CN117719553A - Shaft temperature early warning and monitoring method and device, electronic equipment and readable storage medium - Google Patents
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Abstract
The disclosure provides a method, a device, electronic equipment and a storage medium for early warning and monitoring of shaft temperature, which can be applied to the technical field of rail transit. The shaft temperature early warning and monitoring method comprises the following steps: analyzing a shaft temperature data set from a sensor to obtain temperature rise rate data; determining a time interval from the first temperature rise rate to the second temperature rise rate according to the temperature rise rate data; under the condition that the length of the time interval is smaller than or equal to a preset threshold value, determining the shaft temperature data corresponding to the time interval in the shaft temperature data set as jump data; and carrying out early warning and monitoring according to other shaft temperature data except jump data in the shaft temperature data set.
Description
Technical Field
The disclosure relates to the technical field of rail transit, in particular to a shaft temperature early warning and monitoring method and device, electronic equipment and a readable storage medium.
Background
At present, during the running process of the high-speed motor train unit, the temperature of an axle box, a gear box or a motor bearing (hereinafter referred to as the axle temperature) is increased along with the increase of friction force. In order to ensure the safety of vehicles and personnel, the system needs to perform early warning and monitoring on the shaft temperature so as to prompt the personnel to stop the operation of the vehicles in time and check and maintain the vehicles.
However, in implementing the concepts of the present disclosure, the inventors found that there are at least the following problems in the related art: in an actual working state, false alarm is often caused by the temperature rise of a sensor fault or an unreal fault such as poor contact of a collecting line, and the running order of the motor train unit is influenced.
Disclosure of Invention
In view of the foregoing, the present disclosure provides improved shaft temperature warning monitoring methods, apparatus, devices, media, and program products.
A first aspect of the present disclosure provides a method for early warning and monitoring of shaft temperature, including: analyzing a shaft temperature data set from a sensor to obtain temperature rise rate data; determining a time interval from the first temperature rise rate to the second temperature rise rate according to the temperature rise rate data; under the condition that the length of the time interval is smaller than or equal to a preset threshold value, determining the shaft temperature data corresponding to the time interval in the shaft temperature data set as jump data; and carrying out early warning and monitoring according to other shaft temperature data except jump data in the shaft temperature data set.
According to an embodiment of the present disclosure, the method of the present disclosure further comprises: under the condition that the length of the time interval is greater than a preset threshold value, determining the shaft temperature data corresponding to the time interval in the shaft temperature data set as abnormal data; and under the condition that the performance state of the sensor is normal, early warning is carried out on abnormal data.
According to an embodiment of the present disclosure, determining a time interval from a first rate of temperature rise to a second rate of temperature rise based on temperature rise rate data includes: determining a first moment corresponding to the first temperature rise rate and a second moment corresponding to the second temperature rise rate in monotonically changing temperature rise rate data; the time interval between the first time and the second time is taken as a time interval for converting the first temperature rise rate into the second temperature rise rate.
According to the embodiment of the disclosure, the method is applied to vehicle operation detection, wherein one of the first temperature rise rate and the second temperature rise rate is a positive temperature rise rate used for predicting that the vehicle can normally operate, and the other is a maximum negative temperature rise rate obtained according to historical jump data statistics.
According to an embodiment of the present disclosure, analyzing the shaft temperature dataset from the sensor, obtaining temperature rise rate data includes: according to the shaft temperature data at different moments in the shaft temperature data set, calculating the temperature change rate of each moment relative to the previous moment, and obtaining temperature rise rate initial data; and carrying out smoothing treatment on the initial data of the temperature rise rate to obtain the data of the temperature rise rate.
According to an embodiment of the present disclosure, the shaft temperature dataset is a shaft temperature dataset of an axle box, a gearbox or a motor bearing; the method of the present disclosure further comprises: acquiring historical jump data and historical abnormal data which are consistent with mechanical characteristics of an axle box, a gear box or a motor bearing; and updating the preset threshold according to the historical jump data and the historical abnormal data.
According to an embodiment of the present disclosure, the preset threshold is 30 to 60 seconds.
A second aspect of the present disclosure provides an axle temperature warning and monitoring device, comprising:
the analysis module is used for analyzing the shaft temperature data set from the sensor to obtain temperature rise rate data;
the first determining module is used for determining a time interval from the first temperature rise rate to the second temperature rise rate according to the temperature rise rate data;
the second determining module is used for determining the shaft temperature data corresponding to the time interval in the shaft temperature data set as jump data under the condition that the length of the time interval is smaller than or equal to a preset threshold value; and
and the early warning monitoring module is used for carrying out early warning monitoring according to other shaft temperature data except jump data in the shaft temperature data set.
