CN113945290A - Temperature alarm method, device and medium - Google Patents
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Abstract
The application discloses a temperature alarm method, when current temperature data exceeds an alarm threshold value, alarm evaluation is carried out on the temperature data acquired before the current temperature data is acquired based on time dimension, and whether alarm is given or not is confirmed according to the result of the alarm evaluation. Compared with the prior art, the alarm is given when the temperature data exceeds the alarm threshold value, the technical scheme is adopted, the alarm evaluation is carried out on the temperature data obtained before the current temperature data is obtained, the temperature data are judged based on the time dimension, the alarm is given when the alarm condition is met, the alarm accuracy is improved, and the false alarm condition is reduced. The application also discloses a temperature alarm device and a medium, which correspond to the temperature alarm method and have the same effects.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a temperature alarm method, device, and medium.
Background
The bearing is used as a main part of a locomotive, and the health condition of the bearing directly influences the safe operation of a train. When the bearing is seriously failed, a rapid temperature rise phenomenon inevitably occurs, so that the temperature of the bearing of the train needs to be detected and is used as a last defense line for ensuring the safe operation of the locomotive.
The current technology is to arrange a temperature sensor close to a bearing area and alarm when the collected temperature data is judged to exceed a preset alarm threshold value. However, the sensor may be affected by voltage or current, which causes errors when the acquired temperature data does not match the actual temperature data, and if the alarm process is determined only according to the temperature data at the current time, a false alarm may be caused.
Therefore, how to reduce the false alarm when detecting the temperature of the bearing is an urgent problem to be solved by those skilled in the art.
Disclosure of Invention
The application aims to provide a temperature alarm method, a temperature alarm device and a medium.
In order to solve the above technical problem, the present application provides a temperature alarm method for reducing false alarm when detecting the temperature of a bearing, the method including:
acquiring current temperature data;
judging whether the current temperature data exceeds an alarm threshold value;
if so, performing alarm evaluation on a plurality of continuous temperature data acquired before the current temperature data is acquired based on the time dimension, and judging whether the plurality of continuous temperature data are monotonously changed in temperature;
and confirming whether to alarm or not according to the result of the alarm evaluation.
Preferably, the judging whether the plurality of consecutive temperature data changes monotonically in temperature includes:
judging whether the absolute value of the difference value between each temperature data and the last temperature data obtained last time in a plurality of continuous temperature data is smaller than a fluctuation value, if so, recording the temperature data as the last temperature data, and if not, keeping the temperature data unchanged;
judging whether the finally obtained different temperature data shows monotonous temperature change or not;
if so, determining that the plurality of continuous temperature data are in temperature monotonicity change, otherwise, determining that the plurality of continuous temperature data are not in temperature monotonicity change.
Preferably, if abnormal temperature data does not occur in the temperature data acquired before the current temperature data is acquired, the performing alarm evaluation on a plurality of consecutive temperature data acquired before the current temperature data is acquired includes:
judging whether temperature monotony of continuous BN1 temperature data is changed into temperature monotony rising or not in the latest credible temperature data obtained before the current temperature data is obtained, if yes, confirming that the result of alarm evaluation is alarm, and if not, repeating the step until the result of alarm evaluation is alarm; and/or
Judging whether the most reliable temperature data obtained before the current temperature data is obtained has continuous BN2 temperature data which are monotonously changed and exceed the alarm threshold value, if so, determining that the alarm evaluation result is alarm, and if not, repeating the step until the alarm evaluation result is alarm.
Preferably, if abnormal temperature data occurs in the temperature data acquired before the current temperature data is acquired and the abnormal temperature data are both special temperature values of the sensor, the alarm evaluation of a plurality of consecutive temperature data acquired before the current temperature data is acquired includes:
judging whether the most reliable temperature data obtained before the current temperature data is obtained has continuous BN3 temperature data which are monotonously changed and exceed the alarm threshold value, if so, determining that the alarm evaluation result is alarm, and if not, repeating the step until the alarm evaluation result is alarm.
Preferably, if abnormal temperature data occurs in the temperature data acquired before the current temperature data is acquired, and the unevenness is a special temperature value of the sensor itself, the alarm evaluation of a plurality of consecutive temperature data acquired before the current temperature data is acquired includes:
judging whether the most reliable temperature data obtained before the current temperature data is obtained has continuous BN4 temperature data which are monotonously changed and exceed the alarm threshold value, if so, determining that the alarm evaluation result is alarm, and if not, repeating the step until the alarm evaluation result is alarm.
Preferably, the temperature monotonicity variation includes: the temperature is monotonously increased, or the temperature is monotonously decreased, or the temperature is increased first and then decreased.
Preferably, before the determining whether the current temperature data exceeds the alarm threshold, the method further includes:
performing confidence evaluation on the current temperature data;
and if the current temperature data is evaluated to be credible, the step of judging whether the current temperature data exceeds the alarm threshold value is carried out.
Preferably, if the current temperature data is evaluated as not trusted, the method further comprises:
and replacing the current temperature data with normal temperature data.
Preferably, the replacing the current temperature data with the normal temperature data includes:
judging whether the temperature data of the same measuring point position of other shafts is normal temperature data or not when the current temperature data is obtained;
if not, calling the last normal temperature data which is obtained at the current measuring point position of the shaft for the last time to replace the current temperature data;
if so, calculating the difference value of the normal temperature data acquired at the same moment when the current measuring point position of the axis is closest to the same measuring point position of the other axis, and adding the temperature data at the same measuring point position of the other axis to replace the current temperature data.
Preferably, the performing confidence evaluation on the current temperature data includes:
judging whether the N1 temperature data acquired before the current temperature data is acquired are normal temperature data, and the absolute temperature rise rate of each temperature data and the absolute temperature rise rate of the previous normal temperature data are not greater than a threshold value, if so, determining that the current temperature data is credible, otherwise, repeating the step until the current temperature data is credible;
or judging whether the N2 temperature data acquired before the current temperature data is acquired are normal temperature data, wherein the absolute temperature rise rate of each temperature data and the absolute temperature rise rate of the previous normal temperature data are not greater than the threshold and show a monotonous rising or monotonous falling trend, if so, determining that the current temperature data is credible, and if not, repeating the step until determining that the current temperature data is credible.
