understood that in other examples, step S131 may precede step S11, may be performed simultaneously with step S11, may follow step S11, and step S131 may precede step S12, may be performed simultaneously with step S12. Here, the order of step S131 and other steps is not limited. Referring to fig. 11 and 12, in some embodiments, step S131 includes:

step S1311: the current ambient temperature is acquired by the ambient temperature sensor 200.

In some embodiments, the processor 102 is configured to obtain the current ambient temperature via the ambient temperature sensor 200.

Thus, the current environment temperature is obtained. Specifically, the ambient temperature sensor 200 is disposed outside the ranging system 100. It can be understood that, since the plurality of temperature sensors 110 are all disposed inside the distance measuring system 100, the ambient temperature of the distance measuring system 100 can be directly obtained by the ambient temperature sensor 200 disposed outside the distance measuring system 100, and taken as the current ambient temperature. Therefore, the current environment temperature can be conveniently, quickly and accurately acquired.

In one example, the ambient temperature sensor 200 may continuously obtain the current ambient temperature and send the current ambient temperature to the memory 101 or other storage medium for saving, and the processor 102 may directly read the current ambient temperature from the memory 101 or other storage medium when the current ambient temperature is needed. Even when the ambient temperature at a certain time of the history needs to be acquired, the processor 102 may directly read the ambient temperature from the memory 101.

In another example, when the current ambient temperature is needed, the processor 102 may send a data request signal to the ambient temperature sensor 200, and the ambient temperature sensor 200 directly sends the current ambient temperature to the processor 102 after receiving the data request signal, so that the processor 102 obtains the current ambient temperature.

Referring to fig. 13, in some embodiments, the preset temperature data includes a second corresponding relationship between the temperature of each temperature sensor 110 and the standard temperature rise, and the step S131 includes:

step S1312: acquiring the standard temperature rise of the temperature sensor 110 corresponding to the normal data according to the normal data in the plurality of temperatures and the second corresponding relation;

step S1313: and determining the current environment temperature according to the normal data, the standard temperature rise of the temperature sensor 110 corresponding to the normal data and the confidence weight of the temperature sensor 110 corresponding to the normal data.

In some embodiments, the processor 102 is configured to obtain a standard temperature rise of the temperature sensor 110 corresponding to the normal data according to the normal data in the plurality of temperatures and the second corresponding relationship; and is used for determining the current ambient temperature according to the normal data, the standard temperature rise of the temperature sensor 110 corresponding to the normal data and the confidence weight of the temperature sensor 110 corresponding to the normal data.

Thus, the current environment temperature is obtained. It can be understood that, since the plurality of temperature sensors 110 are all disposed inside the ranging system 100, it can be considered that the current ambient temperatures of the plurality of temperature sensors 110 are the same, that is, the current ambient temperature of the temperature sensor 110 corresponding to the normal data is the same as the current ambient temperature of the temperature sensor 110 corresponding to the abnormal data. Therefore, the current ambient temperature can be determined according to the normal data, the standard temperature rise of the temperature sensor 110 corresponding to the normal data, and the confidence weight of the temperature sensor 110 corresponding to the normal data, and the confidence data can be determined according to the current ambient temperature obtained in this way and the standard temperature rise of the temperature sensor 110 corresponding to the abnormal data.

Specifically, the second correspondence of the temperature of each temperature sensor 110 to the standard temperature rise may be stored in the memory 101 or other storage medium in a form such as a table. In step S1312, the corresponding second mapping table may be searched according to the normal data, so as to determine the standard temperature rise of the temperature sensor 110 corresponding to the normal data.

In addition, the ambient temperature of step S1313 may be realized by the following equation:

T₀＝∑(T_i-TR_i)*W_i；

wherein, T₀As ambient temperature, Ti is the current temperature (normal data) of the ith temperature sensor 110, TR_iis the standard temperature rise of the ith temperature sensor 110, Wi is the confidence weight, Σ W, of the ith temperature sensor 110_i＝1。

Further, in the embodiment of the present application, the confidence weight may be preset according to the reliability and accuracy definitions of the plurality of temperature sensors 110 in the ranging system 100. The reliability of the temperature sensor 110 is positively correlated with the confidence weight, and the accuracy of the temperature sensor 110 is positively correlated with the confidence weight. The confidence weights may be pre-stored in memory 101 or other storage medium.

In one example, the ranging system 100 has a total of 5 temperature sensors 110, which are: temperature sensor TS1, temperature sensor TS2, temperature sensor TS3, temperature sensor TS4 and temperature sensor TS5, wherein temperature sensor TS5 is unusual, and the reliability of 5 temperature sensors 110 is in order from strong to weak: temperature sensor TS1, temperature sensor TS2, temperature sensor TS3, temperature sensor TS4, and temperature sensor TS 5. Confidence weights of the temperature sensor TS1, the temperature sensor TS2, the temperature sensor TS3 and the temperature sensor TS4 are as follows: 0.4, 0.3, 0.2, 0.1. Since the temperature sensor TS5 is abnormal, the confidence weight of the temperature sensor TS5 is 0. The temperatures measured by the temperature sensor TS1, the temperature sensor TS2, the temperature sensor TS3 and the temperature sensor TS4 are as follows in sequence: 10 ℃, 20 ℃, 30 ℃ and 40 ℃. According to the second corresponding relation, it is assumed that the standard temperature rises of the temperature sensor TS1, the temperature sensor TS2, the temperature sensor TS3 and the temperature sensor TS4 are sequentially: 0 deg.C, 10 deg.C, 20 deg.C, 30 deg.C. According to the formula T₀＝∑(T_i-TR_i)*W_iThe current ring can be obtainedThe ambient temperature is: t is₀(10-0) × 0.4+ (20-10) × 0.3+ (30-20) × 0.2+ (40-30) × 0.1 ═ 10. According to the first corresponding relation, if it can be obtained that the standard temperature rise of the temperature sensor TS5 is 5 ℃ when the current ambient temperature is 10 ℃, then the formula T is used_x＝T₀+TR_xThe confidence temperature of the temperature sensor TS5 can be found as: 10+5 ═ 15 ℃.

Referring to fig. 14, in some embodiments, the temperature data processing method further includes:

step S1314: and adjusting the confidence weight of the temperature sensor 110 corresponding to the normal data in real time according to the change of the temperature sensor 110 corresponding to the normal data.

In some embodiments, the processor 102 is configured to adjust the confidence weight of the temperature sensor 110 corresponding to the normal data in real time according to the change of the temperature sensor 110 corresponding to the normal data.

In this way, the adjustment of the signaling weight is realized. Specifically, before determining whether there is abnormal data in the plurality of temperatures, the sum of the confidence weights of the plurality of temperature sensors 110 is 1, after determining the abnormal data, the confidence weight of the temperature sensor 110 corresponding to the abnormal data is assigned to the confidence weight of the temperature sensor 110 corresponding to the normal data, so that the confidence weight of the temperature sensor 110 corresponding to the abnormal data is adjusted to 0, and the sum of the confidence weights of the temperature sensors 110 corresponding to the normal data is 1, thereby realizing real-time adjustment of the confidence weight of the temperature sensor 110 corresponding to the normal data.

Similarly, when the confidence weight of the temperature sensor 110 corresponding to abnormal data is assigned to the confidence weight of the temperature sensor 110 corresponding to normal data, the assignment may be made in accordance with the reliability and accuracy of the temperature sensor 110 corresponding to normal data.

It can be understood that, each time it is determined whether there is abnormal data in the plurality of temperatures, the temperature sensors 110 corresponding to the abnormal data may not be the same, that is, the temperature sensors 110 corresponding to the normal data are not the same, and the confidence weights of the temperature sensors 110 corresponding to the normal data are adjusted in real time according to the change of the temperature sensors 110 corresponding to the normal data, so that the sum of the confidence weights of the temperature sensors 110 corresponding to the normal data can be ensured to be 1, thereby ensuring the reliability of the obtained current environment temperature.

