Sensor loop detection method and system, electronic equipment and storage medium

Abstract

The invention provides a sensor loop detection method and system, electronic equipment and a storage medium, and belongs to the technical field of sensor loop detection.The method comprises the steps that multiple sets of analog signals are generated, and each set of analog signals comprise multiple analog parameters; aiming at each group of analog signals, detecting a sensor loop of the target locomotive based on the group of analog signals to obtain a target parameter group corresponding to the group of analog signals; determining a detection result of each target parameter group based on each target parameter group and the corresponding standard parameter group; determining a target loop detection result based on the detection result of each target parameter group; the target loop detection result is used for representing the state of the sensor loop of the target locomotive. According to the sensor loop detection method and system, the electronic equipment and the storage medium provided by the invention, accurate analysis of the state of the sensor loop of the locomotive can be realized.

Description

Technical Field

[0001] This application belongs to the field of sensor loop detection technology, and more specifically, relates to a sensor loop detection method and system, electronic device, and storage medium. Background Technology

[0002] The locomotive sensor circuit is a data acquisition circuit that monitors the real-time operating status of various components of the locomotive, such as speed, rotational speed, temperature, and pressure. If the sensor signals are abnormal during operation, it will severely interfere with the crew's normal operation, inevitably endangering driving safety. Because it is difficult to accurately pinpoint the fault location after a locomotive malfunction, preventative component replacement by maintenance personnel leads to an expanded repair scope, increased maintenance costs, and indiscriminate replacement of locomotive parts, resulting in incomplete fault resolution and the creation of potential future problems.

[0003] Therefore, how to test the locomotive sensor circuit and achieve accurate analysis of the locomotive sensor circuit status has become an urgent problem to be solved. Summary of the Invention

[0004] The purpose of this application is to provide a sensor circuit detection method and system, electronic device, and storage medium to achieve accurate analysis of the sensor circuit status of a locomotive.

[0005] A first aspect of this application provides a sensor loop detection method, comprising: Multiple sets of simulated signals are generated, each containing multiple simulated parameters; each set of simulated signals is used to simulate different operating parameters of the target locomotive. For each set of analog signals, the sensor circuit of the target locomotive is detected based on the set of analog signals to obtain the target parameter set corresponding to the set of analog signals; the target parameter set consists of parameters detected by multiple sensors of the target locomotive. The detection results of each target parameter group are determined based on each target parameter group and its corresponding standard parameter group. The detection results of the target loop are determined based on the detection results of each set of target parameters; the detection results of the target loop are used to characterize the state of the sensor loop of the target locomotive.

[0006] A second aspect of this application provides a sensor loop detection system, comprising: The signal generation module is used to generate multiple sets of analog signals, each set of analog signals containing multiple analog parameters; each set of analog signals is used to simulate different operating parameters of the target locomotive. The testing module is used to detect the sensor circuits of the target locomotive based on each set of simulated signals to obtain the target parameter set corresponding to that set of simulated signals; the target parameter set consists of parameters detected by multiple sensors of the target locomotive. The comparison module is used to determine the detection results of each target parameter group based on each target parameter group and its corresponding standard parameter group; The output module is used to determine the target loop detection results based on the detection results of each set of target parameters; the target loop detection results are used to characterize the state of the sensor loop of the target locomotive.

[0007] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the sensor loop detection method described above.

[0008] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the sensor loop detection method described above.

[0009] A fifth aspect of this application provides a computer program product, including a computer program or computer-executable instructions, which, when executed by a processor, implement the steps of the above-described sensor loop detection method.

[0010] The beneficial effects of the sensor loop detection method and system, electronic device, and storage medium provided in this application are as follows: This application provides a comprehensive simulated operating scenario for sensor circuit detection by generating multiple sets of simulated signals covering various typical operating conditions of the locomotive. This overcomes the limitations of traditional detection methods, which rely on only a single or a few operating conditions and are unable to expose potential problems across the entire range, thus laying the foundation for comprehensive subsequent detection. Furthermore, by accurately matching simulated inputs with actual feedback and collecting real response data from simulated operating conditions, this provides a concrete basis for subsequently determining whether the circuit is normal. By comparing each set of target parameters with the corresponding standard parameter set, this application can accurately determine the normality of each parameter under a single operating condition, providing a direct criterion for locating local anomalies and avoiding the problem of ambiguous fault location in traditional detection. Finally, by combining the detection results of all sets of target parameters, the overall state of the target locomotive sensor circuit is determined, judging from a global perspective whether there are systemic problems or hidden faults in specific scenarios, forming a comprehensive and clear circuit state determination, and achieving accurate analysis of the locomotive's sensor circuit state. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 A schematic flowchart of a sensor loop detection method provided in an embodiment of this application; Figure 2 This is a structural block diagram of a sensor loop detection system provided in an embodiment of this application; Figure 3 This is a schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0013] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0014] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0015] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a sensor loop detection method provided in an embodiment of this application. The method can be executed by an electronic device, specifically a computer, server, or similar device. The method may include: S101: Generates multiple sets of analog signals, each set containing multiple analog parameters; each set of analog signals is used to simulate different operating parameters of the target locomotive.

