A system for analyzing vehicle status failure

Abstract

The present invention relates to the technical field of vehicle fault diagnosis, and in particular to a vehicle status fault analysis system, comprising a vehicle supervision platform, a vehicle information unit, a real-time evaluation unit, a working condition performance unit, a fault analysis unit and a management response unit; the present invention pre-processes preliminary data of vehicle target components, which helps to verify the validity of the collected data on the one hand, and provides data support for subsequent fault analysis on the other hand, and analyzes through information feedback and fusion, that is, a comprehensive analysis is performed from the two points of state and performance to determine whether the vehicle target layout is faulty, and at the same time, an in-depth analysis of the fault type is performed to understand whether the fault is a conventional fault or an unconventional fault, so as to perform reasonable and targeted maintenance according to the fault code and the fault type, and at the same time, it helps to reasonably arrange operation and maintenance personnel to improve the maintenance efficiency of the vehicle target components.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle fault diagnosis, and in particular to a vehicle state fault analysis system. Background Art

[0002] With the development of vehicle technology, especially the application of electronic technology and computer technology in vehicles, vehicle fault diagnosis is developing from traditional empirical diagnosis methods such as observation, hearing, smelling, touching, isolation, probing and comparison to a modern automobile fault diagnosis technology system with complete system based on information technology and supplemented by digital, integrated and intelligent diagnostic equipment.

[0003] However, in the prior art, it is impossible to pre-process the data of the internal components of the vehicle, which leads to a large deviation in the fault analysis, which is not conducive to the accurate maintenance and fault analysis of the internal components of the vehicle, and it is impossible to analyze the status and performance of the internal components of the vehicle, which reduces the comprehensiveness of the data analysis. At the same time, it is impossible to classify the fault types of the components of the same batch according to the fault codes, which is not conducive to the reasonable operation and maintenance management of the internal components of the vehicle, and reduces the operation and maintenance management efficiency of the vehicle;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a vehicle status fault analysis system to solve the above-mentioned technical defects. The present invention pre-processes the data of preliminary vehicle target components, which is helpful to verify the validity of the collected data on the one hand, and to provide data support for subsequent fault analysis on the other hand. It is also convenient to repair the collected data to improve the analysis efficiency and accuracy. The status and performance of the vehicle target components are analyzed by information feedback to improve the comprehensiveness of data analysis. The fault risk fusion assessment analysis is performed by information feedback and fusion, that is, a comprehensive analysis is performed from the two points of status and performance to determine whether the vehicle target layout is faulty, so as to provide timely early warning feedback management. At the same time, the fault type is analyzed in depth to understand whether the fault is a routine fault or an unconventional fault, so as to perform reasonable and targeted maintenance according to the fault code and fault type. At the same time, it helps to reasonably arrange operation and maintenance personnel to improve the maintenance efficiency of vehicle target components.

[0006] The object of the present invention can be achieved by the following technical solutions: A system for vehicle status fault analysis, comprising a vehicle supervision platform, a vehicle information unit, a real-time evaluation unit, a working condition performance unit, a fault analysis unit, and a management response unit;

[0007] The vehicle information unit is used to collect the working condition information of the target vehicle component, the working condition information includes operation status data and status performance data, and sends the operation status data and status performance data to the real-time evaluation unit and the working condition performance unit respectively;

[0008] The vehicle information unit is also used to perform data preprocessing, verification and analysis on the working condition information, and to distinguish and process the obtained timestamp offset value and loss error value to obtain a normal signal and a repair signal;

[0009] The live evaluation unit is used to respond to the normal signal and simultaneously perform state stability evaluation and analysis on the operation state data, and send the obtained state stability index to the fault analysis unit;

[0010] The working condition performance unit is used to respond to the normal signal, and at the same time perform feature extraction, supervision, evaluation and analysis on the state performance data to obtain a performance evaluation coefficient BX, and perform comparison and analysis on the performance evaluation coefficient BX to obtain a performance risk index BZ;

[0011] The fault analysis unit is used to perform a fault risk fusion assessment analysis on the state stability index and the performance risk index BZ, and to compare and analyze the obtained fault risk assessment coefficient G. If an alarm signal is obtained, the fault code of the vehicle target component corresponding to the alarm signal is obtained, and the fault code is deeply analyzed to obtain unconventional signals and conventional signals.