A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the above-described shaft temperature pre-warning monitoring method.
A fourth aspect of the present disclosure also provides a computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the above-described shaft temperature pre-warning monitoring method.
A fifth aspect of the present disclosure also provides a computer program product comprising a computer program which, when executed by a processor, implements the above-described method of shaft temperature early warning monitoring.
According to the embodiment of the disclosure, because the inherent characteristics of inertia existing in heat transfer and heat dissipation of the mechanical component are found, the duration of temperature rise change under the real fault state is different from the time of temperature jump caused by sensor faults and the like, the duration of temperature rise rate transition is used as the time characteristic for identifying the temperature jump to judge whether the change of the current temperature rise rate is abnormal, so that temperature rise data caused by unreal faults such as sensor faults and the like are eliminated in the early warning and monitoring process, the probability of false alarm is effectively reduced, and the running efficiency and stability of the train are improved.
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The foregoing and other objects, features and advantages of the disclosure will be more apparent from the following description of embodiments of the disclosure with reference to the accompanying drawings, in which:
FIG. 1 schematically illustrates an application scenario diagram of a shaft temperature pre-warning monitoring method, apparatus, device, medium and program product according to an embodiment of the present disclosure;
FIG. 2 schematically illustrates a flow chart of a method of shaft temperature early warning monitoring in accordance with an embodiment of the present disclosure;
FIG. 3 schematically illustrates a schematic diagram of an axle temperature curve true fault and non-true fault condition in accordance with an embodiment of the present disclosure;
FIG. 4 schematically illustrates a flow chart of an anomaly data early warning method caused by a real fault in accordance with an embodiment of the present disclosure;
FIG. 5 schematically illustrates a flow chart of a method of early warning and monitoring of shaft temperature according to another embodiment of the present disclosure;
FIG. 6 schematically illustrates a temperature rise rate curve according to an embodiment of the present disclosure;
FIG. 7 schematically illustrates a block diagram of a shaft temperature early warning monitoring device according to an embodiment of the present disclosure; and
fig. 8 schematically illustrates a block diagram of an electronic device adapted to implement a shaft temperature pre-warning monitoring method according to an embodiment of the disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is only exemplary and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and/or the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.
Where expressions like at least one of "A, B and C, etc. are used, the expressions should generally be interpreted in accordance with the meaning as commonly understood by those skilled in the art (e.g.," a system having at least one of A, B and C "shall include, but not be limited to, a system having a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
In the technical scheme of the invention, the related user information (including but not limited to user personal information, user image information, user equipment information, such as position information and the like) and data (including but not limited to data for analysis, stored data, displayed data and the like) are information and data authorized by a user or fully authorized by all parties, and the processing of the related data such as collection, storage, use, processing, transmission, provision, disclosure, application and the like are all conducted according to the related laws and regulations and standards of related countries and regions, necessary security measures are adopted, no prejudice to the public welfare is provided, and corresponding operation inlets are provided for the user to select authorization or rejection.
For mechanical components of trains such as axle boxes, gearboxes, motor bearings, etc., the inherent mechanical properties are followed, i.e. the heat transfer and heat dissipation of the mechanical components needs to be completed within a certain time. Therefore, the phenomenon that the rapid temperature rise or fall is achieved at a certain instant is not caused by the actual frictional heat generation between the mechanical parts or the heat dissipation to the mechanical parts, and can be determined as other factors without pre-warning. Therefore, when the system early warning prompt is set, jump data caused by other factors can be eliminated or removed, and early warning monitoring is only carried out on abnormal data caused by the real fault condition. Further, in the process of realizing the conception of the present disclosure, it is found that the time length feature sustained by adopting the temperature rise rate transition can be used for more accurately identifying the abnormal data and the jump data, so as to reduce the probability of false alarm and improve the running efficiency and stability of the train.
The embodiment of the disclosure provides a shaft temperature early warning and monitoring method, which comprises the following steps: analyzing a shaft temperature data set from a sensor to obtain temperature rise rate data; determining a time interval from the first temperature rise rate to the second temperature rise rate according to the temperature rise rate data; under the condition that the length of the time interval is smaller than or equal to a preset threshold value, determining the shaft temperature data corresponding to the time interval in the shaft temperature data set as jump data; and carrying out early warning and monitoring according to other shaft temperature data except jump data in the shaft temperature data set.
Fig. 1 schematically illustrates an application scenario diagram of a method, apparatus, device, medium and program product for early warning and monitoring of shaft temperature according to an embodiment of the present disclosure.