[0016] In this embodiment, the analog signal refers to the electrical signal generated by technical means to simulate the normal operating state of the target locomotive, and its characteristics are consistent with the signals received by the sensors when the locomotive is actually running; the analog parameter is the specific quantitative index contained in the analog signal, and it is the basic unit that constitutes the analog signal; the target locomotive refers to the specific locomotive that needs to be detected by the sensor loop; the operating parameter refers to the key parameters that reflect the state of the target locomotive during actual operation.

[0017] In this embodiment, the simulated signal is a standard signal generated using microcontroller technology through the temperature signal module, pressure signal module, and speed signal module within the device. This signal is used to simulate the actual operating state of the target locomotive. The simulated parameters specifically include temperature, speed, and pressure, which directly correspond to the core physical quantities that the locomotive sensors need to detect. That is, the simulated signal, through its contained specific electrical signals, accurately reproduces the electrical signal characteristics of the sensor circuit during locomotive operation, thereby triggering the speedometer to display the corresponding value. The target locomotive can be a mainstream railway traction locomotive such as an HX-type electric locomotive or a diesel locomotive. The operating parameters can be locomotive speed, temperatures of various parts, and various pressures, which need to correspond to the simulated parameters.

[0018] Furthermore, the generation of analog signals relies on independent functional modules of the device. Specifically, the temperature signal module generates standard temperature signals and corresponding analog parameters within the 0-150℃ range; the speed signal module generates standard speed signals and corresponding analog parameters within the 0-200km / h range; and the pressure signal module generates standard pressure signals and corresponding analog parameters within the 0-1000Kp range. It is crucial to ensure that the parameter source for each set of analog signals is consistent with the device's hardware capabilities. Each set of analog signals must contain at least two independent analog parameters, such as speed and temperature, or pressure and temperature. The parameter combination must correspond to a typical operating scenario of the target locomotive to avoid a single parameter failing to fully reflect the loop state. Each signal set corresponds to a unique combination of operating parameters, and the differences in parameter values ​​between sets of signals must be able to distinguish different operating states, providing comprehensive scenario support for the dynamic response characteristics of the subsequent static detection sensor loop.

[0019] S102: For each set of analog signals, the sensor circuit of the target locomotive is detected based on the set of analog signals to obtain the target parameter set corresponding to the set of analog signals; the target parameter set consists of parameters detected by multiple sensors of the target locomotive.

[0020] In this embodiment, the sensor circuit refers to the locomotive data acquisition circuit composed of sensors, matching connecting lines, power modules, digital-to-analog converters, and instruments, which is responsible for collecting locomotive operating status parameters in real time; the target parameter set refers to the actual parameter set output by multiple sensors obtained by detecting a certain set of analog signals through the sensor circuit, and includes instrument display values ​​and sensor electrical signal parameters.

[0021] In this embodiment, each set of analog signals is precisely connected to the corresponding sensor circuit of the target locomotive via an interface device. For example, the speed analog signal is connected to the speed sensor circuit, the temperature analog signal to the temperature sensor circuit, and the pressure analog signal to the pressure sensor circuit, strictly ensuring that the transmission path of the analog signals is completely consistent with the path of the sensors receiving real signals during the actual operation of the target locomotive. The actual detection parameters of multiple sensors on the target locomotive are collected in real time through a test module. These parameters are quantitative data output by the sensors after receiving the analog signals, directly reflecting the circuit response state. All collected parameters are classified and matched to clarify the correspondence between each parameter in the target parameter group and the corresponding analog parameter in the analog signal. Simultaneously, it is ensured that each set of analog signals corresponds to only one independent target parameter group, avoiding cross-contamination of detection data from different analog signals. This lays a precise data foundation for subsequent comparison of the target parameter group with the standard parameter group and determination of individual detection results.

[0022] S103: Determine the detection results of each target parameter group based on each target parameter group and its corresponding standard parameter group.

[0023] In this embodiment, the standard parameter set is a set of ideal parameters preset for each group of analog signals, corresponding one-to-one with the analog parameters. Its values ​​are determined based on the expected response of the target locomotive sensor circuit under normal operating conditions, reflecting the standard feedback of the sensor circuit to a specific analog signal when there is no fault. The detection result is obtained by comparing a target parameter set with the corresponding standard parameter set, determining the pass / fail status or deviation degree of each parameter of the sensor circuit under that set of analog signals.