[0012] Preferably, the data preprocessing, verification and analysis process of the vehicle information unit is as follows:

[0013] The operating time period of the target vehicle component is collected and set as the time threshold, the working condition information of the target vehicle component within the time threshold is obtained, and then the timestamp offset value and loss error value in the working condition information are obtained, and the timestamp offset value and loss error value are judged and processed:

[0014] If there is no timestamp offset value and no loss error value, a normal signal is generated;

[0015] If there is a timestamp offset value or a missing error value, a repair signal is generated;

[0016] Among them, the timestamp offset value represents the number of times the actual timestamp in the operating condition information does not match the standard timestamp; the loss error value represents the sum of the number of times data is lost during the transmission of the operating condition information and the number of times the value after data transmission does not match the value before transmission.

[0017] Preferably, the state stability evaluation and analysis process of the live evaluation unit is as follows:

[0018] The time threshold is divided into i sub-time periods, where i is a natural number greater than zero. The operating status data of the vehicle target components in each sub-time period is obtained, and the operating status data includes characteristic performance values ​​and physical evaluation values. The characteristic performance values ​​and physical evaluation values ​​are compared and analyzed with the preset characteristic performance value thresholds and preset physical evaluation value thresholds entered and stored internally. If the characteristic performance value is less than the preset characteristic performance value threshold, and the physical evaluation value is less than the preset physical evaluation value threshold, then the corresponding sub-time period is determined to be a stable period, and the ratio between the corresponding number of stable time periods and the total number of sub-time periods is set as the state stability index.

[0019] Preferably, the characteristic performance value indicates the overlap time corresponding to the failure of the numerical value corresponding to the characteristic parameter of the vehicle target component to meet the preset condition, and the characteristic parameters include temperature and abnormal sound; the physical evaluation value indicates the product of the overlap time corresponding to the deviation of the numerical value corresponding to the working information of the vehicle target component from the preset threshold and the appearance difference value after data normalization processing, the working information includes working current and working power, and the appearance difference value indicates the difference between the appearance characteristic image of the vehicle target component and the standard characteristic image.

[0020] Preferably, the feature extraction, supervision, evaluation and analysis process of the operating condition performance unit is as follows:

[0021] The status performance data of the target vehicle components within the time threshold are obtained. The status performance data includes the operational risk value and the performance deviation value. The operational risk value and the performance deviation value are labeled as YF and XP respectively. The operational risk value YF and the performance deviation value XP are substituted into the formula to obtain the performance evaluation coefficient BX. The performance evaluation coefficient BX is compared and analyzed with the preset performance evaluation coefficient range stored in the internal input:

[0022] If the performance evaluation coefficient BX is greater than the maximum value in the preset performance evaluation coefficient range, it is determined to be a level 1 risk;

[0023] If the performance evaluation coefficient BX falls within the preset performance evaluation coefficient range, it is determined to be a level 2 risk;

[0024] If the performance evaluation coefficient BX is less than the minimum value in the preset performance evaluation coefficient range, it is determined to be a third-level risk, and the first-level risk, the second-level risk and the third-level risk are set as the performance risk index BZ, BZ=1, 2, 3.

[0025] Preferably, the operational efficiency risk value represents the ratio between the total heat generated by the target component of the vehicle and the preset actual total energy consumption; the performance deviation value represents the duration corresponding to the energy consumption rate of the target component of the vehicle exceeding the preset energy consumption rate threshold.