In order to solve the above technical problem, the present application further provides a temperature alarm device, which includes:
the acquisition module is used for acquiring current temperature data;
the judging module is used for judging whether the current temperature data exceeds an alarm threshold value, and if so, the alarm evaluating module is triggered;
the alarm evaluation module is used for carrying out alarm evaluation on the temperature data acquired before the current temperature data is acquired based on the time dimension and judging whether the continuous temperature data are monotonously changed in temperature or not;
and the alarm module is used for confirming whether to alarm or not according to the alarm evaluation result obtained by the alarm evaluation module.
In order to solve the above technical problem, the present application further provides another temperature alarm device, which includes a memory for storing a computer program;
a processor for implementing the steps of the temperature alarm method as described above when executing said computer program.
In order to solve the above technical problem, the present application further provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of the temperature alarm method as described above.
According to the temperature alarm method, when the current temperature data exceeds the alarm threshold value, alarm evaluation is carried out on the temperature data acquired before the current temperature data is acquired based on the time dimension, and whether alarm is given or not is determined according to the alarm evaluation result. Compared with the prior art, the alarm is given when the temperature data exceeds the alarm threshold value, the technical scheme is adopted, the alarm evaluation is carried out on the temperature data obtained before the current temperature data is obtained, the temperature data are judged based on the time dimension, the alarm is given when the alarm condition is met, the alarm accuracy is improved, and the false alarm condition is reduced.
In addition, the temperature alarm device and the medium provided by the application correspond to the temperature alarm method, and the effect is the same as that of the temperature alarm method.
Drawings
In order to more clearly illustrate the embodiments of the present application, the drawings needed for the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained by those skilled in the art without inventive effort.
Fig. 1 is a flowchart of a temperature alarm method according to an embodiment of the present disclosure;
FIG. 2 is a flow chart of another temperature alarm method provided by an embodiment of the present application;
FIG. 3 is a flow chart of another temperature alarm method provided by an embodiment of the present application;
FIG. 4 is a flow chart of another temperature alarm method provided by the embodiments of the present application;
fig. 5 is a structural diagram of a temperature alarm device according to an embodiment of the present disclosure;
fig. 6 is a block diagram of another temperature alarm device according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without any creative effort belong to the protection scope of the present application.
The bearing is an important part in the modern mechanical equipment. The main function of the device is to support the mechanical rotator, reduce the friction coefficient of the mechanical rotator in the movement process and ensure the rotation precision of the mechanical rotator. The bearings on the locomotive include axle box bearings, traction motor bearings, transmission system bearings, power plant bearings, cooling system bearings and the like, and the bearings are used as main parts of the locomotive, and the health state of the bearings directly influences the safe operation of the train. When the bearing is in failure, the temperature will rise sharply, so it is necessary to detect the temperature of the bearing of the locomotive and to use it as the last line of defense to ensure the safe operation of the locomotive.
The current technology is to arrange a temperature sensor at a bearing, and when the collected temperature data is judged to be temperature data exceeding a threshold value, the temperature sensor is considered to be fault data, and an alarm is given. The method has the defects that the temperature data output by the temperature sensor has deviation with the actual temperature data due to the influence of voltage or current and the like, abnormal temperature data is output, and if the abnormal temperature data is directly adopted to enter a subsequent alarm judging process, the abnormal temperature data can be mistakenly considered as fault temperature data, and then an alarm is sent. However, the actual temperature data at this time is normal temperature data, which causes a false alarm.
The core of the application is to provide a temperature alarm method, a temperature alarm device and a temperature alarm medium, which are used for reducing the situation of false alarm when the temperature of a bearing is detected.
The core of the application is to provide a temperature alarm method, a temperature alarm device and a medium.
In order that those skilled in the art will better understand the disclosure, the following detailed description will be given with reference to the accompanying drawings.
Fig. 1 is a flowchart of a temperature alarm method according to an embodiment of the present application, and as shown in fig. 1, the method includes:
s10: and acquiring current temperature data.
In step S10, the processor receives the current temperature data collected at the current time sent by the sensor at each bearing. The current temperature data may be abnormal temperature data which is collected when the sensor is interfered and does not conform to the actual temperature data, and may also be actual temperature data at the bearing. The actual temperature data at the bearing may be fault temperature data when the bearing fails, or may be good temperature data without alarm. It can be understood that the temperature difference of the bearings at different positions is large due to the difference of the rotation speed, the bearing capacity and the ventilation effect of the bearings. The temperature difference of bearings with the same function is large if the positions are different. The temperature of the bearings at the same position of the same bogie is basically the same. The temperature should also be substantially the same for bearings in the same location on different bogies.
S11: and judging whether the current temperature data exceeds an alarm threshold value, and if so, entering the step S12.
In step S11, different alarm threshold values are set for different types of bearings according to actual conditions, and of course, since there is a fluctuation situation in the current temperature data in the specific implementation, the alarm threshold value should be a temperature that is reached when the bearing fails, but not reached when the bearing normally works. And when the current temperature data exceeds the alarm threshold value, the bearing is in fault or the working condition is abnormal.
S12: and on the basis of the time dimension, carrying out alarm evaluation on a plurality of continuous temperature data acquired before the current temperature data is acquired, and judging whether the plurality of continuous temperature data are monotonously changed in temperature.
In step S12, when the current temperature data exceeds the alarm threshold, it is further determined whether the current temperature data needs to be alarmed through the historical temperature data based on the time dimension. The historical temperature data is a plurality of continuous temperature data acquired before the current temperature data is acquired, and it can be understood that, in order to guarantee the accuracy of alarm evaluation, the plurality of continuous temperature data should be temperature data acquired closest to the current temperature data. The temperature monotonicity change may be a change in which the plurality of temperature data exhibit a monotonous increase in temperature or a monotonous decrease in temperature, or may be a change in which a part of the plurality of temperature data exhibit a monotonous increase in temperature or a monotonous decrease in temperature, that is, a change in which the plurality of temperature data exhibit a temperature monotonicity change.