[0024] In this embodiment, when determining the detection results of each group based on each target parameter group and its corresponding standard parameter group, it is necessary to ensure that each target parameter group is only compared with the standard parameter group corresponding to the analog signal that generated the target parameter group, so as to avoid judgment errors caused by cross-group matching.

[0025] Furthermore, a deviation judgment threshold can be set. Based on the maintenance technical specifications of the target locomotive, an allowable deviation range is preset for each parameter in the standard parameter group, and this threshold must be adapted to the actual operating accuracy requirements of the sensor circuit. Each parameter in the target parameter group is compared with the corresponding parameter in the standard parameter group. If the parameter deviation is within the allowable threshold, the parameter is judged to be qualified; if the deviation exceeds the threshold, the parameter is marked as unqualified and the deviation value is recorded. Finally, the judgment results of all parameters are integrated to form the detection result of the target parameter group.

[0026] S104: Determine the target loop detection results based on the detection results of each group of target parameters; the target loop detection results are used to characterize the state of the sensor loop of the target locomotive.

[0027] In this embodiment, the target loop detection result is the final judgment on the overall status of the target locomotive sensor loop after comprehensively considering the detection results of all target parameter groups. Its core function is to determine whether the sensor loop is normal. If it is abnormal, it is necessary to locate the specific fault link and output loop status information that can directly guide the maintenance.

[0028] Furthermore, weights can be assigned to the detection results of each group of target parameters, and the detection results of each group can be weighted and integrated to determine the detection results of the target loop.

[0029] As can be seen from the above, this application embodiment generates multiple sets of simulated signals covering simulated inputs for various typical operating conditions of locomotives, providing a comprehensive simulated operating scenario for sensor circuit detection. This overcomes the limitations of traditional detection, which can only rely on a single or a few operating conditions and is difficult to expose potential problems across the entire range, laying the foundation for comprehensive subsequent detection. Furthermore, by accurately corresponding simulated inputs with actual feedback and collecting real response data from simulated operating conditions, specific evidence is provided for subsequent judgments on whether the circuit is normal. This application embodiment compares each set of target parameters with the corresponding standard parameter set, accurately determining whether each parameter is normal or not under a single operating condition, providing a direct criterion for locating local anomalies and avoiding the problem of ambiguous fault location in traditional detection. Finally, by combining the detection results of all sets of target parameter sets, the overall state of the target locomotive sensor circuit is determined, judging from a global perspective whether there are systemic problems or hidden faults in specific scenarios, forming a comprehensive and clear circuit state judgment, and realizing accurate analysis of the locomotive's sensor circuit state.

[0030] In one embodiment of this application, multiple analog parameters in each group of analog signals are independent of each other.

[0031] In this embodiment, mutual independence means that there is no correlation or interference between the multiple analog parameters contained in the same group of analog signals. That is, the setting of the value of any analog parameter, the signal generation or adjustment process will not affect the numerical accuracy or signal characteristics of other analog parameters in the same group. Each analog parameter can be adjusted and output independently within its preset range.

[0032] For example, consider a set of analog signals containing three analog parameters: speed (40 km / h), temperature (80°C), and pressure (300 kPa). The speed parameter is generated by a speed signal module, producing a 40 km / h pulse signal within the range of 0-200 km / h. The temperature parameter is generated by a temperature signal module, producing an 80°C voltage signal within the range of 0-150°C. The pressure parameter is generated by a pressure signal module, producing a 300 kPa current signal within the range of 0-1000 kPa. To verify the response of the speed sensor circuit, the host device sends a command to the speed signal module, for example, adjusting the speed parameter from 40 km / h to 60 km / h, and correspondingly generating a 60 km / h pulse signal within the range of 0-200 km / h. In this case, the temperature and pressure signal modules are unaffected.

[0033] As can be seen from the above, the embodiments of this application simulate independent parameters. When an anomaly is detected in a certain parameter of the target parameter group, the sensor circuit corresponding to the anomaly source can be directly identified without eliminating interference from other parameters. This avoids the problem of misjudging faulty components due to parameter coupling in traditional testing, significantly improving fault location efficiency and solving the problems of blindly replacing parts and reducing the scope of repair. Independent parameter adjustment does not require simultaneous calibration of other parameters. Operators can conduct variable tests on suspicious circuits separately, reducing the complexity of on-site operations. Furthermore, it eliminates the need to dismantle the coupling effects between parameters, simplifying the data processing flow, shortening maintenance time, and further improving testing efficiency.

[0034] In one embodiment of this application, for each set of analog signals, the sensor circuit of the target locomotive is detected based on that set of analog signals to obtain a set of target parameters corresponding to that set of analog signals, including: For each set of analog signals, the sensor circuit of the target locomotive is detected based on the set of analog signals to obtain the first target parameter corresponding to the set of analog signals; the first target parameter is the value displayed on the instrument. For each set of analog signals, the sensor circuit of the target locomotive is detected based on the set of analog signals to obtain the second target parameter corresponding to the set of analog signals; the second target parameter is the electrical signal parameter of the sensor circuit. By associating the first target parameter group with the second target parameter group, we obtain the target parameter group.