Referring to fig. 15, in some embodiments, the temperature data processing method further includes:

step S1315: when the heating measure or the heat dissipation measure is performed in the detection range of the temperature sensor 110 corresponding to the normal data, the confidence weight of the temperature sensor 110 corresponding to the normal data is adjusted.

In some embodiments, the processor 102 is configured to adjust the confidence weight of the temperature sensor 110 corresponding to the normal data when the detection range of the temperature sensor 110 corresponding to the normal data performs the heating measure or the heat dissipation measure.

In this way, the confidence weight of the temperature sensor 110 corresponding to the normal data is adjusted according to the environmental change of the detection range of the temperature sensor 110. It is understood that when the heating measure or the heat dissipation measure is performed, the processor 102 sends an enabling signal to the corresponding heating component or the heat dissipation component, and therefore, it is known for the ranging system 100 whether the heating measure or the heat dissipation measure is performed in the detection range of the temperature sensor 110 corresponding to the normal data. Based on this, it may be determined whether the detection range of the temperature sensor 110 corresponding to the normal data performs a heating measure or a heat dissipation measure, thereby adjusting the confidence weight of the temperature sensor 110 corresponding to the normal data.

In addition, if a heating or heat dissipation measure is performed in the detection range of the temperature sensor 110, the temperature law of the temperature sensor 110 may no longer conform to the preset temperature data under the natural condition, and the confidence weight should be reduced, so as to reduce the influence of the related data of the temperature sensor 110 on the calculation.

Of course, when the heating measure or the heat dissipation measure is performed, the temperature data and the confidence weight of the plurality of temperature sensors 110 may be stored in the memory 101, and when it is determined that the detection range of the temperature sensor 110 corresponding to the normal data performs the heating measure or the heat dissipation measure, the confidence weight corresponding to the preset temperature data under the natural condition is not used, but the confidence weight when the heating measure or the heat dissipation measure is performed is used, so that the inaccurate calculation of the current environment temperature caused by the start of the heating measure or the heat dissipation measure is avoided.

Referring to fig. 16, in some embodiments, step S12 includes:

step S121: determining whether each temperature of the plurality of temperatures is within a preset temperature range;

step S122: determining that there is no abnormal data in the plurality of temperatures when each temperature is within a preset temperature range;

step S123: determining that there is abnormal data in the plurality of temperatures when at least one temperature is not within a preset temperature range; wherein, the temperature which is not in the preset temperature range in the plurality of temperatures is abnormal data.

In some embodiments, the processor 102 is configured to determine whether each of the plurality of temperatures is within a preset temperature range; and determining that there is no abnormal data in the plurality of temperatures when each temperature is within a preset temperature range; and determining that there is abnormal data in the plurality of temperatures when at least one temperature is not within a preset temperature range; wherein, the temperature which is not in the preset temperature range in the plurality of temperatures is abnormal data.

In this manner, a determination is made as to whether there is anomalous data in the plurality of temperatures. It is understood that in the distance measuring system 100, the temperature detected by each temperature sensor 110 in the normal state may fluctuate, in the embodiment of the present application, the fluctuation in the preset temperature range is considered as normal, and if the temperature detected by the temperature sensor 110 exceeds the preset temperature range, the temperature sensor 110 may be considered as abnormal, and the temperature is abnormal data.

Specifically, the preset temperature range may be determined through experiments and stored in the memory 101 or other storage medium, and the processor 102 may directly read the preset temperature range from the memory 101 or other storage medium when determining whether each of the plurality of temperatures is within the preset temperature range.

Of course, it is also possible to store the temperature history curves of the plurality of temperature sensors 110 shown in fig. 5 in the memory 101, and process and analyze the temperature history curves by the processor 102 to obtain the preset temperature range.

In one example, by measuring the historical data of the entire temperature interval of the distance measuring system 100, the upper and lower temperature limits that can be reached by each of the plurality of temperature sensors 110 during normal operation, that is, the preset temperature ranges of each of the plurality of temperature sensors 110, can be obtained. When the distance measuring system 100 is in operation, if a certain temperature sensor 110 is out of the preset temperature range, it is considered to be abnormal.

The preset temperature range of each temperature sensor 110 may be different; some of the temperature sensors 110 may have the same preset temperature range and some of the temperature sensors 110 may have different preset temperature ranges; the preset temperature ranges of the plurality of temperature sensors 110 may all be the same. The relationship between the preset temperature ranges of the plurality of temperature sensors 110 is not limited herein.

In another example, the ranging system 100 has a total of 3 temperature sensors 110, which are: temperature sensor TS1, temperature sensor TS2 and temperature sensor TS 3. The temperature measured by the temperature sensor TS1 is 10 ℃, the preset temperature range of the temperature sensor TS1 is 8-12 ℃, and the temperature measured by the temperature sensor TS1 is within the preset temperature range of the temperature sensor TS 1; the temperature measured by the temperature sensor TS2 is 12 ℃, the preset temperature range of the temperature sensor TS2 is 10-13 ℃, and the temperature measured by the temperature sensor TS2 is within the preset temperature range of the temperature sensor TS 2; the temperature measured by the temperature sensor TS3 is 6 ℃, the preset temperature range of the temperature sensor TS3 is 0-4 ℃, and the temperature measured by the temperature sensor TS3 is not in the preset temperature range of the temperature sensor TS 3. Therefore, since one temperature is not within the preset temperature range, it is possible to determine that there is abnormal data among a plurality of temperatures. In addition, the temperature measured by temperature sensor TS3 may be labeled as abnormal data, and temperature sensor TS3 may be labeled as an abnormal sensor.

The following schemes are typical in the related art for determining whether there is abnormal data in a plurality of temperatures: designing a reasonable temperature interval, and if the temperature of a certain sensor exceeds the interval, determining that an error occurs; a reasonable temperature difference interval is designed, and if the temperature difference between two temperature sensors 110 exceeds the interval, an error is considered. However, it can only be determined roughly whether a certain temperature sensor 110 is faulty, and for some complex scenarios, such as when a heating measure is performed inside the system, a false determination may occur. Additionally, this does not ensure that ranging system 100 is functioning properly after temperature sensor 110 has failed.

Therefore, the temperature data processing method of the embodiment of the application provides a plurality of schemes for determining whether abnormal data exists in a plurality of temperatures. Next, the plurality of schemes for determining whether there is abnormal data in the plurality of temperatures will be explained and explained.

Referring to fig. 17, in some embodiments, step S12 includes:

step S124: calculating a temperature change rate of each temperature sensor 110 according to the plurality of temperatures;

step S125: and determining whether abnormal data exist in the plurality of temperatures according to the temperature change rate.

In certain embodiments, processor 102 is configured to calculate a rate of change of temperature for each temperature sensor 110 based on a plurality of temperatures; and determining whether there is abnormal data in the plurality of temperatures according to the temperature change rate.

In this manner, a determination is made as to whether there is anomalous data in the plurality of temperatures. It will be appreciated that the rate of change of the temperature of each temperature sensor 110 may reflect the change in temperature of that temperature sensor 110 over time. In the ranging system 100, the rate of change in the temperature detected by each temperature sensor 110 in the normal state is stable due to the specific heat capacity. When the temperature sensor 110 is damaged, the temperature detected by the temperature sensor may sharply increase or decrease, that is, the temperature change rate thereof may abruptly change. Therefore, it is possible to determine whether there is abnormal data in the plurality of temperatures according to the temperature change rate.

Referring to fig. 18, in some embodiments, step S125 includes:

step S1251: determining whether each rate of temperature change is within a first preset range of change;

step S1252: when each temperature change rate is within a first preset change range, determining that abnormal data do not exist in the plurality of temperatures;

step S1253: determining that abnormal data exists in the plurality of temperatures when at least one temperature change rate is not within a first preset change range; and the temperature corresponding to the temperature change rate which is not in the first preset change range is abnormal data.