S13: and confirming whether to alarm or not according to the result of the alarm evaluation.
And confirming whether to alarm or not according to the result of alarm evaluation, namely the judgment result. The alarm can be a continuous action, for example, the processor is connected with an alarm, when the alarm is confirmed, the processor controls the alarm to flash and sound, when the operator manually turns off the alarm or the current temperature data returns to normal, and when the alarm evaluation result is that the alarm is not needed, the alarm is stopped. Of course, the alarm may also be a timely action, and when the alarm is confirmed, the processor sends characters, audio, animation and other forms to the human-computer interaction device, such as a display, so as to prompt an operator that the bearing is in fault.
According to the temperature alarm method, when the current temperature data exceeds the alarm threshold value, alarm evaluation is carried out on the temperature data acquired before the current temperature data is acquired based on the time dimension, and whether alarm is given or not is determined according to the alarm evaluation result. Compared with the prior art, the alarm is given when the temperature data exceeds the alarm threshold value, the technical scheme is adopted, the alarm evaluation is carried out on the temperature data obtained before the current temperature data is obtained, the temperature data are judged based on the time dimension, the alarm is given when the alarm condition is met, the alarm accuracy is improved, and the false alarm condition is reduced.
In the conventional technique, when it is determined whether or not temperature data changes monotonously in temperature, if the value obtained by subtracting the temperature data at the last time most recently acquired from the current temperature data is positive, it is considered that the monotonous changes in temperature of the two temperature data are monotonously increasing, and if the value is negative, it is considered that the monotonous changes in temperature are monotonously decreasing. However, in the implementation, the actual temperature data at the bearing may fluctuate within a certain range, and if the method for determining the temperature monotonicity change in the prior art is strictly followed, the temperature monotonicity change of a plurality of consecutive temperature data cannot be determined.
On the basis of the foregoing embodiment, in this embodiment, the determining whether the plurality of consecutive temperature data changes monotonically with temperature includes:
judging whether the absolute value of the difference value between each temperature data and the last temperature data obtained last time in a plurality of continuous temperature data is smaller than a fluctuation value, if so, recording the temperature data as the last temperature data, and if not, keeping the temperature data unchanged;
judging whether the finally obtained different temperature data shows monotonous temperature change or not;
if so, determining that the plurality of continuous temperature data are in temperature monotonicity change, otherwise, determining that the plurality of continuous temperature data are not in temperature monotonicity change.
In the present embodiment, the fluctuation value is a normal fluctuation range between every two temperature data collected by the sensor. In the specific implementation, the setting can be set according to the material of the bearing, the external temperature, the error of the sensor and other factors. For example, the fluctuation value is 0.2 ℃, the number of collected temperature data is 8, the actually collected temperature data is shown in the first row of the table, and the second row is a recorded value of temperature data when the temperature monotonicity change determination is performed. The difference between the second temperature data and the first temperature data is 0.1 ℃, and is less than the fluctuation value, so that the recorded value of the second temperature data when the temperature monotonicity change is carried out is 59 ℃. Similarly, the actual value of the fourth temperature data is 58.9 ℃, and although the actual value of the third temperature data is 59.2 ℃ and the difference between the two values is larger than the fluctuation value, the recorded value of the third temperature data when the temperature monotonicity change judgment is performed is 59 ℃ which is different from the actual value of the fourth temperature data by 0.1 ℃, and therefore, the fourth temperature data is also recorded as 59 ℃ when the temperature monotonicity change judgment is performed. The actual value of the fifth temperature data differs from the recorded value of the fourth temperature data by 0.3 c, so the actual value of 59.3 c is recorded as a new recorded value and compared with the next temperature data. Finally, the temperature data involved in the judgment of whether the temperature data changes monotonically is 59 ℃, 59.3 ℃ and 59.6 ℃, and if the temperature is known to rise monotonically, it is determined that a plurality of consecutive temperature data change monotonically.
| 59℃ | 59.1℃ | 59.2℃ | 58.9℃ | 59.3℃ | 59.4℃ | 59.5℃ | 59.6℃ |
| 59℃ | 59℃ | 59℃ | 59℃ | 59.3℃ | 59.3℃ | 59.3℃ | 59.6℃ |
It can be understood that if abnormal temperature data occurs in the obtained continuous plurality of temperature data, the setting of the fluctuation value is too large, which may cause the abnormal temperature data to be used as a record value, and enter the process of judgment, causing inaccurate judgment, and therefore, in a specific implementation, if abnormal temperature data occurs in the obtained continuous plurality of temperature data, the fluctuation value may be set to be smaller than that when the abnormal temperature data does not occur.
According to the temperature alarm method provided by the embodiment of the application, when whether a plurality of continuous temperature data are in temperature monotonicity change or not is judged, two adjacent temperature data in a fluctuation value range are unified into one temperature data, whether different finally obtained temperature data are in temperature monotonicity change or not is judged, the situation that in specific implementation, the temperature data fluctuate in an error range to cause judgment failure is avoided, and the execution of the temperature alarm method steps is guaranteed.
In specific implementation, the sensor is interfered or the acquired temperature data is abnormal temperature data due to the influence of the production process of the sensor, and the acquired temperature data is not consistent with actual temperature data, so that if the plurality of continuous temperature data contain the abnormal temperature data, the alarm evaluation of the plurality of temperature data is inaccurate.
Fig. 2 is a flowchart of another temperature alarm method according to an embodiment of the present application, and as shown in fig. 2, before performing alarm evaluation on a plurality of temperature data, the method further includes:
s110: it is determined whether the temperature data acquired before the current temperature data is acquired has abnormal temperature data, and if not, the process proceeds to step S12. Wherein step S12 includes S120 and/or S121.