[0035] In this embodiment, the first target parameter refers to the parameter value directly read from the instrument of the target locomotive when detecting each set of analog signals. It is the intuitive display result presented to the operator after the sensor circuit signal is processed. The second target parameter refers to the electrical signal parameters collected from the sensor circuit of the target locomotive when detecting each set of analog signals. It is the raw signal data directly output by the sensor without instrument processing. The electrical signal parameters are the specific manifestation of the second target parameter, including quantifiable electrical signal characteristics such as voltage value, current value, and pulse frequency output by the sensor, which directly reflect the working status of the sensor.

[0036] In this embodiment, the first target parameter is the corresponding instrument in the target locomotive's cab, such as the speedometer, temperature gauge, and pressure gauge, which is directly observed. The displayed values ​​of the instruments after receiving the analog signal are recorded, ensuring that the readings correspond to the input of the analog signal. The second target parameter is obtained by connecting the detection end to the signal output end of the sensor circuit through the test module and interface device of the detection device. The electrical signal parameters output by the sensor are collected in real time, such as the pulse frequency of the speed sensor, the voltage value of the temperature sensor, and the current value of the pressure sensor. Finally, the first target parameter and the second target parameter corresponding to the same analog parameter are matched one by one to ensure that each parameter in the associated target parameter group can reflect the entire link status of the sensor circuit from the original signal to the instrument display under the same analog signal, and that each group of analog signals corresponds to only one group of associated target parameters to avoid data confusion.

[0037] For example, when collecting the first target parameter, the operator observes the speedometer, main transformer oil temperature gauge, and fuel pressure gauge in the locomotive cab, recording the speedometer reading 5 km / h, the oil temperature reading 30℃, and the fuel pressure reading 200 kPa. These three values ​​are the first target parameter corresponding to the simulated signal. When collecting the second target parameter, the test module is connected to the sensor circuit through the interface device of the detection device, collecting a pulse frequency of 100 Hz, a voltage value of 0.5 V, and a current value of 4 mA. These three electrical signal parameters are the second target parameter corresponding to the simulated signal. Finally, they are correlated to form the target parameter group: {speed, first target parameter 5 km / h, second target parameter 100 Hz; temperature, first target parameter 30℃, second target parameter 0.5 V; pressure, first target parameter 200 kPa, second target parameter 4 mA}, fully reflecting the signal transmission and instrument display status of the sensor circuit under the simulated operating condition.

[0038] As can be seen from the above, this embodiment of the application, by simultaneously collecting two types of parameters, can clearly locate whether the fault occurs in the sensor signal transmission link or the instrument display link. If the first target parameter is abnormal but the second target parameter is normal, the fault is determined to be an instrument fault; if both types of parameters are abnormal, the fault is determined to be a sensor or signal channel fault. This solves the problem of inaccurate fault diagnosis when relying solely on instrument displays in traditional testing, and avoids blindly replacing sensors. The target parameter set includes both intuitive display values ​​and raw electrical signal values. Compared with the traditional testing method that only collects instrument values, it can more comprehensively reflect the sensor circuit status. Maintenance personnel can quickly trace the fault point by comparing the deviations of the two types of parameters with the standard parameter set, without having to check the sensors, connecting wires, and other components one by one, greatly shortening maintenance time and improving work efficiency.

[0039] In one embodiment of this application, determining the target loop detection result based on the detection results of each set of target parameter groups includes: The weight of the detection result for each set of target parameters is determined based on a set of analog signals corresponding to each set of target parameters; The detection results of each target parameter group are weighted and calculated based on the weight of the detection results of each target parameter group to obtain the target loop detection results.

[0040] In this embodiment, the weight of each group of detection results is assigned based on the frequency of occurrence, safety impact level, and fault incidence of the operating conditions corresponding to the simulated signals in actual locomotive operation. Finally, the weight of each group of detection results is weighted and calculated with the detection results of the corresponding target parameter group to obtain the target loop detection result.

[0041] As can be seen from the above, the embodiments of this application, by allocating weights according to the importance of operating conditions, avoid the problem of low-frequency secondary operating conditions affecting the overall conclusion in traditional equal judgments, ensuring that the judgment results are directly linked to the actual operational risks of the locomotive. The weights can be flexibly adjusted according to the locomotive model and operating scenario, making the test results more relevant to specific application scenarios, solving the limitations of poor universality and insufficient specificity of traditional fixed judgment standards, and further improving the practicality of the test scheme.