In some embodiments, the processor 102 is configured to determine whether each rate of temperature change is within a first preset range of change; and determining that there is no abnormal data in the plurality of temperatures when each temperature change rate is within a first preset change range; and determining that there is abnormal data in the plurality of temperatures when the at least one temperature change rate is not within a first preset change range; and the temperature corresponding to the temperature change rate which is not in the first preset change range is abnormal data.

In this way, whether abnormal data exist in the plurality of temperatures is determined according to the temperature change rate. It is understood that in the distance measuring system 100, the change rate of the temperature detected by each temperature sensor 110 in the normal state may fluctuate, in the embodiment of the present application, the fluctuation of the temperature change rate in the first preset change range is considered as normal, if the temperature change rate of the temperature sensor 110 exceeds the first preset change range, it may be determined that the temperature sensor 110 is abnormal, and the temperature of which the temperature change rate exceeds the first preset change range is considered as abnormal data.

Specifically, the first preset variation range may be determined through experiments and stored in the memory 101 or other storage medium, and the processor 102 may read the first preset variation range directly from the memory 101 or other storage medium when determining whether each temperature change rate is within the first preset variation range.

Of course, the history curves of the temperature change rate under various conditions, such as the ambient temperature rise and fall, the internal heat generation of the system, and the measures for starting the heat dissipation, may also be stored in the memory 101 or other storage media, and the processor 102 may process and analyze the history data to obtain the first preset change range.

In one example, the upper and lower limits of the temperature change rate of each temperature sensor 110, that is, the first preset change range thereof, can be obtained by analyzing the historical curves of the temperature change rate under various conditions, such as ambient temperature increase, ambient temperature decrease, system internal heating, and heat dissipation measures. When the system works, if the change rate of a certain temperature sensor 110 exceeds the first preset change range, the temperature sensor 110 can be determined to be abnormal, and the temperature with the temperature change rate exceeding the first preset change range is abnormal data.

Similarly, the first preset variation range of each temperature sensor 110 may be different; the first preset variation ranges of some of the temperature sensors 110 in the plurality of temperature sensors 110 may be the same, and some of the first preset variation ranges may be different; the first preset variation ranges of the plurality of temperature sensors 110 may all be the same. The relationship between the first preset variation ranges of the plurality of temperature sensors 110 is not limited herein.

Referring to fig. 19, in some embodiments, step S12 includes:

step S126: calculating a first difference between any two of the plurality of temperatures;

step S127: whether abnormal data exists in the plurality of temperatures is determined according to the first difference.

In some embodiments, the processor 102 is configured to calculate a first difference between any two of the plurality of temperatures; and determining whether there is abnormal data in the plurality of temperatures according to the first difference.

In this manner, a determination is made as to whether there is anomalous data in the plurality of temperatures. It is understood that in the distance measuring system 100, the temperature measured by each temperature sensor 110 at the same time in the normal state is stable, and therefore, in the normal state, the first difference between the temperatures detected by any two temperature sensors 110 in the plurality of temperature sensors 110 at the same time should also be stable. Therefore, whether there is abnormal data in the plurality of temperatures can be determined by the first difference of the temperatures detected by any two temperature sensors 110 of the plurality of temperature sensors 110 at the same time.

Referring to fig. 20, in some embodiments, step S127 includes:

step S1271: determining whether the first difference is within a first preset difference range;

step S1272: determining that the two temperatures used to calculate the first difference are not abnormal data when the first difference is within a first preset difference range;

step S1273: and determining that abnormal data exists in the plurality of temperatures when the first difference is not within the first preset difference range.

In some embodiments, the processor 102 is configured to determine whether the first difference is within a first preset difference range; and for determining that the two temperatures used to calculate the first difference are not anomalous data when the first difference is within a first preset difference range; and determining that there is abnormal data in the plurality of temperatures when the first difference is not within the first preset difference range.

In this manner, determining whether there is abnormal data in the plurality of temperatures according to the first difference is achieved. It is understood that in the distance measuring system 100, the first difference between the two temperature sensors 110 may fluctuate in the normal state, and in the embodiment of the present application, the fluctuation of the first difference within the first preset difference range is considered as normal. If the first difference between two temperature sensors 110 is beyond the first predetermined difference range, it can be determined that there is abnormal data in the plurality of temperatures.

Specifically, the first preset difference range may be determined through experiments and stored in the memory 101 or other storage medium, and the processor 102 may directly read the first preset difference range from the memory 101 or other storage medium when determining whether each first difference is within the first preset difference range.

Further, the first difference of the two temperatures may refer to a difference of the two temperatures. In one example, the distance measuring system 100 has 5 temperature sensors 110, and by analyzing the temperature difference values of every two temperature sensors 110 in the 5 temperature sensors 110 in the entire temperature range of the distance measuring system 100, the upper and lower temperature difference limits of every two temperature sensors 110 in the 5 temperature sensors 110 in normal operation, that is, the first preset difference range, can be obtained. When the distance measuring system 100 is in operation, if the temperature difference between two temperature sensors 110 exceeds a first preset difference range of the two temperature sensors 110, abnormal data among a plurality of temperatures is determined.

Similarly, the first preset difference ranges of each two temperature sensors 110 may be different; in the first preset difference range of every two temperature sensors 110, some of the first preset difference ranges may be the same, and some of the first preset difference ranges may be different; the first preset difference ranges of every two temperature sensors 110 may be all the same. The relationship between the first preset difference ranges of each two temperature sensors 110 is not limited herein.

In certain embodiments, step S1273 comprises:

taking two temperatures used for calculating the first difference as two first predetermined data;

when a first difference between one of the first data to be determined and at least one of the plurality of temperatures is within a first preset difference range, another one of the first data to be determined is determined to be anomalous data.

In some embodiments, the processor 102 is configured to use two temperatures for calculating the first difference as the two first predetermined data; and determining another first predetermined data as abnormal data when a first difference between the one first predetermined data and at least one of the plurality of temperatures is within a first preset difference range.

In this way, when the first difference is not within the first preset difference range, abnormal data in the plurality of temperatures is determined. It is understood that, in general, it is rare that a plurality of temperature sensors 110 among the plurality of temperature sensors 110 are abnormal at the same time, that is, when abnormality determination is performed, the number of abnormal temperature sensors 110 is generally smaller than the number of normal temperature sensors 110. And the difference between the normal data and the normal data is within a first preset difference range.

In addition, when the first difference is not within the first preset difference range, it may be that both the two temperatures used for calculating the first difference are abnormal data, or that one of the two temperatures used for calculating the difference is abnormal data.

Therefore, when the difference between one of the first predetermined data and at least one of the plurality of temperatures is within the first preset difference range, it can be estimated that the other first predetermined data is determined to be abnormal data.

In one example, the laser ranging system 100 has 5 temperature sensors 110, which are respectively: temperature sensor TS1, temperature sensor TS2, temperature sensor TS3, temperature sensor TS4, and temperature sensor TS5, wherein a first difference between temperatures detected by temperature sensor TS1 and temperature sensor TS2 is 5 ℃, a first preset difference range between temperature sensor TS1 and temperature sensor TS2 is 1 ℃ to 4 ℃, and a first difference between temperatures detected by temperature sensor TS1 and temperature sensor TS2 is not within the first preset difference range, it may be determined that there is abnormal data among the plurality of temperatures.

And a first difference between the temperatures detected by the temperature sensor TS1 and the temperature sensor TS3, a first difference between the temperatures detected by the temperature sensor TS1 and the temperature sensor TS4, and a first difference between the temperatures detected by the temperature sensor TS1 and the temperature sensor TS5 are not within the corresponding first preset difference range.

Meanwhile, a first difference between temperatures detected by the temperature sensor TS2 and the temperature sensor TS3, a first difference between temperatures detected by the temperature sensor TS2 and the temperature sensor TS4, and a first difference between temperatures detected by the temperature sensor TS2 and the temperature sensor TS5 are within a corresponding first preset difference range.

