Vehicle fault monitoring system and method based on artificial intelligence

Abstract

The invention discloses a vehicle fault monitoring system and method based on artificial intelligence, and belongs to the technical field of vehicle monitoring. The method is used for solving the technical problems that in an existing scheme, the autonomous anomaly analysis and processing effect of vehicle machine faults is poor, and the autonomous fault management effect is poor. The method comprises the following steps: supervising and analyzing a reaction state clicked by a vehicle machine every time, implementing an active processing scheme, and digitally processing a supervising and analyzing result and a processing result corresponding to the active processing scheme to obtain a corresponding reaction state index and a reaction state supervising and processing sequence; according to the method, expansion processing is carried out on a reaction state supervision processing sequence obtained through early-stage processing of an individual vehicle infotainment device, data calculation is carried out on abnormal data obtained through expansion processing, data analysis is carried out on the overall operation state of the vehicle infotainment device, and dynamic management is carried out on operation and maintenance of the vehicle infotainment device according to an analysis result.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle monitoring, and in particular to a vehicle fault monitoring system and method based on artificial intelligence. Background Art

[0002] Vehicle fault monitoring refers to monitoring the operating status of the vehicle through a series of technical means to promptly detect potential faults or abnormal conditions. It is of great significance to ensure driving safety, improve vehicle maintenance efficiency and reduce maintenance costs.

[0003] When implementing existing vehicle fault monitoring solutions, most of them still stay at the level of single data monitoring statistics and judgment prompts. For example, they use different types of sensors to monitor and analyze alarm prompts. For the monitoring of vehicle computer faults, they cannot actively implement multi-dimensional abnormality verification and screening of vehicle computer abnormalities, and independently manage vehicle computer faults dynamically based on the verification and screening results, resulting in poor autonomous abnormality analysis and processing of vehicle computer faults and poor autonomous fault management. Summary of the invention

[0004] The purpose of the present invention is to provide a vehicle fault monitoring system and method based on artificial intelligence, which is used to solve the technical problems of poor autonomous abnormal analysis and processing of vehicle faults and poor autonomous fault management in existing solutions.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] A vehicle fault monitoring system based on artificial intelligence, including a vehicle computer fault monitoring and identification processing module, which is used to monitor and identify the real-time click reaction status of the vehicle computer, and actively perform abnormal processing analysis and digital processing of the abnormal operating status obtained by monitoring and identification in different dimensions, obtain corresponding click supervision results and upload them to the vehicle fault supervision platform in real time;

[0007] Among them, the vehicle computer's reaction after each click is monitored, counted and processed to determine whether the vehicle computer's reaction after being clicked is normal, and actively implement multi-dimensional abnormal cause analysis and active processing solutions for vehicle computers with abnormal reactions;

[0008] The reaction state obtained by monitoring and the processing results corresponding to the active processing scheme are digitally processed respectively to obtain the reaction state index of the click reaction;

[0009] Sorting and combining the reaction state indexes obtained by the supervision corresponding to all clicks on the vehicle computer, and obtaining the reaction state supervision processing sequence corresponding to all click reaction supervisions on the vehicle computer;

[0010] The vehicle computer fault monitoring and analysis management module is used to perform vehicle computer abnormality impact analysis according to the reaction state supervision processing sequence corresponding to all click reaction supervision of the vehicle computer, and adaptively implement targeted operation and maintenance management for the vehicle computer according to the analysis results;

[0011] Among them, the reaction state supervision processing sequence corresponding to all click reaction supervisions of the vehicle computer is traversed and analyzed. If the element values ​​in the reaction state supervision processing sequence are all 0, an overall normal reaction instruction is generated without any prompt;

[0012] If there are non-zero elements in the reaction state supervision processing sequence, the total number of non-zero elements Ny is counted and the abnormal impact formula is used Calculate and obtain the abnormal impact index Yy corresponding to all abnormal elements; where e is a natural constant; N is the total number of all elements in the reaction state supervision processing sequence; α is the abnormal impact standard value;

[0013] Data analysis of the abnormal impact index is performed to dynamically manage the operation and maintenance of the vehicle's onboard computers.

[0014] Preferably, when monitoring and counting the reaction of the vehicle computer after each click, a click supervision signal is generated when the user clicks the vehicle computer, and a click timestamp corresponding to the click supervision signal is obtained;

[0015] And, monitoring and counting the reaction of the vehicle computer after being clicked, if the vehicle computer reacts, generating a reaction implementation signal, and obtaining a reaction timestamp corresponding to the reaction implementation signal;

[0016] Calculate the reaction time difference Tf between the reaction timestamp and the click timestamp, and obtain the reaction state index Fz corresponding to the vehicle computer being clicked by the formula Fz=[Tf / Tf0]; where Tf0 is the standard reaction time difference corresponding to the vehicle computer; [] is the rounding function.