As shown in fig. 1, an application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a server 103, and a network 104. The network 104 is a medium used to provide a communication link between the first terminal device 101, the second terminal device 102, and the server 103. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others. The first terminal device 101 may be a traffic device, such as a train or the like.
The user may interact with the server 103 via the network 104 using the first terminal device 101, the second terminal device 102, to receive or send messages etc. Various communication client applications, such as data analysis software, etc. (for example only) may be installed on the first terminal device 101, the second terminal device 102.
The second terminal device 102 may be a variety of electronic devices with a display screen including, but not limited to, smartphones, tablets, laptop portable computers, desktop computers, and the like.
The server 103 may be a server providing various services, such as a background management server (merely an example) providing support for a user with the shaft temperature early warning monitoring apparatus used by the first terminal device 101, the second terminal device 102. The background management server may analyze and process the received user request or the data such as the shaft temperature from the sensor, and feed back the processing result (e.g. the web page, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that the method for monitoring the shaft temperature early warning provided in the embodiments of the disclosure may be generally executed by the server 103. Accordingly, the shaft temperature early warning and monitoring device provided in the embodiments of the present disclosure may be generally disposed in the server 103. The method for monitoring the early-warning of the shaft temperature provided by the embodiment of the present disclosure may also be performed by a server or a server cluster which is different from the server 103 and is capable of communicating with the first terminal device 101, the second terminal device 102 and/or the server 103. Accordingly, the shaft temperature early warning and monitoring device provided by the embodiments of the present disclosure may also be provided in a server or a server cluster different from the server 103 and capable of communicating with the first terminal device 101, the second terminal device 102 and/or the server 103. In addition, the shaft temperature early warning and monitoring device provided by the embodiment of the disclosure can also be arranged in the terminal equipment and directly executed by the terminal equipment.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
The shaft temperature early warning and monitoring method according to the embodiment of the present disclosure will be described in detail with reference to fig. 2 to 6 based on the scenario described in fig. 1.
Fig. 2 schematically illustrates a flow chart of a method of shaft temperature early warning monitoring in accordance with an embodiment of the present disclosure. Fig. 3 schematically illustrates a schematic diagram of an axle temperature curve real fault and non-real fault condition in accordance with an embodiment of the present disclosure. This is described in detail below in conjunction with fig. 2 and 3.
As shown in fig. 2, the method for monitoring the shaft temperature early warning of this embodiment includes operations S210 to S240.
In operation S210, an axle temperature dataset from a sensor is analyzed to obtain temperature rise rate data.
According to an embodiment of the present disclosure, the axle temperature dataset is constituted by axle temperature data acquired by real-time temperature monitoring of mechanical components of the train to be detected, such as axle boxes, gearboxes, motor bearings, etc., with sensors; the temperature rise rate data is used for representing the speed of temperature change which is displayed along with time change, namely representing the relation between the temperature rise rate and time, wherein the temperature rise rate can be positive temperature rise rate or negative temperature rise rate. And acquiring the shaft temperature data monitored by the sensor in real time, and calculating the temperature rise rate according to the time and the temperature variation.
In operation S220, a time interval for transition from the first temperature rise rate to the second temperature rise rate is determined according to the temperature rise rate data.
According to embodiments of the present disclosure, the transition between the first temperature rise rate and the second temperature rise rate may be a transition between a positive temperature rise rate and a negative temperature rise rate, but is not limited thereto, and in some embodiments may be a transition between a positive or negative temperature rise rate and 0 (i.e., temperature invariant), except that the transition between the positive and negative temperature rise rates more conforms to the transition law.
According to the embodiment of the disclosure, the time interval is determined according to the time corresponding to the first temperature rise rate and the time corresponding to the second temperature rise rate. The time duration used for this time interval is compared with a preset threshold. For example, in the temperature rise rate data, the first temperature rise rate corresponds to a time of 18:03:00, the second temperature rate corresponds to a time of 18:23:00, and the determined time interval is [18:03:00, 18:23:00].
In operation S230, in case that the length of the time interval is less than or equal to a preset threshold, the shaft temperature data corresponding to the time interval in the shaft temperature data set is determined as the jump data.
According to an embodiment of the present disclosure, the preset threshold is used to characterize the length of time required for the rate of temperature rise change caused by a real failure of a mechanical component of the train. As shown in fig. 3, the temperature curves plotted by the three types of shaft temperature data show that the temperature change caused by the real fault is relatively gentle and has relatively long duration, and the temperature curves of the upward jump and the downward jump have relatively quick abrupt changes, and the temperature change is relatively small when no real fault or no jump exists. The preset threshold may be based on analysis of train parameters and historical axle temperature data. The train parameters may be, illustratively, a vehicle type, a train number, a train speed, and the like.