In step S110, in order to ensure the accuracy of the alarm evaluation, it is avoided that the result of the alarm evaluation is affected by mixing abnormal temperature data that does not actually match the alarm evaluation into a plurality of consecutive data. The present embodiment further provides a method for determining abnormal temperature data, where the method includes:
judging whether the current temperature data exceeds the temperature measurement range of the sensor, if so, confirming that the current temperature data is abnormal temperature data;
and/or judging whether the current temperature data is a special temperature value of the sensor, if so, confirming that the current temperature data is abnormal temperature data;
and/or judging whether the absolute temperature rise rate of the current temperature data and the latest normal temperature data acquired before the current temperature data is greater than a second threshold value, and if so, determining that the current temperature data is abnormal temperature data.
When a plurality of continuous temperature data collected by the sensor are the maximum range values of the sensor, the temperature data can be considered to be beyond the temperature measurement range of the sensor, the temperature data cannot reflect the actual situation, and the temperature data is confirmed as abnormal temperature data. If the current temperature data is the special temperature value of the sensor, when the actual temperature reaches a certain value, the temperature data output by the sensor at the moment is the special temperature value, which is not in accordance with the actual temperature, and the actual temperature data can not be reflected, so that the current temperature data can be confirmed to be abnormal temperature data. If the absolute temperature rise rate of the current temperature data and the latest normal temperature data acquired before the current temperature data is larger, the temperature is indicated to have sudden change. The second threshold is set according to different implementation scenarios, and even if the bearing fails, the absolute temperature rise rate should not be greater than the second threshold. And if the absolute temperature rise rate exceeds a second threshold value, the current temperature data is considered to be not in accordance with the reality and is abnormal temperature data. When the current temperature data is judged, if the current temperature data meets any one of the conditions, the current temperature data can be confirmed to be abnormal temperature data, and of course, two or three conditions can be met simultaneously to confirm the current temperature data to be abnormal temperature data. It can be understood that, compared with the method for judging whether the absolute temperature rise rate is greater than the second threshold value, the method for judging the temperature of the sensor does not need excessive calculation amount.
S120: judging whether the temperature monotony of the most recent credible temperature data acquired before the current temperature data is acquired has continuous BN1 temperature data which change into monotonous temperature rise; if yes, the process proceeds to step S13, and if no, the process is repeated until the process proceeds to step S13.
In step S120, a plurality of consecutive temperature data are the most recent reliable temperature data. In a specific implementation, when the current temperature data is acquired, the credible attribute of the current temperature data is defined as credible or incredible, and if the current temperature data is abnormal temperature data, the current temperature data is defined as incredible. In step S120, if the temperature data acquired before the current temperature data is acquired does not have abnormal temperature data, it indicates that the sensor has not been interfered before the current temperature data is acquired. If the temperatures of the continuous BN1 temperature data monotonically rise and the current temperature data exceeds the alarm threshold value, the temperature change is high in probability due to the fact that the bearing is in fault, the temperature rises, and therefore an alarm is confirmed. The temperature data are continuously updated, so the judging step is also continuously carried out, the BN1 temperature data are also continuously updated, and an alarm is confirmed when the newly acquired current temperature data meet the judging condition. In this embodiment, whether to alarm or not is determined by judging the monotonicity change of the temperature of the BN1 temperature data, and if the sensor is not interfered before acquiring the current temperature data, the current temperature data exceeds the alarm threshold, so that a sufficient amount of temperature data should be judged to ensure the accuracy of alarm.
S121: judging whether continuous BN2 temperature data exist in the latest credible temperature data acquired before the current temperature data are acquired and are in monotonous temperature change and exceed an alarm threshold value, if so, entering a step S13, otherwise, repeating the step until entering a step S13.
In step S121, the temperature monotonicity of the BN2 temperature data may be monotonically increasing, monotonically decreasing, or fluctuating, and if consecutive BN2 temperature data are monotonically changing and all exceed the alarm threshold, it is indicated that the bearing has a fault.
It can be understood that, in step S120, it is determined whether the temperature monotonically increases, and an alarm is given when the current temperature data exceeds the alarm threshold, so that an alarm can be given immediately when the bearing fails. In step S121, it is necessary to determine whether all of the BN2 temperature data have exceeded the alarm threshold, which is slightly slower than the alarm time in step S120. However, since the determination method of S121 is more stringent in terms of the restriction conditions than the determination method of S120, BN2 may be smaller than BN 1.
It should be noted that the current temperature data can be alarmed only by satisfying one of the judgment methods in step S120 and step S121. Of course, the current temperature data can also meet the two judgment methods at the same time to alarm. Compared with the condition that only one judgment method is needed, the alarm evaluation of the current temperature data obtained by the two judgment methods is more accurate, but the calculation pressure of the processor is increased. When the current temperature data needs to satisfy the two determination methods, step S120 and step S121 do not have a sequential execution order, and step S120 may be executed first, or step S121 may be executed first, and of course, there may be partial repetition or complete difference between the required BN1 and BN2 temperature data.
According to the temperature alarm method, based on the time dimension, the historical credible temperature data are used for carrying out alarm evaluation on the current temperature data, and the accuracy of the alarm evaluation is ensured.
As shown in fig. 2, if abnormal temperature data occurs in the temperature data acquired before the current temperature data is acquired, the process proceeds to step S122.
S122: and judging whether the abnormal temperature data are all the special temperature values of the sensor, and if so, entering the step S12. Step S12 is S123.
In step S122, if abnormal temperature data occurs in the temperature data acquired before the current temperature data is acquired, and the abnormal temperature data is a special temperature value of the sensor itself, it indicates that the sensor itself has a problem.
S123: judging whether continuous BN3 temperature data exist in the latest credible temperature data acquired before the current temperature data are acquired and are in monotonous temperature change and exceed an alarm threshold value, if so, entering a step S13, otherwise, repeating the step until entering a step S13.