[0026] Preferably, the fault risk fusion assessment and analysis process of the fault analysis unit is as follows:

[0027] The state stability index and performance risk index BZ within the time threshold are obtained, the state stability index is labeled as ZW, and the state stability index ZW and the performance risk index BZ are substituted into the formula G=(ZW÷BZ)×(f1+f2+f3) to obtain the fault risk assessment coefficient, wherein f1 and f2 are respectively the preset weight factor coefficients of the state stability index ZW and the performance risk index BZ, f3 is the preset fault tolerance factor coefficient, f1, f2 and f3 are all greater than zero, G is the fault risk assessment coefficient, and the fault risk assessment coefficient G is compared and analyzed with the preset fault risk assessment coefficient threshold value stored in the internal input:

[0028] If the ratio between the fault risk assessment coefficient G and the preset fault risk assessment coefficient threshold is greater than or equal to 1, no signal is generated;

[0029] If the ratio between the fault risk assessment coefficient G and the preset fault risk assessment coefficient threshold is less than 1, an alarm signal is generated;

[0030] When an alarm signal is generated, the fault code of the target vehicle component corresponding to the alarm signal is obtained, and the fault code is analyzed in depth:

[0031] The number of the target vehicle components corresponding to the same fault code is obtained, and the number of the target vehicle components corresponding to the same fault code is set as the fault classification index, and the fault classification index is compared and analyzed with the preset fault classification index threshold value recorded and stored internally:

[0032] If the ratio between the fault classification index and the preset fault classification index threshold is less than 1, it is determined to be an irregular fault and an irregular signal is generated;

[0033] If the ratio between the fault classification index and the preset fault classification index threshold is greater than or equal to 1, it is determined to be a conventional fault and a conventional signal is generated.

[0034] The beneficial effects of the present invention are as follows:

[0035] (1) The present invention pre-processes the data of preliminary vehicle target components, which is helpful to verify the validity of the collected data on the one hand, and to provide data support for subsequent fault analysis on the other hand, and is convenient for repairing the collected data to improve the analysis efficiency and accuracy. The information feedback method is used to analyze the state and performance of the vehicle target components, that is, the state stability evaluation analysis is performed on the operating state data to understand the state stability of the vehicle target components, and the feature extraction supervision evaluation analysis is performed on the state performance data, so as to analyze from the perspective of the feature performance of the vehicle target components to understand the performance risk level of the vehicle target components;

[0036] (2) The present invention performs fault risk fusion assessment and analysis by means of information feedback and fusion, that is, a comprehensive analysis is performed from the two points of state and performance to determine whether the vehicle target layout is faulty, so as to provide timely early warning feedback management, and at the same time, an in-depth analysis of the fault type is performed to understand whether the fault is a routine fault or an unconventional fault, so as to perform reasonable and targeted maintenance according to the fault code and fault type, and at the same time, it helps to reasonably arrange operation and maintenance personnel to improve the maintenance efficiency of the vehicle target components. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention will be further described below in conjunction with the accompanying drawings;

[0038] Figure 1 It is a flowchart of the system of the present invention;

[0039] Figure 2 This is a local analysis diagram of Example 1 of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Embodiment 1:

[0042] See also Figure 1 to Figure 2 As shown, the present invention is a system for analyzing vehicle status faults, including a vehicle supervision platform, a vehicle information unit, a real-time evaluation unit, a working condition performance unit, a fault analysis unit, and a management response unit. The vehicle supervision platform is connected to the vehicle information unit in a one-way communication manner, the vehicle information unit is connected to the real-time evaluation unit, the working condition performance unit, and the management response unit in a one-way communication manner, the real-time evaluation unit and the working condition performance unit are connected to the fault analysis unit in a one-way communication manner, and the fault analysis unit is connected to the management response unit in a one-way communication manner;

[0043] When the vehicle supervision platform monitors the operation of the target vehicle component, a supervision instruction is generated and sent to the vehicle information unit. After receiving the supervision instruction, the vehicle information unit immediately collects the working condition information of the target vehicle component, the working condition information includes the operating status data and the status performance data, and sends the operating status data and the status performance data to the real-time evaluation unit and the working condition performance unit respectively;