According to the embodiment of the disclosure, when the length of the current time interval is smaller than or equal to a preset threshold, the change duration of the temperature rise rate is insufficient to reach the change duration of the temperature rise rate in real faults, but the change process of the temperature rise rate exists, the change of the temperature rise rate is determined to be the change of the temperature rise rate caused by the non-real faults, and the jump data is determined. As shown in fig. 3, the upward and downward jumps in the shaft temperature data caused by the non-real fault are abrupt and short in duration.
In operation S240, early warning monitoring is performed according to other shaft temperature data except the jump data in the shaft temperature data set.
According to the embodiment of the disclosure, in an actual working scene of monitoring the axle temperature of a train, early warning is needed for the temperature rise phenomenon caused by real faults, and early warning is avoided for the temperature rise phenomenon (such as the phenomenon of axle temperature data jump) caused by non-real faults. Therefore, after confirming that the temperature rise rate in the time interval is jump data, the jump data can be eliminated or removed, and other data in the shaft temperature data set can be subjected to early warning and monitoring.
According to the embodiment of the disclosure, because the inherent characteristics of inertia existing in heat transfer and heat dissipation of mechanical components are found, the duration of temperature rise change under the real fault state is different from the time of temperature jump caused by sensor faults and the like, the duration of temperature rise rate transition is used as the time characteristic for identifying the temperature jump to judge whether the change of the current temperature rise rate is abnormal, so that temperature rise data caused by unreal faults such as sensor faults and the like are eliminated in the early warning and monitoring process, the probability of false alarm is greatly reduced, and the running efficiency and stability of the train are improved.
Fig. 4 schematically illustrates a flowchart of an anomaly data early warning method caused by a real fault according to an embodiment of the present disclosure. As shown in fig. 4, the shaft temperature early warning and monitoring method further includes operations S310 to S320.
In operation S310, in case that the length of the time interval is greater than a preset threshold value, the shaft temperature data corresponding to the time interval in the shaft temperature data set is determined as abnormal data.
According to an embodiment of the present disclosure, in operation S310, the length of the time interval is greater than a preset threshold, and it is characterized that the change duration of the temperature rise rate reaches the change duration of the temperature rise rate when the actual fault, and then it is determined that the change of the temperature rise rate is the change of the temperature rise rate caused by the actual fault, and it is determined as abnormal data.
In operation S320, in case that the performance state of the sensor itself is normal, the abnormal data is early-warned.
According to the embodiment of the present disclosure, in operation S320, before the temperature rise phenomenon is pre-warned, the performance of the sensor is further checked, if the sensor state is normal, the abnormal data is determined to be the temperature rise caused by the real fault, so as to further eliminate the false alarm caused by the sensor fault, and reduce the false alarm probability.
Fig. 5 schematically illustrates a flow chart of a method of early warning and monitoring of shaft temperature according to another embodiment of the present disclosure.
As shown in fig. 5, the shaft temperature early warning and monitoring method according to the embodiment of the present disclosure includes S510 to S530:
in operation S510, temperature rise rate jump detection is performed, specifically including: obtaining a shaft temperature data set according to the temperature signal detected by the sensor; analyzing the shaft temperature data set, and determining that the shaft temperature data corresponding to the time interval is jump data under the condition that the length of the time interval of temperature rise rate transition is smaller than or equal to a preset threshold value; otherwise, determining the abnormal data;
in operation S520, a sensor fault diagnosis is performed, specifically including: and detecting the performance state of the sensor according to the temperature signal detected by the sensor. The specific detection method may be implemented by using an algorithm known in the art, which is not described herein.
In operation S530, the shaft temperature early warning is performed according to the temperature rise rate jump detection result and the sensor fault diagnosis result, and the early warning result is output, which specifically includes: and under the condition that the shaft temperature data are abnormal data (namely no jump data are reported) and the performance state of the sensor is normal, early warning is carried out on the abnormal data.
In accordance with an embodiment of the present disclosure, analyzing the shaft temperature dataset from the sensor in operation S210, obtaining temperature rise rate data includes: according to the shaft temperature data at different moments in the shaft temperature data set, calculating the temperature change rate of each moment relative to the previous moment, and obtaining temperature rise rate initial data; and carrying out smoothing treatment on the initial data of the temperature rise rate to obtain the data of the temperature rise rate.
According to an embodiment of the disclosure, a shaft temperature dataset monitored by a sensor in real time is obtained, wherein each shaft temperature data may be a temperature corresponding to a certain moment. For example: 12:30:20, the shaft temperature is 25 ℃;12:40:20, the shaft temperature is 26 ℃;12:50:20, an axis temperature of 24 ℃, etc.