[0017] Preferably, when the reaction state index is analyzed to determine the reaction state corresponding to the click reaction, if the reaction state index is 0, a normal reaction instruction is generated and a prompt indicating that the reaction is normal is provided;

[0018] If the reaction state index is not 0, a reaction abnormality instruction is generated and a reaction abnormality prompt is given;

[0019] If the vehicle computer does not respond, a response loss signal is generated, and all response loss verification indicators YBi,i={1, 2, 3, ..., n} corresponding to the vehicle computer are obtained according to the response loss signal monitoring, where n is a positive integer;

[0020] All acquired reaction loss verification indicators are analyzed through the indicator state recognition function, and the indicator state values ​​ZZi corresponding to different reaction loss verification indicators are output;

[0021] The indicator status value includes a value of 0 or 1, indicating whether the indicator status of the corresponding response loss verification indicator is normal or abnormal;

[0022] All indicator status values ​​obtained from the processing of the response loss verification indicators are sorted and combined to obtain the corresponding indicator status processing sequence.

[0023] Preferably, the expression of the indicator state identification function is: Where Ui is the standard range of verification indicators corresponding to different reaction loss verification indicators.

[0024] Preferably, data analysis is performed on the indicator status processing sequence to determine the rescue implementation status corresponding to the vehicle computer response loss of connection;

[0025] Conduct traversal analysis on the indicator status processing sequence;

[0026] If the element values ​​in the indicator status processing sequence are all 0, an active processing instruction is generated, and the system version number corresponding to the vehicle computer is obtained according to the active processing instruction, and the obtained system version number is traversed and matched with the pre-built version requirement database.

[0027] Preferably, if there is a sample system version number in the version requirement database that is consistent with the obtained system version number, then necessary instructions for implementing the rescue are generated and a prompt is given to implement the rescue implementation plan, and at the same time, the reaction state index corresponding to the click reaction is set to -1;

[0028] If there is no sample system version number consistent with the obtained system version number in the version requirement database, a system update instruction is generated and the system version of the vehicle computer is autonomously controlled to be updated to the system version corresponding to the oldest sample system version number in the version requirement database, and the updated vehicle computer status is retroactively evaluated.

[0029] Preferably, if the updated vehicle computer status response is normal, an active processing effective instruction is generated and the total number of active processing effective times is increased by one;

[0030] If the vehicle computer status response after the update is still abnormal, an active processing invalid instruction is generated and the total number of active processing invalid times is increased by one.

[0031] Preferably, if the value of an element in the indicator state processing sequence is 1, a rescue delay instruction is generated, and the reaction loss verification indicator corresponding to the element with a value of 1 is obtained and marked as an abnormal indicator, and the corresponding abnormal processing scheme is implemented for the abnormal indicator, and the reaction state index corresponding to the click reaction is set to -2;

[0032] The reaction state indexes obtained by the supervision corresponding to different click reactions of the vehicle computer are arranged and combined in the time sequence of the click timestamps to obtain the reaction state supervision processing sequence corresponding to all click reaction supervisions of the vehicle computer.

[0033] Preferably, if the abnormal impact index is less than 1, a second operation and maintenance signal is generated and the existing operation and maintenance cycle of the vehicle computer is shortened;

[0034] If the abnormal impact index is greater than 1, a first operation and maintenance signal is generated and the user is prompted to immediately perform operation and maintenance management on the vehicle computer.

[0035] A vehicle fault monitoring method based on artificial intelligence, comprising:

[0036] Monitor and identify the real-time click response status of the vehicle computer, and actively perform abnormal processing analysis and digital processing of the abnormal operating status obtained through monitoring and identification in different dimensions, obtain the corresponding click supervision results and upload them to the vehicle fault supervision platform in real time;

[0037] According to the reaction status supervision processing sequence corresponding to all click reaction supervisions of the vehicle computer, the vehicle computer abnormality impact analysis is implemented, and the vehicle computer is adaptively implemented with targeted operation and maintenance management based on the analysis results.

[0038] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0039] The present invention performs supervision and analysis on the reaction state of the vehicle computer each time it is clicked and implements an active processing plan, and digitally processes the results of the supervision and analysis and the processing results corresponding to the active processing plan to obtain the corresponding reaction state index. While realizing the digital representation of the local reaction state of the vehicle computer each time it is clicked, it can also provide reliable local supervision data support for the corresponding overall reaction state analysis and operation and maintenance dynamic management of the subsequent vehicle computer, thereby improving the autonomous abnormal analysis and processing effect of vehicle computer faults.