[0044] In the embodiment of the present invention, the vehicle information unit is also used for data preprocessing, verification and analysis of the working condition information, which helps to verify the validity of the collected data on the one hand, and helps to provide data support for subsequent fault analysis on the other hand, and is convenient for repairing the collected data to improve the analysis efficiency. The specific data preprocessing, verification and analysis process is as follows:

[0045] The operating time period of the target vehicle component is collected and set as the time threshold, the working condition information of the target vehicle component within the time threshold is obtained, and then the timestamp offset value and loss error value in the working condition information are obtained, and the timestamp offset value and loss error value are judged and processed:

[0046] If the timestamp offset value and the loss error value do not exist, a normal signal is generated and sent to the live evaluation unit and the working condition performance unit;

[0047] If there is a timestamp offset value or a missing error value, a repair signal is generated and sent to the management response unit. After receiving the repair signal, the management response unit immediately performs timestamp alignment and missing data filling on the running status data and status performance data to ensure the accuracy of the data;

[0048] In the implementation of the present invention, the timestamp offset value indicates the number of times that the actual timestamp in the operating condition information does not match the standard timestamp; the loss error value indicates the sum of the number of times that data is lost during the transmission of the operating condition information and the number of times that the value after the data transmission does not match the value before the transmission; it should be noted that the timestamp offset value and the loss error value are two influencing parameters that reflect the accuracy of the operating condition information, and the target components of the vehicle include but are not limited to: motors, batteries, etc.;

[0049] The real-time evaluation unit is used to respond to normal signals and perform state stability evaluation and analysis on the operating state data to understand the state stability of the target components of the vehicle, so as to provide data support for subsequent fault analysis, and then obtain the stable period through the state stability evaluation and analysis, and further analyze the stable period to obtain the state stability index;

[0050] In the implementation of the present invention, the specific state stability evaluation and analysis process is as follows:

[0051] The time threshold is divided into i sub-time periods, where i is a natural number greater than zero, and the operating status data of the target vehicle components in each sub-time period is obtained, the operating status data including the characteristic performance value and the physical evaluation value, and the characteristic performance value and the physical evaluation value are compared and analyzed with the preset characteristic performance value threshold and the preset physical evaluation value threshold that are internally entered and stored. If the characteristic performance value is less than the preset characteristic performance value threshold, and the physical evaluation value is less than the preset physical evaluation value threshold, then the corresponding sub-time period is determined to be a stable time period, and the ratio between the number corresponding to the stable time period and the total number of sub-time periods is set as a state stability index, and the state stability index is sent to the fault analysis unit;

[0052] In the embodiment of the present invention, the characteristic performance value indicates the overlap time corresponding to the failure of the value corresponding to the characteristic parameter of the vehicle target component to meet the preset condition. The characteristic parameter includes temperature, abnormal sound, etc. It should be noted that the analysis is performed from the perspective of characteristic performance to understand the state of the vehicle target component so as to understand whether the vehicle has a fault.

[0053] In an embodiment of the present invention, the physical evaluation value represents the product of the overlap time corresponding to the deviation of the numerical value corresponding to the working information of the target vehicle component from the preset threshold and the appearance difference value after data normalization processing, the working information includes the working current, working power, etc., and the appearance difference value represents the difference between the appearance feature image of the target vehicle component and the standard feature image. It should be noted that analysis is performed from two points of working parameters and appearance to understand the risk situation of the target vehicle component.

[0054] Embodiment 2:

[0055] The working condition performance unit is used to respond to normal signals and perform feature extraction, supervision, evaluation and analysis on the state performance data, so as to analyze from the perspective of the characteristic performance of the vehicle target components, so as to understand the performance risk level of the vehicle target components, so as to further increase the comprehensiveness of data analysis. The specific feature extraction, supervision, evaluation and analysis process is as follows:

[0056] Obtain the status performance data of the target vehicle components within the time threshold. The status performance data includes the operational risk value and the performance deviation value. The operational risk value and the performance deviation value are labeled as YF and XP respectively. Substitute the operational risk value YF and the performance deviation value XP into the formula BX=(YF×a1+XP) 2×a2÷a3 to get the performance evaluation coefficient, a1 and a2 are the preset proportional factor coefficients of the operational risk value YF and the performance deviation value XP respectively, the proportional factor coefficient is used to correct the deviation of various parameters in the formula calculation process, so as to make the calculation result more accurate, a3 is the preset correction factor coefficient, a1, a2 and a3 are all greater than zero, BX is the performance evaluation coefficient, the performance evaluation coefficient BX is compared and analyzed with the preset performance evaluation coefficient range stored internally:

[0057] If the performance evaluation coefficient BX is greater than the maximum value in the preset performance evaluation coefficient range, it is determined to be a level 1 risk;

[0058] If the performance evaluation coefficient BX falls within the preset performance evaluation coefficient range, it is determined to be a level 2 risk;

[0059] If the performance evaluation coefficient BX is less than the minimum value in the preset performance evaluation coefficient range, it is determined as a third-level risk, wherein the fault risks corresponding to the first-level risk, the second-level risk and the third-level risk are successively reduced, and the first-level risk, the second-level risk and the third-level risk are set as the performance risk index BZ, BZ=1, 2, 3, that is, when the performance risk index BZ=1, it indicates a first-level risk, when the performance risk index BZ=2, it indicates a second-level risk, and when the performance risk index BZ=3, it indicates a third-level risk, and the performance risk index BZ is sent to the fault analysis unit;

[0060] In the embodiment of the present invention, the operational efficiency risk value represents the ratio between the total amount of heat generated by the target component of the vehicle and the preset actual total amount of energy consumption. It should be noted that the analysis is performed from the perspective of heat dissipation to understand the risk of insufficient heat dissipation of the target component of the vehicle, which in turn leads to an increase in the risk of vehicle abnormality;

[0061] In the embodiment of the present invention, the performance deviation value indicates the duration corresponding to the energy consumption rate of the vehicle target component exceeding the preset energy consumption rate threshold. It should be noted that the performance of the vehicle target component is understood by analyzing from the perspective of the energy consumption rate.

[0062] After receiving the state stability index and performance risk index BZ, the fault analysis unit immediately performs a fault risk fusion evaluation and analysis, so as to conduct a comprehensive analysis from the two points of state and performance to determine whether the vehicle target layout is faulty, so as to provide timely early warning feedback management. The specific fault risk fusion evaluation and analysis process is as follows:

[0063] The state stability index and performance risk index BZ within the time threshold are obtained, the state stability index is labeled as ZW, and the state stability index ZW and the performance risk index BZ are substituted into the formula G=(ZW÷BZ)×(f1+f2+f3) to obtain the fault risk assessment coefficient, wherein f1 and f2 are respectively the preset weight factor coefficients of the state stability index ZW and the performance risk index BZ, f3 is the preset fault tolerance factor coefficient, f1, f2 and f3 are all greater than zero, G is the fault risk assessment coefficient, and the fault risk assessment coefficient G is compared and analyzed with the preset fault risk assessment coefficient threshold value stored in the internal input:

[0064] If the ratio between the fault risk assessment coefficient G and the preset fault risk assessment coefficient threshold is greater than or equal to 1, no signal is generated;

[0065] If the ratio between the fault risk assessment coefficient G and the preset fault risk assessment coefficient threshold is less than 1, an alarm signal is generated. When the alarm signal is generated, the fault code of the vehicle target component corresponding to the alarm signal is obtained, and then the number of the vehicle target components corresponding to the same fault code is obtained, and the number of the vehicle target components corresponding to the same fault code is set as the fault classification index, and the fault classification index is compared and analyzed with the preset fault classification index threshold stored in the internal input:

[0066] If the ratio between the fault classification index and the preset fault classification index threshold is less than 1, it is determined to be an irregular fault and an irregular signal is generated;