According to the embodiment of the disclosure, further, the initial data of the temperature rise rate can be calculated according to the following formula (1) according to the shaft temperature data at different moments:
dT t ＝(T t -T t-1 )/dt (1)；
wherein dT is t The initial value of the temperature rise rate at the time T is T t The temperature of the shaft at the time T is T t-1 The temperature of the shaft at time t-1, and dt is the interval between time t and time t-1.
For example, at a sensor sampling frequency of 1000Hz, the temperature at time t rises by 0.03 ℃ relative to the temperature at time t-1, and the initial value of the temperature rise rate at time t is a positive temperature rise rate of 30 ℃/s.
Further, the obtained temperature rise initial rate data may be smoothed according to the formula (2) to obtain a smoothed temperature rise rate curve in the time period.
Wherein P is t dT is the temperature rise rate after smoothing treatment at time t t 、dT t+i 、dT t-i And n is 1, 2 or 3 for the initial value of the temperature rise rate at the time t, the time t+i and the time t-i in the initial data of the temperature rise rate.
According to the embodiment of the disclosure, the temperature rise rate data is obtained through smoothing, so that data noise can be reduced to prevent interference of the noise data, and whether the preset temperature rise rate, namely the first temperature rise rate and the second temperature rise rate, is accurately determined.
According to the embodiment of the disclosure, a temperature rise rate curve can be generated according to the temperature rise rate data after the smoothing process. Fig. 6 schematically illustrates a temperature rise rate curve according to an embodiment of the present disclosure. As shown in fig. 6, in the axis temperature curve coordinate system, the abscissa is time, the ordinate is temperature rise rate, and a curve that fluctuates up and down along the X axis can be formed with accumulation of time and the temperature rise rate. The fluctuation degree of the curve changes along with the temperature rise rate, and when the temperature rise rate is positive, the curve is positioned above the X axis; when the rate of temperature rise is negative, the curve is located below the X-axis. The gray curve shows that there is a downward jump compared to the no jump case shown in the black curve.
According to the embodiment of the disclosure, the method is applied to vehicle operation detection, wherein one of the first temperature rise rate and the second temperature rise rate is a positive temperature rise rate used for predicting that the vehicle can normally operate, and the other is a maximum negative temperature rise rate obtained according to historical jump data statistics.
According to embodiments of the present disclosure, the first temperature rise rate or the second temperature rise rate may be set according to train parameters and historical temperature rise rates. Illustratively, the train parameter may be a train model. For example, the real-time shaft temperature system of the AA-sized motor train unit is used for setting the temperature rise rate to be more than or equal to 8 ℃/min as the pre-judgment, the vehicle can normally run, the temperature rise rate to be more than or equal to 10 ℃/min as the pre-warning, the vehicle needs to run at a reduced speed, the temperature rise rate to be more than or equal to 15 ℃/min, and the vehicle needs to be stopped for inspection. Thus, at a first rate of temperature rise P 1 Positive value, second temperature rise rate P 2 Taking a negative value as an example, namely taking the case that the temperature rise rate data has upward jump, for the AA-number motor train unit, the first temperature rise rate P 1 The temperature rise rate should be set before the early warning, for example, 8 ℃/min, so that the normal operation of the vehicle can be ensured. And a second rate of temperature rise P 2 The maximum negative temperature rise rate which can be achieved by the historical jump data is about 98 percent or more-6 ℃/min, wherein the historical jump data can be determined by counting the historical temperature rise rate data and the actual jump condition.
According to the embodiment of the disclosure, the first temperature rise rate or the second temperature rise rate is set to be the positive temperature rise rate and the negative temperature rise rate respectively, so that the duration of temperature rise and fall back can be judged, and compared with the condition of independently judging temperature rise or temperature fall, the method is more accurate.
According to an embodiment of the present disclosure, when the actual temperature rise rate reaches the first temperature rise rate P 1 When the current time is determined as the first time t1. For example, P can be satisfied at the actual temperature rise rate 1 At + -1deg.C, a first rate of temperature rise P is considered to be reached 1 . If the actual positive temperature rise rate of 09:05:00 at the current time is 8.5 ℃/min, then t1 can be determined to be 09:05:00.
Similarly, when the actual temperature rise rate reaches the second temperature rise rate P 2 When this is the case, the current time may be determined as the second time t2. For example, P can be satisfied at the actual temperature rise rate 2 The second temperature rise rate P is considered to be reached at + -1deg.C 2 。
According to an embodiment of the present disclosure, determining a time interval for transitioning from a first rate of temperature rise to a second rate of temperature rise from the rate of temperature rise data in operation S220 includes: determining a first moment corresponding to the first temperature rise rate and a second moment corresponding to the second temperature rise rate in monotonically changing temperature rise rate data; and converting the time interval between the first time and the second time from the first temperature rise rate to the second temperature rise rate.