In step S123, if abnormal temperature data occurs in the temperature data acquired before the current temperature data is acquired, the abnormal temperature data may be one or more. Specifically, if the temperature data are all the special temperature values of the sensor, it indicates that the one or more abnormal temperature data are all the special temperature values of the sensor, which represents the problem of the sensor itself, and by determining whether the temperature data exceed the alarm threshold value, it is possible to determine the temperature data that are relatively less than the BN 1. In order to accurately judge whether the current temperature data is fault temperature data or a special temperature value of the sensor, more temperature data relative to the BN2 can be judged, namely, the BN3 is larger than the BN 2.
The temperature alarm method provided by the embodiment of the application carries out alarm evaluation on the current temperature data based on the time dimension, and further improves the alarm accuracy. Meanwhile, compared with the above embodiment, if abnormal temperature data occurs in the temperature data acquired before the current temperature data is acquired, and the abnormal temperature data is a special temperature value of the sensor itself, the determined temperature data may be less than the BN 1.
As shown in fig. 2, if abnormal temperature data occurs in the temperature data acquired before the current temperature data is acquired and the unevenness is a special temperature value of the sensor itself, the process proceeds to step S12. Step S12 is S124.
S124: judging whether continuous BN4 temperature data exist in the latest credible temperature data acquired before the current temperature data are acquired and are in monotonous temperature change and exceed an alarm threshold value, if so, entering a step S13, otherwise, repeating the step until entering a step S13.
In step S124, if one or more abnormal temperature data are not the special temperature values of the sensor itself, it indicates that the sensor is disturbed by voltage, current, or the like, and therefore it is necessary to determine more temperature data than BN3 to distinguish whether the current temperature data are disturbed.
In this embodiment, if the temperature data acquired before the current temperature data is acquired does not have abnormal temperature data, under the condition that the current temperature data exceeds the alarm threshold value, more temperature data needs to be determined to determine whether the current temperature data is caused by interference of the sensor. If abnormal temperature data occurs, the sensor is interfered, and in order to avoid that the abnormal temperature data cannot obtain enough temperature data to influence the judgment process of alarming, the number of the required temperature data can be less than that of the abnormal temperature data. Specifically, BN1 is greater than BN 4. When the sensor is influenced by voltage or current, the acquired temperature data fluctuates, so that a plurality of temperature data are not in accordance with the reality. The special temperature value of the sensor is displayed as a special temperature value because the current temperature data reaches a certain value. It will be appreciated that inaccurate temperature data collected when a sensor is affected is more than the particular temperature value of the sensor itself, and therefore, BN4 should be greater than BN 3.
According to the temperature alarm method, alarm evaluation is carried out on the current temperature data based on the time dimension, and the accuracy of alarm evaluation is improved. Under the condition that the current temperature data exceeds a preset alarm threshold value, the current temperature data is further judged, and the condition of false alarm caused by inconsistency between the acquired data and the actual data due to interference of the sensor is avoided.
It can be understood that, in the above embodiment, when the alarm evaluation is performed on the current temperature data through a plurality of historical data, the alarm is performed when the current temperature data meets the alarm evaluation, and along with the update of the temperature data, if the fault is cleared, the temperature data is recovered to be normal, and when the current temperature data does not meet the alarm evaluation, if the alarm is a persistent action, the alarm may also be ended. On the basis of the above embodiment, in the present embodiment, BN1 is greater than BN4, BN4 is greater than BN3, and BN3 is greater than BN 2.
According to the temperature alarm method, different numbers of historical temperature data are selected according to different conditions, the calculated amount of the processor is reduced under the condition that the accuracy of alarm evaluation is guaranteed, and the alarm efficiency is improved.
In the above embodiment, the temperature monotonicity change of the temperature data is not limited, and in this embodiment, the temperature monotonicity change includes: the temperature is monotonously increased, or the temperature is monotonously decreased, or the temperature is increased first and then decreased.
It will be appreciated that, after a bearing failure, the temperature may drop gradually due to environmental influences. Different from the prior art, only the temperature monotonicity change is judged to be temperature monotonicity rising or temperature monotonicity falling, the temperature alarming method provided by the embodiment of the application also comprises the step that the temperature rises firstly and then falls, even if the temperature is reduced after the bearing is in fault, the temperature alarming method still can give an alarm, and the condition of alarming omission is avoided.
In the above embodiment, the historical temperature data needs to be judged to determine whether the current temperature data needs to be alarmed. In specific implementation, if the current temperature data is judged to be not consistent with the actual temperature data and is incredible temperature data when the current temperature data is obtained, the current temperature data does not need to enter a subsequent judgment step, and the condition of false alarm is avoided. However, due to the method for determining abnormal temperature data mentioned in the above embodiment, the processor may mistake the abnormal temperature data collected when the sensor is interfered as the fault temperature data, thereby causing a false alarm, or may mistake the fault temperature data as the abnormal temperature data, thereby considering the abnormal temperature data as the unreliable temperature data, thereby causing a false alarm.
Therefore, on the basis of the foregoing embodiment, fig. 3 is a flowchart of another temperature alarm method provided in the embodiment of the present application, and as shown in fig. 3, in this embodiment, before determining whether the current temperature data exceeds the alarm threshold value, the method further includes:
s100: and performing confidence evaluation on the current temperature data, judging whether the current temperature data is credible, and if the current temperature data is evaluated to be credible, entering the step S11.
In step S100, the confidence evaluation of the current temperature data may be based on a time dimension, and whether the current temperature data is credible is determined by the credible attribute of the historical temperature data. Of course, the determination may be made by determining a trend of change in the temperature data.
According to the temperature alarm method provided by the embodiment of the application, the confidence evaluation is carried out on the current temperature data, whether the current temperature data is credible or not is judged, and the subsequent judgment steps are carried out when the current temperature data is credible, so that the situations of false alarm and missed alarm are reduced.