[0067] If the ratio between the fault classification index and the preset fault classification index threshold is greater than or equal to 1, it is determined to be a conventional fault, a conventional signal is generated, and the unconventional signal and the conventional signal are sent to the management response unit. After receiving the unconventional signal and the conventional signal, the management response unit immediately displays the preset warning text and fault code corresponding to the unconventional signal and the conventional signal, so as to perform reasonable and targeted maintenance according to the fault code information, and at the same time help to reasonably arrange the operation and maintenance personnel to improve the maintenance efficiency of the target components of the vehicle;

[0068] In the embodiment of the present invention, the historical fault code list represents a list of historical fault codes of the vehicle;

[0069] In summary, the present invention performs preprocessing on the data of preliminary vehicle target components, which helps to verify the validity of the collected data on the one hand, and provides data support for subsequent fault analysis on the other hand, and is convenient for patching the collected data to improve the analysis efficiency and accuracy. The information feedback method is used to analyze the state and performance of the vehicle target components, that is, the state stability evaluation analysis is performed on the operating state data to understand the state stability of the vehicle target components, and the feature extraction supervision evaluation analysis is performed on the state performance data to analyze from the perspective of the feature performance of the vehicle target components to understand the performance risk level of the vehicle target components. The fault risk fusion evaluation analysis is performed by information feedback and fusion, that is, a comprehensive analysis is performed from the two points of state and performance to determine whether the vehicle target layout is faulty, so as to provide timely early warning feedback management, and at the same time, an in-depth analysis is performed on the fault type to understand whether the fault is a routine fault or an unconventional fault, so as to perform reasonable and targeted maintenance according to the fault code and fault type, and at the same time, it helps to reasonably arrange operation and maintenance personnel to improve the maintenance efficiency of the vehicle target components.