It may be determined that temperature sensor TS1 is abnormal and the temperature measured by temperature sensor TS1 is abnormal data.

Referring to fig. 21, in some embodiments, step S12 includes:

step S128: determining temperature rise data for each temperature sensor 110 from the plurality of temperatures;

step S129: and determining whether abnormal data exist in the plurality of temperatures according to the temperature rise data.

In some embodiments, the processor 102 is configured to determine temperature rise data for each temperature sensor 110 based on a plurality of temperatures; and determining whether there is abnormal data in the plurality of temperatures according to the temperature rise data.

In this manner, a determination is made as to whether there is anomalous data in the plurality of temperatures. As previously mentioned, the temperature rise is the difference between the temperature sensed by the temperature sensor 110 and the ambient temperature. It is understood that when the temperature detected by the temperature sensor 110 is abnormal, the difference between the temperature detected by the temperature sensor 110 and the ambient temperature is also abnormal, and therefore, whether abnormal data exists in the plurality of temperatures can be determined according to the temperature rise data.

In some embodiments, the temperature rise data includes the current actual temperature rise for each temperature sensor 110, or the current actual temperature rise for each temperature sensor 110 and a standard temperature rise.

That is, whether there is abnormal data in the plurality of temperatures may be determined according to the current actual temperature rise of each temperature sensor 110, or whether there is abnormal data in the plurality of temperatures may be determined according to the current actual temperature rise of each temperature sensor 110 and the standard temperature rise.

Referring to fig. 22, in some embodiments, step S128 includes:

step S1281: acquiring the current ambient temperature through an ambient temperature sensor 200;

step S1282: determining the actual temperature rise of each temperature sensor 110 according to the plurality of temperatures and the current ambient temperature, and determining the standard temperature rise of each temperature sensor 110 at the current ambient temperature according to preset temperature data, wherein the preset temperature data comprises a first corresponding relation between the ambient temperature and the standard temperature rise of each temperature sensor 110;

step S129 includes:

step S1291: and determining whether abnormal data exist in the plurality of temperatures according to the difference between the actual temperature rise and the standard temperature rise.

In some embodiments, the processor 102 is configured to obtain a current ambient temperature via the ambient temperature sensor 200; and a temperature sensor for determining an actual temperature rise of each temperature sensor 110 according to the plurality of temperatures and the current ambient temperature, and determining a standard temperature rise of each temperature sensor 110 at the current ambient temperature according to preset temperature data, the preset temperature data including a first corresponding relationship between the ambient temperature and the standard temperature rise of each temperature sensor 110; and determining whether there is abnormal data in the plurality of temperatures according to the difference between the actual temperature rise and the standard temperature rise.

In this way, it is achieved that the determination of whether there is abnormal data in the plurality of temperatures is made based on the current actual temperature rise and the standard temperature rise of each temperature sensor 110. Specifically, the first correspondence of the ambient temperature to the standard temperature rise of each temperature sensor 110 may be stored in the memory 101 in a form such as a table. When the standard temperature rise of each temperature sensor 110 at the current ambient temperature is determined according to the preset temperature data, the first corresponding relation table of each temperature sensor 110 may be searched according to the current ambient temperature, so as to determine the standard temperature rise of each temperature sensor 110 at the current ambient temperature.

Of course, the most reliable temperature sensor 110 may be used as the main control temperature sensor according to the reliability of the plurality of temperature sensors 110, the temperature detected by the main control temperature sensor may be used as the main control temperature, and the standard temperature rise of each of the other temperature sensors 110 may be found according to the main control temperature and the preset temperature data. It is understood that in this case, the preset temperature data may include a correspondence between the master temperature and the standard temperature rises of the other respective temperature sensors 110.

It can be understood that, in a normal state, the actual temperature rise of each temperature sensor 110 in the current environment is stable. Therefore, in a normal state, the difference between the actual temperature rise and the standard temperature rise of each temperature sensor 110 should also be stable. Based on this, whether there is abnormal data in a plurality of temperatures can be determined through the difference between the actual temperature rise and the standard temperature rise.

In some embodiments, the temperature data processing method is used in the distance measuring system 100, the plurality of temperature sensors 110 are disposed inside the distance measuring system 100, and the ambient temperature sensor 200 is disposed outside the distance measuring system 100.

It can be understood that, since the plurality of temperature sensors 110 are all disposed inside the distance measuring system 100 and the environment temperature sensor 200 is disposed outside the distance measuring system 100, the temperature of the environment where the distance measuring system 100 is currently located can be directly obtained through the environment temperature sensor 200 and taken as the current environment temperature. Therefore, the current environment temperature can be conveniently, quickly and accurately acquired.

Referring to fig. 23, in some embodiments, step S1291 includes:

step S1292: determining whether the difference is within a preset difference range;

step S1293: determining that no abnormal data exists in the plurality of temperatures when each difference is within a preset difference range;

step S1294: determining abnormal data in the plurality of temperatures when at least one difference is not within a preset difference range; wherein, the temperature corresponding to the difference not in the difference range is abnormal data.

In some embodiments, the processor 102 is configured to determine whether the gap is within a predetermined gap range; and determining that there is no abnormal data in the plurality of temperatures when each difference is within a preset difference range; and determining abnormal data in the plurality of temperatures when the at least one difference is not within a preset difference range; wherein, the temperature corresponding to the difference not in the difference range is abnormal data.

Therefore, whether abnormal data exist in the plurality of temperatures or not is determined according to the difference between the actual temperature rise and the standard temperature rise. It can be understood that in the distance measuring system 100, in a normal state, the difference between the actual temperature rise and the standard temperature rise of each temperature sensor 110 may fluctuate, and in the embodiment of the present application, the fluctuation of the difference within the preset difference range is regarded as normal. If the difference between the actual temperature rise and the standard temperature rise of a certain temperature sensor 110 is beyond the preset difference range, it can be determined that the temperature sensor 110 is abnormal, and the temperature measured by the temperature sensor 110 is abnormal data.

Similarly, the preset gap range may be determined by experiment and stored in the memory 101, and the processor 102 may directly read the preset gap range from the memory 101 when determining whether the gap is within the preset gap range.

Of course, it is also possible to store the temperature history curves of the plurality of temperature sensors 110 shown in fig. 5 in the memory 101, and process and analyze the temperature history curves by the processor 102, so as to obtain the preset difference range.

Referring to fig. 24, in some embodiments, step S1291 includes:

step S1295: calculating the temperature rise change rate of each temperature sensor 110 according to the difference;

step S1296: and determining whether abnormal data exist in the plurality of temperatures according to the temperature rise change rate.

In some embodiments, the processor 102 is configured to calculate a rate of change of temperature rise for each temperature sensor 110 based on the difference; and determining whether there is abnormal data in the plurality of temperatures according to the rate of change of the temperature rise.

Therefore, whether abnormal data exist in the plurality of temperatures or not is determined according to the difference between the actual temperature rise and the standard temperature rise. It will be appreciated that the rate of change of temperature rise of each temperature sensor 110 can reflect the change in temperature rise of that temperature sensor 110 over time. In the ranging system 100, the rate of change in the temperature rise detected by each temperature sensor 110 in the normal state is generally stable due to the specific heat capacity. When the temperature sensor 110 is suddenly damaged, the detected temperature thereof will be sharply increased or decreased, and the temperature rise rate thereof will also be abruptly changed. Therefore, it is possible to determine whether there is abnormal data in the plurality of temperatures according to the rate of change of temperature rise.

Referring to fig. 25, in some embodiments, step S1296 includes:

step S1297: determining whether each temperature rise change rate is within a second preset change range;

step S1298: when each temperature rise change rate is within a second preset change range, determining that no abnormal data exists in the plurality of temperatures;

step S1299: when at least one temperature rise change rate is not within a second preset change range, determining that abnormal data exist in the plurality of temperatures; and the temperature corresponding to the temperature rise change rate which is not in the second preset change range is abnormal data.