In a specific implementation, the processor, after acquiring the temperature data, usually draws the temperature data into a graph and sends the graph to the human-computer interaction device, so that an operator can know the temperature of the bearing and perform subsequent tracing. When the temperature data is found to be not credible, manual investigation is often required to ensure the safety of the locomotive. However, when the operator cannot check the graph in time, the operator still needs to check and confirm the data when the temperature data at a certain moment before the operator is checked is not reliable.
As shown in fig. 3, on the basis of the above embodiment, in this embodiment, if the current temperature data is evaluated as not trusted, the method further includes:
s101: and replacing the current temperature data with normal temperature data.
According to the temperature alarm method provided by the embodiment of the application, the current temperature data is replaced by the normal temperature data, so that the situation that operators repeatedly check the incredible temperature data during tracing and manpower and material resources are wasted can be prevented. Meanwhile, when a temperature change curve graph is drawn, the incredible current temperature data is replaced by normal temperature data, so that the drawn curve is smoother, and the temperature change trend of the bearing is more favorably checked.
On the basis of the foregoing embodiments, the present embodiment provides a specific method for replacing current temperature data with normal temperature data, including:
judging whether the temperature data of the same measuring point position of other shafts is normal temperature data or not when the current temperature data is obtained;
if not, calling the last normal temperature data which is obtained at the current measuring point position of the shaft for the last time to replace the current temperature data;
if so, calculating the difference value of the normal temperature data acquired at the same moment when the current measuring point position of the axis and the same measuring point positions of other axes are in the same position and are nearest, and adding the difference value to the temperature data at the same measuring point positions of other axes to replace the current temperature data.
It should be noted that the same position of the other axis measured point in this embodiment should be a bearing that has the same function as the current measured point of this axis, and in a specific implementation, the temperature data of the same position of the current measured point of this axis and the same position of the other axis measured point should be substantially the same within a certain range at the same time. According to the replacement method provided by the embodiment of the application, when the current temperature data is replaced, whether the temperature data of the same position of the same measuring point position of other shafts is normal temperature data or not is judged, and if the temperature data of the same measuring point position of other shafts is not normal temperature data, the current temperature data is replaced by the normal temperature data obtained last time at the current measuring point position of the shaft. If the measured temperature data is normal temperature data, calculating the difference between the normal temperature data acquired at the same moment when the current measured point position of the axis and the same measured point position of other axes are closest, wherein the difference can be positive or negative. And when the difference is added to the current measuring point position of the shaft to obtain the current temperature data, the temperature data obtained from the same measuring point positions of other shafts are used for replacing the current temperature data.
According to the temperature alarm method provided by the embodiment of the application, when the current temperature data is replaced, the temperature data of the same position of the same measuring point of other shafts or the latest normal temperature data at the current measuring point of the shaft is used for replacing the current temperature data, the temperature data similar to the latest normal temperature data is used for replacing the current temperature data, and the actual temperature data of the current measuring point of the shaft is reflected in a maximized mode. Meanwhile, when the temperature change curve graph is drawn, the current temperature data determined to be the abnormal temperature data or the current temperature data which does not meet the preset confidence condition is replaced by the normal temperature data, so that the drawn curve is smoother, and the temperature change trend of the bearing is more favorably checked.
Fig. 4 is a flowchart of another temperature alarm method provided in the embodiment of the present application, and as shown in fig. 4, on the basis of the above embodiment, the embodiment provides a specific method for performing confidence evaluation on current temperature data, where the method is step S1001 or step S1002.
S1001: judging whether the N1 temperature data acquired before the current temperature data is acquired are normal temperature data and the absolute temperature rise rate of each temperature data and the previous normal temperature data is not greater than a threshold value, if so, entering step S1003, otherwise, repeating the step until entering step S1003.
In step S1001, in the case where the current temperature data is acquired, N1 pieces of temperature data acquired before the current temperature data is acquired are further determined based on the time dimension, and it is confirmed whether the current temperature data is authentic according to the determination result. Wherein the temperature rise rate represents the amount of change between two temperature data, and the temperature rise rate is calculated in the manner of
Wherein, Delta T is temperature rise rate, TnewAs current temperature data, tnewTime of acquisition, T, for current temperature dataoldFor temperature data acquired before the acquisition of current temperature data, toldIs the acquisition time of the temperature data acquired before the current temperature data is acquired. The absolute temperature rise is an absolute value of the temperature rise. It is understood that, in order to ensure the accuracy of the judgment, the number of the acquired temperature data for judgment should be sufficient, the value of N1 should be as large as possible, but too much temperature data may cause the calculation amount of the processor to be too large. In a specific implementation, 8 or 10 temperature data can be selected from the N1 temperature data. It should be noted that the absolute temperature rise here refers to the absolute temperature rise of the latter temperature data, for example, N1 is 8, the first absolute temperature rise required for the determination is calculated by the second temperature data and the first temperature data, and the seventh absolute temperature rise required for the determination is calculated by the eighth temperature data and the seventh temperature data.
And judging whether the N1 temperature data are normal temperature data, wherein the absolute temperature rise rate of each temperature data and the absolute temperature rise rate of the previous normal temperature data are not greater than a first threshold value. For example, N1 selects 8, and if the 8 temperature data are all normal temperature data and the absolute temperature rise rate of each temperature data and the previous normal temperature data is not greater than the first threshold, it indicates that the current temperature data is the same as the previous normal temperature data and is authentic, and modifies the current temperature data to be authentic. Because the process of acquiring the temperature data is continuous, the processor continuously acquires new current temperature data, and therefore, if the current temperature data does not meet the preset confidence condition, for example, abnormal temperature data exists in 8 temperature data, the current temperature data is still untrustworthy, whether the next newly acquired current temperature data meets the preset confidence condition or not is judged, the first temperature data of the original 8 temperature data is discharged, and the current temperature data becomes the eighth temperature data in the judgment of the new current temperature data. It can be understood that, in this embodiment, two requirements need to be satisfied when the current temperature data satisfies the preset confidence condition, where firstly, the N1 temperature data are all normal temperature data, and secondly, the absolute temperature rise rate of each temperature data in the N1 temperature data and the previous normal temperature data is not greater than the first threshold. When abnormal temperature data occurs in the N1 pieces of temperature data, it is indicated that the temperature data are inaccurate, and it is not possible to confirm that the credible attribute of the current temperature data is credible. When the absolute temperature rise rate in the N1 temperature data exceeds the first threshold, it indicates that the sensor is fluctuated, and it is impossible to determine whether the interference disappears, and it is also impossible to determine the credible attribute of the current temperature data. It should be noted that, even if the temperature rises due to a fault of the bearing, the temperature data at this time is fault temperature data, and the absolute temperature rise rate of the fault temperature data may exceed the first threshold, it can be understood that, even if the temperature rises continuously, the absolute temperature rise rate of the fault temperature data also decreases with the rise of the temperature, the absolute temperature rise rate between every two fault temperature data is also smaller than the first threshold, a preset confidence condition is satisfied, and the fault temperature data also enters a judgment process of alarm.