[0042] In one embodiment of this application, determining the weight of the detection result for each set of target parameters based on a set of analog signals corresponding to each set of target parameters includes: For each set of target parameters, calculate the deviation of each simulated parameter in the set of simulated signals from its corresponding conventional operating condition parameters; the conventional operating condition parameters are those within a preset range. The weights of the detection results for the target parameter group are determined based on the deviation; the deviation and the weights are positively correlated.

[0043] In this embodiment, the normal operating condition parameters refer to the normal operating state parameters of the target locomotive during daily operation. Their values ​​are limited to a preset reasonable range, reflecting the typical parameter level when the locomotive is running normally and stably. The deviation refers to the degree of deviation between the value of each analog parameter in a set of analog signals and the corresponding normal operating condition parameters. The difference between the operating condition corresponding to the analog signal and the normal operating condition is reflected by quantitative calculation.

[0044] In this embodiment, firstly, based on the operational data statistics of the target locomotive, a preset range is set for each simulated parameter as the benchmark for deviation calculation. For each simulated parameter in each group of simulated signals, the deviation corresponding to the single parameter is calculated using the first formula. Furthermore, the larger the deviation, the higher the weight assigned, ensuring that the simulated signal that deviates further from the normal operating conditions has a higher proportion in the evaluation of the detection results.

[0045] As can be seen from the above, the embodiments of this application avoid the arbitrariness of subjective experience judgment by assigning weights to the deviation between simulated parameters and conventional operating conditions. This ensures that the weight allocation is based on quantifiable parameter differences, thereby improving the scientific rigor and consistency of the detection results. The positive correlation between deviation and weight means that the greater the deviation from conventional operating conditions, the greater the impact on the detection results, and the more likely it is to expose latent faults under such high-risk conditions. Furthermore, the parameters of conventional operating conditions can be flexibly adjusted according to the locomotive model and operating route, ensuring that the weight system always conforms to actual operating characteristics, further enhancing the adaptability of the detection scheme to different scenarios.

[0046] In one embodiment of this application, the process of determining the deviation includes: For each simulated parameter in each group of target parameters, the deviation of each simulated parameter from its corresponding conventional operating condition parameter is determined; the deviation is calculated using a first formula; the first formula is:

[0047] in, The deviation of the i-th simulation parameter; Let be the value of the i-th analog parameter in the analog signal; Let be the mean of the normal operating condition parameters of the i-th simulation parameter; Let be the standard deviation of the i-th simulation parameter under normal operating conditions; Let be the sensitivity coefficient of the i-th simulation parameter; The historical fault correlation coefficient of the i-th simulation parameter; This is the coupling correction term for the i-th simulation parameter.

[0048] In this embodiment, The calculation of deviation not only reflects the magnitude of parameter deviation, but also integrates the influence characteristics of the parameter on the circuit, historical fault correlation and multi-parameter coupling effect. It can more accurately reflect the actual impact of the parameter abnormality on the sensor circuit, and provide core quantitative basis for subsequent weight allocation of detection results and fault location. This is used to characterize the natural fluctuation range of the i-th parameter under normal operating conditions, through historical sample data of the i-th parameter under normal operating conditions, and the mean of that sample data. Calculated. The degree of influence of the i-th parameter on the overall performance of the sensor circuit or the safety of train operation can be measured by combining expert experience with statistical analysis of actual operating data, and by evaluating the degree of influence of each parameter on the overall performance of the sensor circuit or the safety of train operation based on the locomotive's design principles, operating mechanisms, and other knowledge. If a parameter is frequently associated with faults in history, then its historical fault correlation coefficient is large; otherwise, it is small. It can be determined through statistical analysis of fault data and in combination with the severity of the fault. This is used to correct the slight coupling effects between multiple parameters, making the calculation of the deviation of a single parameter more accurate, eliminating interference from other parameters caused by coupling, and analyzing the possible coupling effects between parameters based on the physical relationship and mathematical model between the parameters in the locomotive sensor circuit, thereby obtaining the coupling correction term.

[0049] In this embodiment, taking speed parameters as an example, multiple sets of speed data during normal locomotive operation are collected, and the average value of these data is calculated. Then, the standard deviation is calculated based on the mean and the data of each sample. Next, the sensitivity coefficient is determined based on the degree of influence of speed parameters on driving safety. The correlation coefficient of historical faults was determined by referring to the correlation between speed parameters and faults in historical data. Simultaneously, the coupling correction term is determined based on the coupling relationship between the velocity parameter and other parameters. Then, when obtaining the value of the velocity parameter in the current analog signal... Then, these values ​​are substituted into the first formula to calculate the deviation of the velocity parameters. .

[0050] Furthermore, for other simulation parameters, such as temperature and pressure, the same steps are followed to determine their respective relevant parameters and current values. Then, their respective deviations are calculated.