[0070] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0071] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. A vehicle status fault analysis system, characterized in that: It includes vehicle supervision platform, vehicle information unit, real-time evaluation unit, working condition performance unit, fault analysis unit and management response unit; The vehicle information unit is used to collect the working condition information of the target vehicle component, the working condition information includes operation status data and status performance data, and sends the operation status data and status performance data to the real-time evaluation unit and the working condition performance unit respectively; The vehicle information unit is also used to perform data preprocessing, verification and analysis on the working condition information, and to distinguish and process the obtained timestamp offset value and loss error value to obtain a normal signal and a repair signal; The live evaluation unit is used to respond to the normal signal and simultaneously perform state stability evaluation and analysis on the operation state data, and send the obtained state stability index to the fault analysis unit; The working condition performance unit is used to respond to the normal signal, and at the same time perform feature extraction, supervision, evaluation and analysis on the state performance data to obtain a performance evaluation coefficient BX, and perform comparison and analysis on the performance evaluation coefficient BX to obtain a performance risk index BZ; The fault analysis unit is used to perform a fault risk fusion assessment analysis on the state stability index and the performance risk index BZ, and compare and analyze the obtained fault risk assessment coefficient G. If an alarm signal is obtained, the fault code of the vehicle target component corresponding to the alarm signal is obtained, and the fault code is deeply analyzed to obtain an unconventional signal and a conventional signal; The data preprocessing, verification and analysis process of the vehicle information unit is as follows: The operating time period of the target vehicle component is collected and set as the time threshold, the working condition information of the target vehicle component within the time threshold is obtained, and then the timestamp offset value and loss error value in the working condition information are obtained, and the timestamp offset value and loss error value are judged and processed: If there is no timestamp offset value and no loss error value, a normal signal is generated; If there is a timestamp offset value or a missing error value, a repair signal is generated; The timestamp offset value indicates the number of times that the actual timestamp in the working condition information does not match the standard timestamp; the loss error value indicates the sum of the number of times that data is lost during the transmission of the working condition information and the number of times that the value after data transmission does not match the value before transmission; The state stability evaluation and analysis process of the live evaluation unit is as follows: The time threshold is divided into i sub-time periods, where i is a natural number greater than zero, and the operating status data of the vehicle target component in each sub-time period is obtained, the operating status data including the characteristic performance value and the physical evaluation value, and the characteristic performance value and the physical evaluation value are compared and analyzed with the preset characteristic performance value threshold and the preset physical evaluation value threshold that are internally entered and stored. If the characteristic performance value is less than the preset characteristic performance value threshold, and the physical evaluation value is less than the preset physical evaluation value threshold, then the corresponding sub-time period is determined to be a stable time period, and the ratio between the number corresponding to the stable time period and the total number of sub-time periods is set as the state stability index; The characteristic performance value indicates the overlap time corresponding to the value corresponding to the characteristic parameter of the vehicle target component not meeting the preset condition, and the characteristic parameters include temperature and abnormal sound; the physical evaluation value indicates the product value obtained by multiplying the overlap time corresponding to the value corresponding to the working information of the vehicle target component deviating from the preset threshold by the value of the appearance difference value after data normalization processing, the working information includes working current and working power, and the appearance difference value indicates the difference value between the appearance characteristic image of the vehicle target component and the standard characteristic image; The feature extraction, supervision, evaluation and analysis process of the working condition performance unit is as follows: Obtain the status performance data of the target vehicle components within the time threshold. The status performance data includes the operational risk value and the performance deviation value. The operational risk value and the performance deviation value are labeled as YF and XP respectively. Substitute the operational risk value YF and the performance deviation value XP into the formula BX=(YF×a1+XP) 2 ×a2÷a3 to obtain the performance evaluation coefficient BX, a1 and a2 are the preset proportional factor coefficients of the operational risk value YF and the performance deviation value XP respectively, a3 is the preset correction factor coefficient, a1, a2 and a3 are all greater than zero, and the performance evaluation coefficient BX is compared and analyzed with the preset performance evaluation coefficient range stored in the internal entry: If the performance evaluation coefficient BX is greater than the maximum value in the preset performance evaluation coefficient range, it is determined to be a level 1 risk; If the performance evaluation coefficient BX falls within the preset performance evaluation coefficient range, it is determined to be a level 2 risk; If the performance evaluation coefficient BX is less than the minimum value in the preset performance evaluation coefficient range, it is determined to be a third-level risk, and the first-level risk, the second-level risk and the third-level risk are set as the performance risk index BZ, BZ = 1, 2, 3; The operational efficiency risk value represents the ratio between the total amount of heat generated by the target vehicle component and the preset actual total amount of energy consumption; the performance deviation value represents the duration corresponding to the energy consumption rate of the target vehicle component exceeding the preset energy consumption rate threshold; The fault risk fusion assessment and analysis process of the fault analysis unit is as follows: The state stability index and performance risk index BZ within the time threshold are obtained, the state stability index is labeled as ZW, and the state stability index ZW and the performance risk index BZ are substituted into the formula G=(ZW÷BZ)×(f1+f2+f3) to obtain the fault risk assessment coefficient, wherein f1 and f2 are respectively the preset weight factor coefficients of the state stability index ZW and the performance risk index BZ, f3 is the preset fault tolerance factor coefficient, f1, f2 and f3 are all greater than zero, G is the fault risk assessment coefficient, and the fault risk assessment coefficient G is compared and analyzed with the preset fault risk assessment coefficient threshold value stored in the internal input: If the ratio between the fault risk assessment coefficient G and the preset fault risk assessment coefficient threshold is greater than or equal to 1, no signal is generated; If the ratio between the fault risk assessment coefficient G and the preset fault risk assessment coefficient threshold is less than 1, an alarm signal is generated; When an alarm signal is generated, the fault code of the target vehicle component corresponding to the alarm signal is obtained, and the fault code is analyzed in depth: The number of the target vehicle components corresponding to the same fault code is obtained, and the number of the target vehicle components corresponding to the same fault code is set as the fault classification index, and the fault classification index is compared and analyzed with the preset fault classification index threshold value recorded and stored internally: If the ratio between the fault classification index and the preset fault classification index threshold is less than 1, it is determined to be an irregular fault and an irregular signal is generated; If the ratio between the fault classification index and the preset fault classification index threshold is greater than or equal to 1, it is determined to be a conventional fault and a conventional signal is generated.

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