S1002: judging whether the N2 temperature data acquired before the current temperature data is acquired are all normal temperature data, and the absolute temperature rise rate of each temperature data and the absolute temperature rise rate of the previous normal temperature data are not greater than a threshold value and show a monotonous rising or monotonous falling trend, if so, entering step S1003, otherwise, repeating the step until entering step S1003.
In step S1002, with respect to the determination method provided in the above embodiment, the N2 pieces of temperature data in the present embodiment need to be determined whether the trend is monotonously increasing or monotonously decreasing. It can be understood that, compared to the above method, the conditions of the determination method in this embodiment are more severe, and in the specific implementation, when the N2 temperature data have a monotone rising or monotone falling trend, it indicates that the bearing may have a fault, so the number of N2 may be less than that of N1, that is, N2 may be less than that of N1. Of course, to further improve accuracy, N2 may also be greater than N1. It should be noted that if N2 is 1, the logic of the method may also be implemented, but in a specific implementation, the accuracy of the determination cannot be guaranteed, so in practical use, N2 may be 6.
S1003: and confirming that the current temperature data is credible.
The temperature alarm method provided by the embodiment of the application judges whether the current temperature data meets the preset confidence condition through the historical temperature data based on the time dimension, confirms whether the current temperature data is credible, guarantees the judgment accuracy, further guarantees the alarm accuracy, and reduces the situations of false alarm and missed alarm.
In the above embodiments, the temperature alarm method is described in detail, and the present application also provides embodiments corresponding to the temperature alarm device. It should be noted that the present application describes the embodiments of the apparatus portion from two perspectives, one from the perspective of the function module and the other from the perspective of the hardware.
Fig. 5 is a structural diagram of another temperature alarm device provided in an embodiment of the present application, and as shown in fig. 5, the device includes:
an obtaining module 10, configured to obtain current temperature data;
the judging module 11 is used for judging whether the current temperature data exceeds an alarm threshold value, and if so, triggering the alarm evaluation module;
the alarm evaluation module 12 is configured to perform alarm evaluation on temperature data acquired before the current temperature data is acquired based on a time dimension, and determine whether a plurality of consecutive temperature data changes monotonically in temperature;
and the alarm module 13 is used for confirming whether to alarm or not according to the alarm evaluation result obtained by the alarm evaluation module.
The temperature alarm device provided by the application carries out alarm evaluation on the temperature data acquired before acquiring the current temperature data based on the time dimension when the current temperature data exceeds the alarm threshold value, and confirms whether to alarm or not according to the result of the alarm evaluation. Compared with the prior art, the alarm is given when the temperature data exceeds the alarm threshold value, the technical scheme is adopted, the alarm evaluation is carried out on the temperature data obtained before the current temperature data is obtained, the temperature data are judged based on the time dimension, the alarm is given when the alarm condition is met, the alarm accuracy is improved, and the false alarm condition is reduced.
Since the embodiments of the apparatus portion and the method portion correspond to each other, please refer to the description of the embodiments of the method portion for the embodiments of the apparatus portion, which is not repeated here.
Fig. 6 is a block diagram of another temperature alarm device provided in an embodiment of the present application, and as shown in fig. 6, the device includes: a memory 20 for storing a computer program;
a processor 21 for implementing the steps of the temperature alarm method according to the above embodiment when executing the computer program.
The temperature alarm device provided by the embodiment may include, but is not limited to, a smart phone, a tablet computer, a notebook computer, or a desktop computer.
The processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 21 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 21 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the display screen. In some embodiments, the processor 21 may further include an AI (Artificial Intelligence) processor for processing a calculation operation related to machine learning.
The memory 20 may include one or more computer-readable storage media, which may be non-transitory. Memory 20 may also include high speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In this embodiment, the memory 20 is at least used for storing a computer program 201, wherein after being loaded and executed by the processor 21, the computer program can implement the relevant steps of the temperature alarm method disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202, data 203, and the like, and the storage manner may be a transient storage manner or a permanent storage manner. Operating system 202 may include, among others, Windows, Unix, Linux, and the like. Data 203 may include, but is not limited to, alarm threshold values, fluctuation values, and the like.
In some embodiments, the temperature alarm device may further include a display 22, an input/output interface 23, a communication interface 24, a power source 25, and a communication bus 26.
Those skilled in the art will appreciate that the configuration shown in FIG. 6 does not constitute a limitation of the temperature alert device and may include more or fewer components than those shown.
The temperature alarm device provided by the embodiment of the application comprises a memory and a processor, wherein when the processor executes a program stored in the memory, the following method can be realized:
acquiring current temperature data;
judging whether the current temperature data exceeds an alarm threshold value;
if so, performing alarm evaluation on a plurality of continuous temperature data acquired before the current temperature data is acquired based on the time dimension, and judging whether the plurality of continuous temperature data are monotonously changed in temperature;
and confirming whether to alarm or not according to the result of the alarm evaluation.