[0051] As can be seen from the above, the deviation calculation in this application not only reflects the magnitude of the parameter's value deviating from the average value under normal operating conditions, but also integrates the parameter's influence characteristics on the circuit, historical fault correlation, and multi-parameter coupling effect. Parameters with high sensitivity coefficients will yield relatively high results in deviation calculation even if the value deviation is not large, highlighting their importance to the sensor circuit or train safety. Parameters with large historical fault correlation coefficients will also have a correspondingly higher deviation if they deviate, making it easier to identify parameter anomalies that may cause faults in advance. On the other hand, this accurate deviation calculation can more precisely reflect the actual impact of the parameter anomaly on the sensor circuit, providing a core quantitative basis for the subsequent weight allocation of detection results and fault location, helping to more accurately judge the state of the sensor circuit, promptly detect potential faults, and ensure the safety and reliability of locomotive operation.

[0052] In one embodiment of this application, the deviation also includes a comprehensive deviation: The deviation of each simulation parameter is determined based on the corresponding conventional operating condition parameters, and the comprehensive deviation of the target parameter group is calculated. The overall deviation is calculated using the second formula; the second formula is:

[0053] in, The overall deviation of this single set of analog signals; The importance weight of the i-th simulation parameter; The working condition risk coefficient; This is a correction factor for historical failure frequency. The weights of the detection results for this set of target parameters are determined based on the deviation; including: The weights of the detection results for this set of target parameters are determined based on the deviation and the overall deviation.

[0054] In this embodiment, The overall deviation of the target parameter group is calculated using the second formula based on the deviation of each simulated parameter in each target parameter group. This is used to comprehensively reflect the impact of a set of simulated parameters on the sensor circuit. This represents the quantitative representation of the importance of the i-th parameter in sensor loop detection or driving safety, etc. The higher the importance, the greater the weight. It is used to measure the risk level of the locomotive operating condition corresponding to the current analog signal. The higher the risk, the larger the coefficient. It can be determined in combination with the locomotive's operating speed, operating environment and load conditions. The correction factor is determined based on the frequency of failures under the operating conditions corresponding to the historical set of simulation parameters. The higher the failure frequency, the larger the factor.

[0055] In this embodiment, based on the deviation of each simulation parameter in each target parameter group, a corresponding importance weight is assigned to each simulation parameter. Combined with the working condition risk coefficient Historical fault frequency correction factor Substitute the values ​​into the second formula to calculate and determine the overall deviation.

[0056] For example, suppose a set of target parameters includes three simulation parameters: velocity, temperature, and pressure. The deviation of the velocity parameter... Importance weight Deviation of temperature parameters Importance weight Deviation of pressure parameters Importance weight The current operating condition risk coefficient R = 1.2, and the historical failure frequency correction coefficient F = 0.3. Substitute these data into the second formula to calculate the overall deviation. The weights of the detection results for this set of target parameters are determined by combining the deviations of each simulation parameter and the overall deviation.

[0057] As can be seen from the above, the embodiments of this application, by calculating the comprehensive deviation degree, can comprehensively consider the deviation of multiple simulation parameters, as well as factors such as parameter importance, operating condition risk, and historical fault frequency, to more comprehensively and accurately reflect the impact of a set of simulation parameters on the sensor circuit. The weights of the detection results of the target parameter group are determined based on the deviation degree and the comprehensive deviation degree, making the weight allocation more scientific and reasonable. This leads to a more accurate determination of the detection results of the target circuit, providing a more reliable basis for fault diagnosis and condition assessment of locomotive sensor circuits, helping to promptly detect potential faults, and ensuring the safety and stability of locomotive operation.

[0058] Corresponding to the sensor loop detection method in the above embodiments, Figure 2 This is a structural block diagram of a sensor loop detection system provided according to an embodiment of this application. For ease of explanation, only the parts relevant to the embodiment of this application are shown. References Figure 2 The sensor loop detection system 20 includes: a signal generation module 21, a test module 22, a comparison module 23, and an output module 24.

[0059] The signal generation module 21 is used to generate multiple sets of analog signals, each set of analog signals containing multiple analog parameters; each set of analog signals is used to simulate different operating parameters of the target locomotive. Test module 22 is used to detect the sensor circuit of the target locomotive based on each set of simulated signals to obtain the target parameter set corresponding to the set of simulated signals; the target parameter set consists of parameters detected by multiple sensors of the target locomotive. Comparison module 23 is used to determine the detection results of each target parameter group based on each target parameter group and its corresponding standard parameter group; Output module 24 is used to determine the target loop detection result based on the detection results of each set of target parameters; the target loop detection result is used to characterize the state of the sensor loop of the target locomotive.