According to an embodiment of the present disclosure, the first time is used to characterize a time corresponding to the first temperature rise rate in the temperature rise rate data, as shown at time t3 in fig. 6; the second time is used to characterize the time corresponding to the second temperature rise rate in the temperature rise rate data, as shown at time t1 in fig. 6. And the time t2 and the time t1 are not in the monotonous change process and are not used for determining the time interval. According to an embodiment of the present disclosure, the length of time between the first time t3 and the second time t1 may be denoted by Δt, then Δt=t1-t 3.
According to the embodiment of the disclosure, based on the inherent mechanical characteristics, namely the characteristics of heat transfer and heat dissipation with inertia, the temperature rise phenomenon caused by non-real fault conditions is accurately eliminated, the duration of temperature change is used as a judgment condition, jump data or abnormal data is determined by comparing the duration with the preset threshold, and the accuracy of the shaft temperature early warning and monitoring method is further improved.
According to an embodiment of the present disclosure, the preset threshold is 30 to 60 seconds.
According to an embodiment of the present disclosure, the preset threshold value of the time length is 30 to 60s. The preset threshold is used for representing the time required for the change of the first temperature rise rate and the second temperature rise rate under the real fault.
The preset threshold value can be obtained according to train parameters and historical real temperature rise data. As shown in table 1.
According to the embodiment of the present disclosure, illustratively, from the jump data and the anomaly data under the real fault in table 1, it can be seen that, for 10 jump anomaly data, only 1 history data greater than the preset threshold exists, and about 90% false alarm faults can be reduced.
According to an embodiment of the present disclosure, the shaft temperature dataset is a shaft temperature dataset of an axle box, a gearbox or a motor bearing; the shaft temperature early warning and monitoring method further comprises the following steps: acquiring historical jump data and historical abnormal data which are consistent with mechanical characteristics of an axle box, a gear box or a motor bearing; and updating the preset threshold according to the historical jump data and the historical abnormal data.
According to the embodiment of the disclosure, the historical jump data is used for representing jump data caused by non-real faults in the historical data, and the historical abnormal data is used for representing abnormal data caused by real faults in the historical data. During long-term use of the train, the length of time of induction to temperature or loss of each component may change. The axle temperatures generated by different train parameters are also different. Therefore, the preset thresholds of different train parameters can be updated according to the historical jump data and the historical abnormal data.
For example, historical trip data and historical anomaly data for different recent trains are obtained. The recent time range may be in units of months or years, for example: about 3 months, about 6 months, about 9 months, about 12 months, about two years, about three years, etc. Further, a preset threshold value may be selected that is capable of distinguishing between historical trip data and historical anomaly data, e.g., the preset threshold value needs to be met such that the duration of the temperature rise rate transition in 100% of the historical anomaly data should be greater than the preset threshold value, and the duration of the temperature rise rate transition in at least 90% of the historical trip data should be less than or equal to the preset threshold value.
According to the embodiment of the disclosure, the preset threshold value is determined according to the historical data, so that the use condition and the data under the real condition of the train can be further determined according to different train models, train speeds and the like, the monitoring accuracy is further improved, and the false alarm probability is reduced.
Based on the shaft temperature early warning and monitoring method, the disclosure also provides a shaft temperature early warning and monitoring device. The device will be described in detail below in connection with fig. 7.
Fig. 7 schematically illustrates a block diagram of a shaft temperature early warning monitoring device according to an embodiment of the present disclosure.
As shown in fig. 7, the shaft temperature early warning and monitoring device 700 of this embodiment includes an analysis module 710, a first determination module 720, a second determination module 730, and an early warning and monitoring module 740.
The analysis module 710 is configured to analyze the shaft temperature data set from the sensor to obtain temperature rise rate data. In an embodiment, the analysis module 710 may be configured to perform the operation S210 described above, which is not described herein.
The first determining module 720 is configured to determine a time interval for converting the first temperature rise rate to the second temperature rise rate according to the temperature rise rate data. In an embodiment, the first determining module 720 may be configured to perform the operation S220 described above, which is not described herein.
The second determining module 730 is configured to determine, as the jump data, the shaft temperature data corresponding to the time interval in the shaft temperature data set when the length of the time interval is less than or equal to a preset threshold, where the preset threshold is 30-70 s. In an embodiment, the second determining module 730 may be configured to perform the operation S230 described above, which is not described herein.