Finally, the application also provides a corresponding embodiment of the computer readable storage medium. The computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps as set forth in the above-mentioned method embodiments.
It is to be understood that if the method in the above embodiments is implemented in the form of software functional units and sold or used as a stand-alone product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium and executes all or part of the steps of the methods described in the embodiments of the present application, or all or part of the technical solutions. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The temperature alarm method, device and medium provided by the present application are described in detail above. The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (13)
1. A temperature warning method, comprising:
acquiring current temperature data;
judging whether the current temperature data exceeds an alarm threshold value;
if so, performing alarm evaluation on a plurality of continuous temperature data acquired before the current temperature data is acquired based on the time dimension, and judging whether the plurality of continuous temperature data are monotonously changed in temperature;
and confirming whether to alarm or not according to the result of the alarm evaluation.
2. The temperature alarm method of claim 1, wherein said determining whether said consecutive plurality of said temperature data changes monotonically with temperature comprises:
judging whether the absolute value of the difference value between each temperature data and the last temperature data obtained last time in a plurality of continuous temperature data is smaller than a fluctuation value, if so, recording the temperature data as the last temperature data, and if not, keeping the temperature data unchanged;
judging whether the finally obtained different temperature data shows monotonous temperature change or not;
if so, determining that the plurality of continuous temperature data are in temperature monotonicity change, otherwise, determining that the plurality of continuous temperature data are not in temperature monotonicity change.
3. The temperature alarm method according to claim 2, wherein if the temperature data acquired before the current temperature data is acquired has no abnormal temperature data, the performing alarm evaluation on a plurality of consecutive temperature data acquired before the current temperature data is acquired comprises:
judging whether temperature monotony of continuous BN1 temperature data is changed into temperature monotony rising or not in the latest credible temperature data obtained before the current temperature data is obtained, if yes, confirming that the result of alarm evaluation is alarm, and if not, repeating the step until the result of alarm evaluation is alarm; and/or
Judging whether the most reliable temperature data obtained before the current temperature data is obtained has continuous BN2 temperature data which are monotonously changed and exceed the alarm threshold value, if so, determining that the alarm evaluation result is alarm, and if not, repeating the step until the alarm evaluation result is alarm.
4. The temperature alarm method according to claim 2, wherein if the temperature data acquired before the current temperature data is acquired has abnormal temperature data and is a special temperature value of the sensor, the alarm evaluation of the plurality of consecutive temperature data acquired before the current temperature data is acquired comprises:
judging whether the most reliable temperature data obtained before the current temperature data is obtained has continuous BN3 temperature data which are monotonously changed and exceed the alarm threshold value, if so, determining that the alarm evaluation result is alarm, and if not, repeating the step until the alarm evaluation result is alarm.
5. The temperature alarm method according to claim 2, wherein if the temperature data acquired before the current temperature data is acquired has abnormal temperature data and is not uniform to a specific temperature value of the sensor itself, the alarm evaluation of a plurality of consecutive temperature data acquired before the current temperature data is acquired comprises:
judging whether the most reliable temperature data obtained before the current temperature data is obtained has continuous BN4 temperature data which are monotonously changed and exceed the alarm threshold value, if so, determining that the alarm evaluation result is alarm, and if not, repeating the step until the alarm evaluation result is alarm.
6. The temperature alerting method of any one of claims 1 or 2, wherein the temperature monotonicity change comprises: the temperature is monotonously increased, or the temperature is monotonously decreased, or the temperature is increased first and then decreased.
7. The temperature alarm method according to claim 2, wherein before said determining whether the current temperature data exceeds the alarm threshold value, further comprising:
performing confidence evaluation on the current temperature data;
and if the current temperature data is evaluated to be credible, the step of judging whether the current temperature data exceeds the alarm threshold value is carried out.
8. The temperature alert method of claim 7, further comprising, if the current temperature data is assessed as not trustworthy:
and replacing the current temperature data with normal temperature data.
9. The temperature alerting method of claim 8, wherein the replacing the current temperature data with normal temperature data comprises:
judging whether the temperature data of the same measuring point position of other shafts is normal temperature data or not when the current temperature data is obtained;
if not, calling the last normal temperature data which is obtained at the current measuring point position of the shaft for the last time to replace the current temperature data;
if so, calculating the difference value of the normal temperature data acquired at the same time when the current measuring point position of the axis and the same measuring point position of the other axis are in the same position and are nearest, and adding the difference value to the temperature data at the same measuring point position of the other axis to replace the current temperature data.
10. The temperature alert method of any of claims 7 to 9, wherein the confidence evaluation of the current temperature data comprises:
judging whether the N1 temperature data acquired before the current temperature data is acquired are normal temperature data, and the absolute temperature rise rate of each temperature data and the absolute temperature rise rate of the previous normal temperature data are not greater than a threshold value, if so, determining that the current temperature data is credible, otherwise, repeating the step until the current temperature data is credible;
or judging whether the N2 temperature data acquired before the current temperature data is acquired are normal temperature data, wherein the absolute temperature rise rate of each temperature data and the absolute temperature rise rate of the previous normal temperature data are not greater than the threshold and show a monotonous rising or monotonous falling trend, if so, determining that the current temperature data is credible, and if not, repeating the step until determining that the current temperature data is credible.
11. A temperature warning device, comprising:
the acquisition module is used for acquiring current temperature data;
the judging module is used for judging whether the current temperature data exceeds an alarm threshold value, and if so, the alarm evaluating module is triggered;
the alarm evaluation module is used for carrying out alarm evaluation on the temperature data acquired before the current temperature data is acquired based on the time dimension and judging whether the continuous temperature data are monotonously changed in temperature or not;
and the alarm module is used for confirming whether to alarm or not according to the alarm evaluation result obtained by the alarm evaluation module.
12. A temperature warning device comprising a memory for storing a computer program;
a processor for implementing the steps of the temperature alert method as claimed in any one of claims 1 to 10 when executing the computer program.
13. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the temperature alert method according to any one of claims 1 to 10.
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