In some embodiments, the processor 102 is configured to determine whether each rate of change of temperature rise is within a second predetermined range of change; and determining that no abnormal data exists in the plurality of temperatures when each temperature rise change rate is within a second preset change range; and determining that there is abnormal data in the plurality of temperatures when the at least one temperature rise change rate is not within a second preset change range; and the temperature corresponding to the temperature rise change rate which is not in the second preset change range is abnormal data.

Therefore, whether abnormal data exist in the plurality of temperatures or not is determined according to the temperature rise change rate. It can be understood that in the distance measuring system 100, the temperature rise change rate of the temperature detected by each temperature sensor 110 in the normal state may fluctuate, in the embodiment of the present application, the fluctuation of the temperature rise change rate in the second preset change range is considered as normal, and if the temperature rise change rate of the temperature sensor 110 exceeds the second preset change range, it may be determined that the temperature sensor 110 is abnormal, and the temperature of which the temperature rise change rate exceeds the second preset change range is abnormal data.

Specifically, the second preset variation range may be determined through experiments and stored in the memory 101, and the processor 102 may directly read the second preset variation range from the memory 101 when determining whether each temperature rise variation rate is within the second preset variation range.

Similarly, the second preset variation range of each temperature sensor 110 may be different, the second preset variation ranges of some temperature sensors 110 in the plurality of temperature sensors 110 may be the same, and the second preset variation ranges of the plurality of temperature sensors 110 may be all the same. The relationship between the second preset variation ranges of the plurality of temperature sensors 110 is not limited herein.

Referring to fig. 26, in some embodiments, step S12 includes:

step S12 a: calculating a second difference between any two of the plurality of differences;

step S12 b: determining whether there is abnormal data in the plurality of temperatures according to the second difference.

In some embodiments, the processor 102 is configured to calculate a second difference between any two of the plurality of gaps; and determining whether there is abnormal data in the plurality of temperatures according to the second difference.

In this manner, a determination is made as to whether there is anomalous data in the plurality of temperatures. It can be understood that in the distance measuring system 100, in a normal state, the temperature rise of each temperature sensor 110 is stable in the same time period, and then the difference between the actual temperature rise and the standard temperature rise of each temperature sensor 110 is also stable in the same time period. Therefore, in a normal state, the second difference of the gap of any two temperature sensors 110 of the plurality of temperature sensors 110 should also be stable. Accordingly, it is possible to determine whether there is abnormal data in the plurality of temperatures based on the second difference.

Referring to fig. 27, in some embodiments, step S12b includes:

step S12b 1: determining whether the second difference is within a second preset difference range;

step S12b 2: when the second difference is within a second preset difference range, determining that the temperatures corresponding to the two differences for calculating the second difference are not abnormal data;

step S12b 3: and determining that abnormal data exists in the plurality of temperatures when the second difference is not within the second preset difference range.

In some embodiments, the processor 102 is configured to determine whether the second difference is within a second preset difference range; and determining that the temperatures corresponding to the two differences for calculating the second difference are not abnormal data when the second difference is within a second preset difference range; and determining that there is abnormal data in the plurality of temperatures when the second difference is not within a second preset difference range.

In this manner, determination of whether there is abnormal data in the plurality of temperatures based on the second difference is achieved. It is understood that in the distance measuring system 100, the second difference between the two temperature sensors 110 may fluctuate in the normal state, and in the embodiment of the present application, the fluctuation of the second difference within the second preset difference range is considered as normal. If the second difference between two temperature sensors 110 is beyond the second predetermined difference range, it can be determined that there is abnormal data in the plurality of temperatures.

Specifically, the second preset difference range may be determined through experiments and stored in the memory 101, and the processor 102 may directly read the second preset difference range from the memory 101 when determining whether the second difference is within the second preset difference range.

Further, the second difference of the two temperatures may refer to a difference between the difference of the actual temperature rise and the standard temperature rise of the two temperature sensors.

In certain embodiments, step S12b3 includes:

taking the two differences used for calculating the second difference as two second pending data;

and when a second difference between one of the second undetermined data and at least one of the plurality of differences is within a second preset difference range, determining the temperature corresponding to the other second undetermined data as abnormal data.

In some embodiments, the processor 102 is configured to use the two differences for calculating the second difference as two second pending data; and the temperature corresponding to the other second undetermined data is determined as abnormal data when a second difference between one of the second undetermined data and at least one of the plurality of differences is within a second preset difference range.

In this way, it is achieved that the abnormal data in the plurality of temperatures is determined when the second difference is not within the second preset difference range. The method for determining the abnormal data in the plurality of temperatures when the second difference is not within the second preset difference range is similar to the method for determining the abnormal data in the plurality of temperatures when the first difference is not within the first preset difference range, and is not described herein again to avoid redundancy.

Referring to fig. 28, in some embodiments, a method for processing temperature data includes:

step S18: when abnormal data exists in a plurality of temperatures, the abnormal data is specially marked.

In some embodiments, processor 102 is configured to specifically mark anomalous data in a plurality of temperatures.

In this way, the marking of the abnormal data is realized. Specifically, each temperature may be provided with a flag bit, each temperature defaults to normal, and when there is abnormal data among a plurality of temperatures, the flag bit of the abnormal data is set to abnormal.

In one example, the flag bit of each temperature is set to 1 by default to indicate that the temperature is normal, and when there is abnormal data among a plurality of temperatures, the flag bit of the abnormal data is set to 0 to indicate that the temperature is abnormal data.

Of course, the flag bit for each temperature may be set to 0 by default to indicate that the temperature is normal, and when there is abnormal data among a plurality of temperatures, the flag bit for the abnormal data may be set to 1 to indicate that the temperature is abnormal data. The specific form of marking the abnormal data is not limited herein.

Similarly, when there is abnormal data among a plurality of temperatures, the temperature sensor 110 corresponding to the abnormal data may be specifically marked. Specifically, each temperature sensor 110 may be provided with an identifier, each temperature sensor 110 defaults to normal, and when there is abnormal data in a plurality of temperatures, the identifier of the temperature sensor 110 corresponding to the abnormal data is set to abnormal.

In one example, the identifier of each temperature sensor 110 defaults to "correct" to indicate that the temperature sensor 110 is normal, and when there is abnormal data in a plurality of temperatures, the identifier of the temperature sensor 110 corresponding to the abnormal data is set to "error" to indicate that the temperature sensor 110 is abnormal.

Referring to fig. 29, in some embodiments, the temperature data processing method further includes:

step S19: when abnormal data exists in a plurality of temperatures, warning information is sent out.

In some embodiments, processor 102 is configured to issue a warning message when there is abnormal data among the plurality of temperatures.

Thus, the indication that abnormal data exists in a plurality of temperatures is realized. Specifically, when there is abnormal data in a plurality of temperatures, the processor 102 may issue a warning message to the relevant components in the ranging system 100, and the relevant components may take corresponding measures after receiving the warning message. Of course, the processor 102 may also send warning information to the server so that the server can know and record the temperature data in the ranging system 100 in time. The object of sending the warning information is not limited herein.

Note that, in the example shown in fig. 29, step S19 follows step S13. It is understood that, in other examples, step S19 may be performed before step S13 or simultaneously with step S13. The order relationship of step S19 in step S13 is not limited herein.

That is, when abnormal data exists in a plurality of temperatures, confidence data of the abnormal data can be determined according to preset temperature data, and then alarm information can be sent; or firstly sending out warning information, and then determining confidence data of abnormal data according to preset temperature data; the confidence data of the abnormal data can be determined according to the preset temperature data while the warning information is sent out.