The early warning monitoring module 740 is used for carrying out early warning monitoring according to other shaft temperature data except jump data in the shaft temperature data set. In an embodiment, the early warning and monitoring module 740 may be used to perform the operation S240 described above, which is not described herein.
According to an embodiment of the present disclosure, the shaft temperature pre-warning and monitoring device 700 further includes:
the third determining module is used for determining the shaft temperature data corresponding to the time interval in the shaft temperature data set as abnormal data under the condition that the length of the time interval is larger than a preset threshold value;
and the early warning module is used for carrying out early warning on abnormal data under the condition that the performance state of the sensor is normal.
According to an embodiment of the present disclosure, the first determining module 720 includes:
the first determining submodule is used for determining a first moment corresponding to the first temperature rise rate and a second moment corresponding to the second temperature rise rate in monotonically changing temperature rise rate data;
the second determining submodule is used for converting a time interval between the first moment and the second moment into a time interval with a second temperature rising rate from the first temperature rising rate.
According to the embodiment of the disclosure, the shaft temperature early warning and monitoring method is applied to vehicle operation detection, wherein one of the first temperature rise rate and the second temperature rise rate is a positive temperature rise rate used for predicting that the vehicle can normally operate, and the other is a maximum negative temperature rise rate obtained according to historical jump data statistics.
According to an embodiment of the present disclosure, the analysis module 710 includes:
The calculation sub-module is used for calculating the temperature change rate of each moment relative to the previous moment according to the shaft temperature data at different moments in the shaft temperature data set to obtain initial data of the temperature rise rate;
and the processing sub-module is used for carrying out smoothing processing on the initial data of the temperature rise rate to obtain the data of the temperature rise rate.
According to an embodiment of the present disclosure, wherein the shaft temperature dataset is a shaft temperature dataset of an axle box, a gearbox or a motor bearing; the shaft temperature early warning and monitoring device 700 further includes:
the acquisition module is used for acquiring historical jump data and historical abnormal data which are consistent with the mechanical characteristics of the axle box, the gear box or the motor bearing;
and the updating module is used for updating the preset threshold according to the historical jump data and the historical abnormal data.
Any of the analysis module 710, the first determination module 720, the second determination module 730, and the early warning monitoring module 740 may be combined in one module to be implemented, or any of the modules may be split into a plurality of modules, according to an embodiment of the present disclosure. Alternatively, at least some of the functionality of one or more of the modules may be combined with at least some of the functionality of other modules and implemented in one module. According to embodiments of the present disclosure, at least one of the analysis module 710, the first determination module 720, the second determination module 730, and the early warning monitoring module 740 may be implemented at least in part as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable way of integrating or packaging the circuitry, or in any one of or a suitable combination of three of software, hardware, and firmware. Alternatively, at least one of the analysis module 710, the first determination module 720, the second determination module 730, and the pre-alarm monitoring module 740 may be at least partially implemented as a computer program module, which when executed, may perform the corresponding functions.
Fig. 8 schematically illustrates a block diagram of an electronic device adapted to implement a shaft temperature pre-warning monitoring method according to an embodiment of the disclosure.
As shown in fig. 8, an electronic device 800 according to an embodiment of the present disclosure includes a processor 801 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 802 or a program loaded from a storage section 808 into a Random Access Memory (RAM) 803. The processor 801 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or an associated chipset and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. The processor 801 may also include on-board memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing the different actions of the method flows according to embodiments of the disclosure.
In the RAM 803, various programs and data required for the operation of the electronic device 800 are stored. The processor 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. The processor 801 performs various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM 802 and/or the RAM 803. Note that the program may be stored in one or more memories other than the ROM 802 and the RAM 803. The processor 801 may also perform various operations of the method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.
According to an embodiment of the present disclosure, the electronic device 800 may also include an input/output (I/O) interface 805, the input/output (I/O) interface 805 also being connected to the bus 804. The electronic device 800 may also include one or more of the following components connected to the I/O interface 805: an input portion 806 including a keyboard, mouse, etc.; an output portion 807 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage section 808 including a hard disk or the like; and a communication section 809 including a network interface card such as a LAN card, a modem, or the like. The communication section 809 performs communication processing via a network such as the internet. The drive 810 is also connected to the I/O interface 805 as needed. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 810 as needed so that a computer program read out therefrom is mounted into the storage section 808 as needed.
The present disclosure also provides a computer-readable storage medium that may be embodied in the apparatus/device/system described in the above embodiments; or may exist alone without being assembled into the apparatus/device/system. The computer-readable storage medium carries one or more programs which, when executed, implement methods in accordance with embodiments of the present disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example, but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the present disclosure, the computer-readable storage medium may include ROM 802 and/or RAM 803 and/or one or more memories other than ROM 802 and RAM 803 described above.
Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowcharts. The program code, when executed in a computer system, causes the computer system to implement the item recommendation method provided by embodiments of the present disclosure.
The above-described functions defined in the system/apparatus of the embodiments of the present disclosure are performed when the computer program is executed by the processor 801. The systems, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.
In one embodiment, the computer program may be based on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted, distributed, and downloaded and installed in the form of a signal on a network medium, and/or from a removable medium 811 via a communication portion 809. The computer program may include program code that may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In such an embodiment, the computer program may be downloaded and installed from a network via the communication section 809, and/or installed from the removable media 811. The above-described functions defined in the system of the embodiments of the present disclosure are performed when the computer program is executed by the processor 801. The systems, devices, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.
According to embodiments of the present disclosure, program code for performing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, such computer programs may be implemented in high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. Programming languages include, but are not limited to, such as Java, c++, python, "C" or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Those skilled in the art will appreciate that the features recited in the various embodiments of the disclosure and/or in the claims may be provided in a variety of combinations and/or combinations, even if such combinations or combinations are not explicitly recited in the disclosure. In particular, the features recited in the various embodiments of the present disclosure and/or the claims may be variously combined and/or combined without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of the present disclosure.
The embodiments of the present disclosure are described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the disclosure, and such alternatives and modifications are intended to fall within the scope of the disclosure.
Claims (10)
1. A shaft temperature early warning and monitoring method comprises the following steps:
analyzing a shaft temperature data set from a sensor to obtain temperature rise rate data;
Determining a time interval from the first temperature rise rate to the second temperature rise rate according to the temperature rise rate data;
when the length of the time interval is smaller than or equal to a preset threshold value, determining the shaft temperature data corresponding to the time interval in the shaft temperature data set as jump data;
and carrying out early warning monitoring according to other shaft temperature data except the jump data in the shaft temperature data set.
2. The method of claim 1, further comprising:
determining the shaft temperature data corresponding to the time interval in the shaft temperature data set as abnormal data under the condition that the length of the time interval is larger than the preset threshold value;
and under the condition that the performance state of the sensor is normal, early warning is carried out on the abnormal data.
3. The method of claim 1, wherein the determining a time interval from a first rate of temperature rise to a second rate of temperature rise based on the rate of temperature rise data comprises:
determining a first moment corresponding to the first temperature rise rate and a second moment corresponding to the second temperature rise rate in monotonically changing temperature rise rate data;
and taking the time interval between the first time and the second time as the time interval for converting the first temperature rise rate into the second temperature rise rate.
4. The method of claim 3, wherein the method is applied to vehicle operation detection, wherein one of the first temperature rise rate and the second temperature rise rate is a positive temperature rise rate used for predicting that a vehicle can normally operate, and the other is a maximum negative temperature rise rate obtained according to historical jump data statistics.
5. The method of claim 1, wherein analyzing the shaft temperature dataset from the sensor to obtain temperature rise rate data comprises:
according to the shaft temperature data at different moments in the shaft temperature data set, calculating the temperature change rate of each moment relative to the previous moment, and obtaining temperature rise rate initial data;
and carrying out smoothing treatment on the initial data of the temperature rise rate to obtain the data of the temperature rise rate.
6. The method of claim 1, wherein the shaft temperature dataset is a shaft temperature dataset of an axle box, a gearbox, or a motor bearing; the method further comprises the steps of:
acquiring historical jump data and historical abnormal data which are consistent with the mechanical characteristics of the axle box, the gear box or the motor bearing;
and updating the preset threshold according to the historical jump data and the historical abnormal data.
7. The method according to claim 1 or 6, wherein the preset threshold is 30-60 s.
8. An axle temperature early warning monitoring device, comprising:
the analysis module is used for analyzing the shaft temperature data set from the sensor to obtain temperature rise rate data;
the first determining module is used for determining a time interval from the first temperature rise rate to the second temperature rise rate according to the temperature rise rate data;
the second determining module is used for determining the shaft temperature data corresponding to the time interval in the shaft temperature data set as jump data under the condition that the length of the time interval is smaller than or equal to a preset threshold value; and
and the early warning monitoring module is used for carrying out early warning monitoring according to the other shaft temperature data except the jump data in the shaft temperature data set.
9. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of any of claims 1-7.
10. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method according to any of claims 1-7.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311752130.6A CN117719553A (en) | 2023-12-19 | 2023-12-19 | Shaft temperature early warning and monitoring method and device, electronic equipment and readable storage medium |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202311752130.6A CN117719553A (en) | 2023-12-19 | 2023-12-19 | Shaft temperature early warning and monitoring method and device, electronic equipment and readable storage medium |
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