[0060] In one embodiment of this application, when determining the target loop detection result based on the detection results of each set of target parameter groups, the comparison module 23 is specifically used for: The weight of the detection result for each set of target parameters is determined based on a set of analog signals corresponding to each set of target parameters; The detection results of each target parameter group are weighted and calculated based on the weight of the detection results of each target parameter group to obtain the target loop detection results.

[0061] In one embodiment of this application, when determining the weight of the detection result of each set of target parameter groups based on a set of analog signals corresponding to each set of target parameter groups, the comparison module 23 is specifically used for: For each set of target parameters, calculate the deviation of each simulated parameter in the set of simulated signals from its corresponding conventional operating condition parameters; the conventional operating condition parameters are those within a preset range. The weights of the detection results for the target parameter group are determined based on the deviation; the deviation and the weights are positively correlated.

[0062] In one embodiment of this application, the comparison module 23 is specifically used in the process of determining the deviation degree to: For each simulated parameter in each group of target parameters, the deviation of each simulated parameter from its corresponding conventional operating condition parameter is determined; the deviation is calculated using a first formula; the first formula is:

[0063] in, The deviation of the i-th simulation parameter; Let be the value of the i-th analog parameter in the analog signal; Let be the mean of the normal operating condition parameters of the i-th simulation parameter; Let be the standard deviation of the i-th simulation parameter under normal operating conditions; Let be the sensitivity coefficient of the i-th simulation parameter; The historical fault correlation coefficient of the i-th simulation parameter; This is the coupling correction term for the i-th simulation parameter.

[0064] In one embodiment of this application, the comparison module 23 is specifically used to: The deviation of each simulation parameter is determined based on the corresponding conventional operating condition parameters, and the comprehensive deviation of the target parameter group is calculated. The overall deviation is calculated using the second formula; the second formula is:

[0065] in, The overall deviation of this single set of analog signals; The importance weight of the i-th simulation parameter; The working condition risk coefficient; This is a correction factor for historical failure frequency. The weights of the detection results for this set of target parameters are determined based on the deviation; including: The weights of the detection results for this set of target parameters are determined based on the deviation and the overall deviation.

[0066] In one embodiment of this application, multiple analog parameters in each group of analog signals are independent of each other.

[0067] In one embodiment of this application, when the test module 21 detects the sensor circuit of the target locomotive based on each set of analog signals to obtain the target parameter set corresponding to that set of analog signals, it is specifically used for: For each set of analog signals, the sensor circuit of the target locomotive is detected based on the set of analog signals to obtain the first target parameter corresponding to the set of analog signals; the first target parameter is the value displayed on the instrument. For each set of analog signals, the sensor circuit of the target locomotive is detected based on the set of analog signals to obtain the second target parameter corresponding to the set of analog signals; the second target parameter is the electrical signal parameter of the sensor circuit. By associating the first target parameter group with the second target parameter group, we obtain the target parameter group.

[0068] See Figure 3 , Figure 3 This is a schematic block diagram of an electronic device provided according to an embodiment of this application. Figure 3 The electronic device 300 in this embodiment may include one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memories 304 store computer programs, including program instructions. The processors 301 execute the program instructions stored in the memories 304. Specifically, the processors 301 are configured to invoke the program instructions to perform the functions of each module / unit in the above-described device embodiments, for example... Figure 2The functions of the signal generation module 21, test module 22, comparison module 23, and output module 24 are shown.

[0069] It should be understood that, in the embodiments of this application, the processor 301 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0070] Input device 302 may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint orientation information), a microphone, etc., and output device 303 may include a display (LCD, etc.), a speaker, etc.

[0071] The memory 304 may include read-only memory and random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include non-volatile random access memory. For example, the memory 304 may also store device type information.

[0072] In specific implementations, the processor 301, input device 302, and output device 303 described in the embodiments of this application can execute the implementation method described in the sensor loop detection method provided in the embodiments of this application, or they can execute the implementation method of the electronic device described in the embodiments of this application, which will not be repeated here.

[0073] In another embodiment of this application, a computer-readable storage medium is provided. This computer-readable storage medium stores a computer program, which includes program instructions. When executed by a processor, the program instructions implement all or part of the processes in the methods described above. Alternatively, the computer program can instruct related hardware to complete the process. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0074] The computer-readable storage medium can be an internal storage unit of the electronic device in any of the foregoing embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium can also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., provided on the electronic device. Furthermore, the computer-readable storage medium can include both internal and external storage units of the electronic device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0075] This application provides a computer program product, which includes computer-executable instructions or a computer program. The computer-executable instructions or computer program are stored in a computer-readable storage medium. The processor of an electronic device reads the computer-executable instructions from the computer-readable storage medium and executes the computer-executable instructions, causing the electronic device to perform the sensor loop detection method described in this application embodiment.

[0076] Those skilled in the art will recognize that the modules / units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0077] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the electronic devices and units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0078] In the several embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules, units, or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces or modules / units, or it may be an electrical, mechanical, or other form of connection.