Referring to fig. 30, in some embodiments, the temperature data processing method further includes:

step S20: determining whether the detection data of the temperature sensor 110 corresponding to the abnormal data within the preset time length is normal;

step S21: when the detected data does not return to normal within the preset time, closing the temperature sensor 110 corresponding to the abnormal data;

step S22: and when the detected data is recovered to be normal within the preset time length, warning clearing information is sent.

In some embodiments, the processor 102 is configured to determine whether the detected data of the temperature sensor 110 corresponding to the abnormal data within a preset time period returns to normal; and a temperature sensor 110 for turning off the temperature sensor corresponding to the abnormal data when the detected data is not restored to normal within a preset time; and the alarm clearing information is sent out when the detection data are recovered to be normal within the preset time length.

In this way, the temperature sensor 110 that has continuously abnormal detected temperature may be turned off, and a warning may be prompted to clear after the abnormal temperature sensor 110 has detected normal temperature. It can be understood that, when the detected data does not return to normal within the preset time period, it can be estimated that the temperature abnormality detected by the temperature sensor 110 corresponding to the detected data is not accidental and is not suitable for resuming the operation. Accordingly, the temperature sensor 110 corresponding to the abnormal data may be turned off, thereby preventing the ranging system 100 from being damaged. When the detected data is recovered to be normal within the preset time period, it can be estimated that the temperature abnormality detected by the temperature sensor 110 corresponding to the detected data is accidental, and the operation can be continued after the detected data is recovered to be normal.

Similarly, processor 102 may send alert clearance information to relevant components and/or servers in ranging system 100. Further, the processor 102 may send alert clearance information to the object that received the corresponding alert information.

Referring to fig. 31, in some embodiments, the temperature data processing method further includes:

step S23: and when the detected data are not recovered to be normal within the preset time length, sending out error information of the temperature sensor 110 corresponding to the abnormal data.

In some embodiments, the processor 102 is configured to send out an error message for the temperature sensor 110 corresponding to the abnormal data when the detected data is not normal within a preset time period.

In this way, an error of the temperature sensor 110 corresponding to the abnormal data is presented. Similarly, the processor 102 may send error information to the relevant components and/or servers in the ranging system 100 to make the relevant components and/or servers in the ranging system 100 aware of the current status of each temperature sensor 110 in the ranging system 100.

Note that, in the example shown in fig. 31, step S23 follows step S21. It is understood that, in other examples, step S23 may be performed before step S21 or simultaneously with step S21. The order relationship between step S23 and step S21 is not limited.

That is, when the detected data is not restored to normal within the preset duration, the temperature sensor 110 corresponding to the abnormal data may be turned off first, and then the error information for the temperature sensor 110 corresponding to the abnormal data may be sent out; or sending error information of the temperature sensor 110 corresponding to the abnormal data first, and then closing the temperature sensor 110 corresponding to the abnormal data; it is also possible to turn off the temperature sensor 110 corresponding to abnormal data while issuing error information for the temperature sensor 110 corresponding to abnormal data.

Referring to fig. 32, an embodiment of the present application provides a mobile terminal 1000. The mobile terminal 1000 according to the embodiment of the present application includes the ranging system 100 described above.

In some embodiments, mobile terminal 1000 includes a drone or a robot. The mobile terminal 1000 shown in fig. 32 is a mobile robot. It is understood that in other embodiments, the mobile terminal 1000 may be another mobile terminal such as a mobile cart.

In addition, mobile terminal 1000 may be a product that performs ranging in accordance with lidar, laser ranging, or other time-of-flight (TOF) based techniques.

In summary, the temperature data processing method, the temperature data processing apparatus 10, the ranging system 100, and the mobile terminal 1000 according to the embodiments of the present application provide a temperature sensor abnormality detection and control scheme for the ranging system 100 with the built-in multi-channel temperature sensor 110 for performing temperature measurement and precision compensation, so that the ranging system can still work normally as much as possible when one or more signals are abnormal. Specifically, multiple strategies are adopted to judge whether the temperature sensor 110 is abnormal, and after a certain temperature sensor 110 has an error, a confidence temperature is comprehensively calculated according to the temperatures of other temperature sensors 110 to replace an error value, so that the abnormality of the temperature sensor 110 can be more accurately identified, and the normal working state can be still maintained as much as possible after the abnormality occurs, thereby improving the reliability of the distance measuring system 100, and avoiding starting an erroneous temperature compensation measure due to the abnormality of the temperature sensor 110 and damaging devices or the distance measuring system 100.

In the description herein, references to the description of the terms "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps in the process, and the scope of the preferred embodiments of the present application includes additional implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.

The logic and/or steps represented in the flowcharts or otherwise described herein, such as an ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.

It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, various steps or methods may be performed by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for performing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

It will be understood by those skilled in the art that all or part of the steps carried out in the method of implementing the above embodiments may be implemented by hardware associated with instructions of a program, which may be stored in a computer-readable storage medium, and which, when executed, includes one or a combination of the steps of the method embodiments.

In addition, each functional unit in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be executed in the form of hardware or in the form of a software functional module. The integrated module, if executed in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.

The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is to be understood that the above embodiments are exemplary and not to be construed as limiting the present application, and that changes, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.

Claims

A temperature data processing method, characterized in that the temperature data processing method comprises:

acquiring a plurality of temperatures detected by a plurality of temperature sensors;

determining whether there is anomalous data in the plurality of temperatures;

and when the abnormal data exist in the plurality of temperatures, determining confidence data of the abnormal data according to preset temperature data.
The temperature data processing method according to claim 1, further comprising:

and performing temperature compensation according to normal data and the confidence data in the plurality of temperatures.
The temperature data processing method as claimed in claim 2, wherein before the temperature compensation based on the normal data and the confidence data in the plurality of temperatures, the temperature data processing method further comprises:

verifying whether the confidence data is normal;

when the confidence data is normal, the step of performing temperature compensation according to the normal data and the confidence data in a plurality of temperatures is carried out;

and when the confidence data are abnormal, performing temperature compensation according to normal data in the plurality of temperatures.
The method of processing temperature data according to claim 3, wherein said verifying said confidence data is normal comprises:

determining whether the confidence data is normal based on normal data in a plurality of the temperatures.
The temperature data processing method according to claim 1, further comprising:

and adjusting the temperature in the detection range of the temperature sensor corresponding to the abnormal data according to the confidence data.
The temperature data processing method according to claim 1, wherein the preset temperature data includes a first correspondence of an ambient temperature and a standard temperature rise of each of the temperature sensors, the temperature data processing method further comprising:

acquiring the current environment temperature;

the determining confidence data of the abnormal data according to the preset temperature data comprises the following steps:

determining the standard temperature rise of the temperature sensor corresponding to the abnormal data according to the current environment temperature and the first corresponding relation;

and determining the confidence data according to the current environment temperature and the standard temperature rise of the temperature sensor corresponding to the abnormal data.
The temperature data processing method of claim 6, wherein obtaining the current ambient temperature comprises:

and acquiring the current ambient temperature through an ambient temperature sensor.
The temperature data processing method according to claim 6, wherein the preset temperature data includes a second corresponding relationship between the temperature of each of the temperature sensors and a standard temperature rise, and the obtaining of the current ambient temperature includes:

acquiring standard temperature rise of the temperature sensor corresponding to the normal data according to the normal data in the plurality of temperatures and the second corresponding relation;

and determining the current environment temperature according to the normal data, the standard temperature rise of the temperature sensor corresponding to the normal data and the confidence weight of the temperature sensor corresponding to the normal data.
The temperature data processing method according to claim 8, further comprising:

and adjusting the confidence weight of the temperature sensor corresponding to the normal data in real time according to the change of the temperature sensor corresponding to the normal data.
The temperature data processing method according to claim 8, further comprising:

and when the heating measure or the heat dissipation measure is executed in the detection range of the temperature sensor corresponding to the normal data, the confidence weight of the temperature sensor corresponding to the normal data is adjusted.
The method of processing temperature data according to claim 1, wherein said determining whether there is abnormal data in a plurality of said temperatures comprises:

determining whether each of said plurality of temperatures is within a preset temperature range;

determining that there is no abnormal data in the plurality of temperatures when each of the temperatures is within the preset temperature range;

determining that there is the abnormal data in a plurality of the temperatures when at least one of the temperatures is not within the preset temperature range;

wherein a temperature out of the plurality of temperatures that is not within the preset temperature range is the abnormal data.
The method of processing temperature data according to claim 1, wherein said determining whether there is abnormal data in a plurality of said temperatures comprises:

calculating a temperature change rate of each temperature sensor according to a plurality of temperatures;

and determining whether abnormal data exist in the plurality of temperatures according to the temperature change rate.
The method of processing temperature data according to claim 12, wherein said determining whether there is abnormal data in a plurality of said temperatures according to said rate of temperature change comprises:

determining whether each of the temperature change rates is within a first preset change range;

determining that there is no abnormal data in the plurality of temperatures when each of the temperature change rates is within the first preset change range;

when at least one temperature change rate is not within the first preset change range, determining that abnormal data exist in a plurality of temperatures;

and the temperature corresponding to the temperature change rate which is not in the first preset change range is the abnormal data.
The method of processing temperature data according to claim 1, wherein said determining whether there is abnormal data in a plurality of said temperatures comprises:

calculating a first difference between any two of said temperatures in the plurality of said temperatures;

and determining whether abnormal data exists in the plurality of temperatures according to the first difference.
The method of processing temperature data according to claim 14, wherein said determining whether there is abnormal data in a plurality of said temperatures based on said first difference comprises:

determining whether the first difference is within a first preset difference range;

determining that the two temperatures used to calculate the first difference are not the anomaly data when the first difference is within the first preset difference range;

and when the first difference is not within the first preset difference range, determining that the abnormal data exists in the plurality of temperatures.
The method of processing temperature data according to claim 15, wherein said determining that there is anomalous data in said plurality of temperatures comprises:

taking the two temperatures used for calculating the first difference as two first predetermined data;

when the difference between one of the first pending data and at least one of the plurality of temperatures is within the first preset difference range, determining the other first pending data as the abnormal data.
The method of processing temperature data according to claim 1, wherein determining whether there is anomalous data in the plurality of temperatures comprises:

determining temperature rise data for each of said temperature sensors based on a plurality of said temperatures;

and determining whether abnormal data exist in the plurality of temperatures according to the temperature rise data.
The temperature data processing method according to claim 17, wherein the temperature rise data includes a current actual temperature rise of each of the temperature sensors, or a current actual temperature rise of each of the temperature sensors and a standard temperature rise.
The method of processing temperature data according to claim 18, wherein said determining temperature rise data for each of said temperature sensors based on a plurality of said temperatures comprises:

acquiring the current ambient temperature through an ambient temperature sensor;

determining the actual temperature rise of each temperature sensor according to the temperatures and the current ambient temperature, and determining the standard temperature rise of each temperature sensor at the current ambient temperature according to the preset temperature data, wherein the preset temperature data comprises a first corresponding relation between the ambient temperature and the standard temperature rise of each temperature sensor;

determining whether there is abnormal data in the plurality of temperatures according to the temperature rise data includes:

and determining whether abnormal data exist in the plurality of temperatures according to the difference between the actual temperature rise and the standard temperature rise.
The temperature data processing method according to claim 7 or 19, wherein the temperature data processing method is used for a ranging system, a plurality of the temperature sensors are provided inside the ranging system, and the ambient temperature sensor is provided outside the ranging system.
The method of processing temperature data according to claim 19, wherein said determining whether there is abnormal data in a plurality of said temperatures based on the difference between said actual temperature rise and said standard temperature rise comprises:

determining whether the difference is within a preset difference range;

determining that there is no abnormal data in the plurality of temperatures when each difference is within the preset difference range;

determining that there is the abnormal data in the plurality of temperatures when at least one of the differences is not within the preset difference range;

and the temperature corresponding to the difference which is not in the difference range is the abnormal data.
The method of processing temperature data according to claim 19, wherein said determining whether there is abnormal data in a plurality of said temperatures based on the difference between said actual temperature rise and said standard temperature rise comprises:

calculating the temperature rise change rate of each temperature sensor according to the difference;

and determining whether abnormal data exist in the plurality of temperatures according to the temperature rise change rate.
The method for processing temperature data according to claim 22, wherein said determining whether there is abnormal data in a plurality of said temperatures according to said rate of change of temperature rise comprises:

determining whether each temperature rise change rate is within a second preset change range;

determining that there is no abnormal data in the plurality of temperatures when each of the temperature rise change rates is within the second preset change range;

determining that there is the abnormal data in the plurality of temperatures when at least one of the temperature rise change rates is not within the second preset change range;

and the temperature corresponding to the temperature rise change rate which is not in the second preset change range is the abnormal data.
The method of processing temperature data according to claim 19, wherein said determining whether there is anomalous data in said plurality of temperatures comprises:

calculating a second difference between any two of the plurality of gaps;

determining whether there is the abnormal data in the plurality of temperatures according to the second difference.
The method of processing temperature data according to claim 24, wherein said determining whether there is abnormal data in a plurality of said temperatures based on said second difference comprises:

determining whether the second difference is within a second preset difference range;

when the second difference is within the second preset difference range, determining that the temperatures corresponding to the two differences for calculating the second difference are not the abnormal data;

and when the second difference is not within the second preset difference range, determining that the abnormal data exists in the plurality of temperatures.
The method of processing temperature data according to claim 25, wherein said determining that there is anomalous data in said plurality of temperatures comprises:

taking the two gaps used to calculate the second difference as two second pending data;

and when a second difference between one of the second pending data and at least one of the differences is within the second preset difference range, determining the temperature corresponding to the other second pending data as the abnormal data.
The temperature data processing method according to claim 1, characterized in that the temperature data processing method comprises:

when the abnormal data exists in a plurality of temperatures, the abnormal data is specially marked.
The temperature data processing method according to claim 1, further comprising:

and when the abnormal data exists in the plurality of temperatures, warning information is sent out.
The temperature data processing method of claim 28, further comprising:

determining whether the detection data of the temperature sensor corresponding to the abnormal data in a preset time length is normal or not;

when the detection data are not recovered to be normal within the preset time, closing the temperature sensor corresponding to the abnormal data;

and sending warning clearing information when the detection data is recovered to be normal within the preset time length.
The temperature data processing method according to claim 29, further comprising:

and sending error information of the temperature sensor corresponding to the abnormal data when the detection data is not recovered to be normal within the preset time.
A temperature data processing apparatus comprising a processor and a memory, the memory storing one or more programs, the processor configured to obtain a plurality of temperatures detected by a plurality of temperature sensors; and for determining whether there is anomalous data in the plurality of temperatures; and when the abnormal data exist in the plurality of temperatures, determining confidence data of the abnormal data according to preset temperature data.
The temperature data processing apparatus of claim 31, wherein the processor is further configured to perform temperature compensation based on normal data and the confidence data for a plurality of the temperatures.
The temperature data processing apparatus of claim 32, wherein the processor is further configured to verify that the confidence data is normal; and when the confidence data is normal, the step of performing temperature compensation according to the normal data and the confidence data in the plurality of temperatures is carried out; and the temperature compensation module is used for performing temperature compensation according to normal data in a plurality of temperatures when the confidence data are abnormal.
The temperature data processing apparatus of claim 33, wherein the processor is specifically configured to determine whether the confidence data is normal based on normal data in a plurality of the temperatures.
The temperature data processing apparatus of claim 31, wherein the processor is further configured to adjust a temperature within a detection range of the temperature sensor corresponding to the anomaly data based on the confidence data.
The temperature data processing apparatus of claim 31, wherein the preset temperature data comprises a first correspondence of an ambient temperature to a standard temperature rise of each of the temperature sensors, the processor further configured to obtain a current ambient temperature; the temperature sensor is specifically used for determining the standard temperature rise of the temperature sensor corresponding to the abnormal data according to the current environment temperature and the first corresponding relation; and the confidence data is specifically determined according to the current environment temperature and the standard temperature rise of the temperature sensor corresponding to the abnormal data.
The temperature data processing apparatus of claim 36, wherein the processor is specifically configured to obtain the current ambient temperature via an ambient temperature sensor.
The temperature data processing apparatus according to claim 36, wherein the preset temperature data includes a second corresponding relationship between the temperature of each of the temperature sensors and a standard temperature rise, and the processor is specifically configured to obtain the standard temperature rise of the temperature sensor corresponding to the normal data according to normal data in the plurality of temperatures and the second corresponding relationship; and the current environment temperature is determined according to the normal data, the standard temperature rise of the temperature sensor corresponding to the normal data and the confidence weight of the temperature sensor corresponding to the normal data.
The temperature data processing apparatus of claim 38, wherein the processor is further configured to adjust the confidence weight of the temperature sensor corresponding to the normal data in real time according to a change of the temperature sensor corresponding to the normal data.
The temperature data processing apparatus according to claim 38, wherein the processor is further configured to adjust the confidence weight of the temperature sensor corresponding to the normal data when the detection range of the temperature sensor corresponding to the normal data performs the heating measure or the heat dissipation measure.
The temperature data processing apparatus of claim 31, wherein the processor is specifically configured to determine whether each of the plurality of temperatures is within a preset temperature range; the method is specifically configured to determine that there is no abnormal data in the plurality of temperatures when each of the temperatures is within the preset temperature range; and specifically configured to determine that there is the abnormal data in the plurality of temperatures when at least one of the temperatures is not within the preset temperature range; wherein a temperature out of the plurality of temperatures that is not within the preset temperature range is the abnormal data.
The temperature data processing apparatus of claim 31, wherein the processor is specifically configured to calculate a rate of change of temperature for each of the temperature sensors based on a plurality of the temperatures; and specifically, determining whether there is abnormal data in the plurality of temperatures according to the temperature change rate.
The temperature data processing apparatus of claim 42, wherein the processor is specifically configured to determine whether each of the rates of temperature change is within a first preset range of variation; and specifically, when each of the temperature change rates is within the first preset change range, determining that there is no abnormal data in the plurality of temperatures; and specifically for determining that there is said abnormal data in a plurality of said temperatures when at least one of said rates of change of temperature is not within said first preset range of variation; and the temperature corresponding to the temperature change rate which is not in the first preset change range is the abnormal data.
The temperature data processing apparatus of claim 31, wherein the processor is specifically configured to calculate a first difference between any two of the plurality of temperatures; and in particular for determining whether there is anomalous data in the plurality of temperatures based on the first difference.
The temperature data processing apparatus of claim 44, wherein the processor is specifically configured to determine whether the first difference is within a first preset difference range; and in particular for determining that the two said temperatures used to calculate the first difference are not the anomaly data when the first difference is within the first preset difference range; and specifically, the method is used for determining that the abnormal data exists in the plurality of temperatures when the first difference is not within the first preset difference range.
The temperature data processing apparatus of claim 45, wherein the processor is specifically configured to treat two of the temperatures used to calculate the first difference as two first predetermined data; and the data processing device is specifically used for determining another first pending data as the abnormal data when the difference between one of the first pending data and at least one of the plurality of temperatures is within the first preset difference range.
The temperature data processing apparatus of claim 31, wherein the processor is specifically configured to determine temperature rise data for each of the temperature sensors based on a plurality of the temperatures; and specifically, determining whether there is abnormal data in the plurality of temperatures according to the temperature rise data.
The temperature data processing apparatus according to claim 47, wherein the temperature rise data comprises a current actual temperature rise of each of the temperature sensors, or a current actual temperature rise of each of the temperature sensors and a standard temperature rise.
The temperature data processing apparatus of claim 48, wherein the processor is specifically configured to obtain a current ambient temperature via an ambient temperature sensor; the temperature sensor is specifically used for determining the actual temperature rise of each temperature sensor according to the plurality of temperatures and the current environment temperature, and determining the standard temperature rise of each temperature sensor at the current environment temperature according to the preset temperature data, wherein the preset temperature data comprises a first corresponding relation between the environment temperature and the standard temperature rise of each temperature sensor; and specifically, the method is used for determining whether abnormal data exists in the plurality of temperatures according to the difference between the actual temperature rise and the standard temperature rise.
The temperature data processing apparatus of claim 37 or 49, wherein the temperature data processing apparatus is for a ranging system, a plurality of the temperature sensors are provided inside the ranging system, and the ambient temperature sensor is provided outside the ranging system.
The temperature data processing apparatus of claim 49, wherein the processor is specifically configured to determine whether the gap is within a predetermined gap range; and specifically, when each of the differences is within the preset difference range, determining that there is no abnormal data in the plurality of temperatures; and specifically configured to determine that there is the abnormal data in the plurality of temperatures when at least one of the differences is not within the preset difference range; and the temperature corresponding to the difference which is not in the difference range is the abnormal data.
The temperature data processing apparatus of claim 49, wherein the processor is further configured to calculate a rate of change of temperature rise for each of the temperature sensors based on the difference; and specifically for determining whether there is abnormal data in the plurality of temperatures according to the rate of change of the temperature rise.
The temperature data processing apparatus of claim 52, wherein said processor is specifically configured to determine whether each of said temperature rise rates of change are within a second predetermined range of change; and specifically, when each of the temperature rise change rates is within the second preset change range, determining that there is no abnormal data in the plurality of temperatures; and specifically configured to determine that there is the abnormal data in the plurality of temperatures when at least one of the temperature rise change rates is not within the second preset change range; and the temperature corresponding to the temperature rise change rate which is not in the second preset change range is the abnormal data.
The temperature data processing apparatus of claim 49, wherein the processor is further configured to calculate a second difference between any two of the plurality of differences; and in particular for determining whether there is said anomalous data in a plurality of said temperatures based on said second difference.
The temperature data processing apparatus of claim 54, wherein the processor is specifically configured to determine whether the second difference is within a second preset difference range; and specifically, when the second difference is within the second preset difference range, determining that the temperatures corresponding to the two differences used for calculating the second difference are not the abnormal data; and specifically, the method is used for determining that the abnormal data exists in the plurality of temperatures when the second difference is not within the second preset difference range.
The temperature data processing apparatus of claim 55, wherein the processor is specifically configured to treat the two differences used to calculate the second difference as two second pending data; and the temperature determination unit is specifically configured to determine, as the abnormal data, a temperature corresponding to another one of the second pending data when a second difference between one of the second pending data and at least one of the plurality of differences is within the second preset difference range.
The temperature data processing apparatus of claim 31, wherein the processor is further configured to specifically mark the anomalous data when there is the anomalous data in a plurality of the temperatures.
The temperature data processing apparatus of claim 31, wherein the processor is further configured to issue a warning message when there is the abnormal data in a plurality of the temperatures.
The temperature data processing device as claimed in claim 58, wherein the processor is further configured to determine whether the detected data of the temperature sensor corresponding to the abnormal data within a preset time period is normal; and the temperature sensor is also used for closing the temperature sensor corresponding to the abnormal data when the detection data does not return to normal within the preset time length; and the alarm clearing information is sent out when the detection data is recovered to be normal within the preset time length.
The temperature data processing device of claim 59, wherein the processor is further configured to send out an error message for the temperature sensor corresponding to the abnormal data when the detected data does not return to normal within the preset time period.
A ranging system comprising a plurality of temperature sensors arranged within the ranging system and a temperature data processing apparatus as claimed in any of claims 31 to 60.
A mobile terminal comprising the ranging system of claim 61.
The mobile terminal of claim 62, wherein the mobile terminal comprises a drone or a robot.