[0079] The modules / units described as separate components may or may not be physically separate. Similarly, the components shown as modules / units may or may not be physical modules / units; they may be located in one place or distributed across multiple network modules / units. Some or all of the modules / units can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0080] Furthermore, the functional modules / units in the various embodiments of this application can be integrated into one processing module / unit, or each module / unit can exist physically separately, or two or more modules / units can be integrated into one module / unit. The integrated modules / units described above can be implemented in hardware or in the form of software functional modules / units.

[0081] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A sensor loop detection method, characterized in that, include: Multiple sets of simulated signals are generated, each containing multiple simulated parameters; each set of simulated signals is used to simulate different operating parameters of the target locomotive. For each set of analog signals, the sensor circuit of the target locomotive is detected based on the set of analog signals to obtain the target parameter set corresponding to the set of analog signals; the target parameter set consists of parameters detected by multiple sensors of the target locomotive. The detection results of each target parameter group are determined based on each target parameter group and its corresponding standard parameter group. The target loop detection results are determined based on the detection results of each set of target parameters; the target loop detection results are used to characterize the state of the sensor loop of the target locomotive.

2. The sensor loop detection method as described in claim 1, characterized in that, The determination of the target loop detection result based on the detection results of each set of target parameter groups includes: The weight of the detection result for each set of target parameters is determined based on a set of analog signals corresponding to each set of target parameters; The detection results of each target parameter group are weighted and calculated based on the weight of the detection results of each target parameter group to obtain the target loop detection results.

3. The sensor loop detection method as described in claim 2, characterized in that, The determination of the weight of the detection result for each set of target parameters based on a set of analog signals corresponding to each set of target parameters includes: For each set of target parameters, a set of simulated signals is used to calculate the deviation between each simulated parameter in the set of simulated signals and its corresponding conventional operating condition parameters; the conventional operating condition parameters are parameters within a preset range. The weight of the detection results of the target parameter group is determined based on the deviation; the deviation is positively correlated with the weight.

4. The sensor loop detection method as described in claim 3, characterized in that, The process of determining the deviation includes: For each simulated parameter in each group of target parameters, the deviation of each simulated parameter from its corresponding conventional operating condition parameter is determined; the deviation is calculated using a first formula; the first formula is: in, The deviation of the i-th simulation parameter; Let be the value of the i-th analog parameter in the analog signal; Let be the mean of the normal operating condition parameters of the i-th simulation parameter; Let be the standard deviation of the i-th simulation parameter under normal operating conditions; Let be the sensitivity coefficient of the i-th simulation parameter; The historical fault correlation coefficient of the i-th simulation parameter; This is the coupling correction term for the i-th simulation parameter.

5. The sensor loop detection method as described in claim 4, characterized in that, The deviation also includes a comprehensive deviation: The deviation of each simulation parameter is determined based on the corresponding conventional operating condition parameters, and the comprehensive deviation of the target parameter group is calculated. The overall deviation is calculated using the second formula; the second formula is: in, The overall deviation of this single set of analog signals; The importance weight of the i-th simulation parameter; The working condition risk coefficient; This is a correction factor for historical failure frequency. The determination of the weights of the detection results for the target parameter group based on the deviation includes: The weights of the detection results for the target parameter group are determined based on the deviation and the comprehensive deviation.

6. The sensor loop detection method as described in claim 1, characterized in that, The multiple analog parameters in each group of analog signals are independent of each other.

7. The sensor loop detection method as described in claim 1, characterized in that, For each set of analog signals, the sensor circuit of the target locomotive is detected based on that set of analog signals to obtain the target parameter set corresponding to that set of analog signals, including: For each set of analog signals, the sensor circuit of the target locomotive is detected based on the set of analog signals to obtain the first target parameter corresponding to the set of analog signals; the first target parameter is the instrument display value; For each set of analog signals, the sensor circuit of the target locomotive is detected based on the set of analog signals to obtain the second target parameter corresponding to the set of analog signals; the second target parameter is the electrical signal parameter of the sensor circuit. The first target parameter group and the second target parameter are associated to obtain the target parameter group.

8. A sensor loop detection system, characterized in that, The signal generation module is used to generate multiple sets of analog signals, each set containing multiple analog parameters; each set of analog signals is used to simulate different operating parameters of the target locomotive. The testing module is used to detect the sensor circuit of the target locomotive based on each set of simulated signals to obtain the target parameter set corresponding to that set of simulated signals; the target parameter set consists of parameters detected by multiple sensors of the target locomotive. The comparison module is used to determine the detection results of each target parameter group based on each target parameter group and its corresponding standard parameter group; The output module is used to determine the target loop detection results based on the detection results of each set of target parameters. The target loop detection results are used to characterize the state of the sensor loop of the target locomotive.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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