[0040] The present invention expands the reaction status supervision processing sequence obtained by the early processing of the individual vehicle computer, performs data calculation on the abnormal data obtained by the expanded processing and performs data analysis on the overall operating status of the vehicle computer, and dynamically manages the operation and maintenance of the vehicle computer according to the analysis results, thereby improving the autonomous fault management effect of the vehicle computer itself. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The present invention will be further described below in conjunction with the accompanying drawings.

[0042] Figure 1 This is a module block diagram of a vehicle fault monitoring system based on artificial intelligence of the present invention.

[0043] Figure 2 The present invention is a flowchart of a vehicle fault monitoring method based on artificial intelligence. DETAILED DESCRIPTION

[0044] 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.

[0045] Example 1: Figure 1 As shown, the present invention is a vehicle fault monitoring system based on artificial intelligence, including a vehicle fault monitoring platform, and a vehicle machine fault monitoring and identification processing module connected to the vehicle fault monitoring platform in communication;

[0046] The vehicle computer fault monitoring and identification processing module is used to monitor and identify the real-time click response status of the vehicle computer, and actively perform abnormal processing analysis and digital processing of the abnormal operating status obtained by monitoring and identification in different dimensions, obtain the corresponding click supervision results and upload them to the vehicle fault supervision platform in real time; including:

[0047] When monitoring and counting the reaction of the vehicle computer after each click, a click supervision signal is generated when the user clicks the vehicle computer, and a click timestamp corresponding to the click supervision signal is obtained; the unit of the click timestamp is accurate to milliseconds;

[0048] Among them, the monitoring of the vehicle computer being clicked can be achieved by using the controller in the vehicle computer to determine the position of the touch point according to the change of resistance or charge, and combining the driver in the vehicle computer operating system and the click event processing mechanism of the user interface layer;

[0049] Also, monitor and count the reaction of the vehicle computer after being clicked. If the vehicle computer reacts, a reaction implementation signal is generated, and a reaction timestamp corresponding to the reaction implementation signal is obtained; the unit of the reaction timestamp is also accurate to milliseconds; the reaction of the vehicle computer can be monitored according to the operation of the driver and different software in the vehicle computer operating system;

[0050] Calculate the reaction time difference Tf between the reaction timestamp and the click timestamp, and calculate the reaction state index Fz corresponding to the vehicle computer after being clicked through the formula Fz=[Tf / Tf0]; where Tf0 is the reaction standard time difference corresponding to the vehicle computer, which is determined according to the operation design data corresponding to the vehicle computer; [] is the rounding function;

[0051] It should be noted that the reaction state index is used to calculate and digitally represent the reaction state of the vehicle after the vehicle computer is clicked;

[0052] Generally speaking, users expect the click response time to be within 100 milliseconds, because the response within this time range gives people a relatively immediate feeling; if the response time exceeds 200 milliseconds, users may feel sluggish or unsmooth; and if the response time exceeds 500 milliseconds, users may feel that the system is stuck or unresponsive.

[0053] When the reaction state index is analyzed to determine the reaction state corresponding to the click reaction, if the reaction state index is 0, a normal reaction instruction is generated and a prompt indicating a normal reaction is given;

[0054] If the reaction state index is not 0, a reaction abnormality instruction is generated and a reaction abnormality prompt is given;

[0055] It should be noted that when the vehicle computer responds, there are situations where the response is normal or abnormal, and there are also situations where there is no response, which requires further supervision and analysis;

[0056] If the vehicle computer does not respond, a response loss signal is generated, and all response loss verification indicators YBi,i={1, 2, 3, ..., n} corresponding to the vehicle computer are obtained according to the response loss signal monitoring, where n is a positive integer; the response loss verification indicators include but are not limited to the computer real-time memory indicator and the real-time ambient temperature indicator;

[0057] It should be noted that when the real-time memory usage of the vehicle computer is large and the real-time ambient temperature is abnormal, it will affect the normal response of the vehicle computer when it is clicked. Therefore, it is necessary to implement digital processing and analysis of different response loss verification indicators;

[0058] All acquired reaction loss verification indicators are analyzed through the indicator state recognition function, and the indicator state values ​​ZZi corresponding to different reaction loss verification indicators are output;

[0059] Among them, the expression of the indicator state identification function is Where Ui is the verification index standard range corresponding to different reaction loss verification indexes, which can be determined according to the operation design data corresponding to the vehicle computer;

[0060] It should be noted that the indicator status value is used to digitally represent the indicator status corresponding to different reaction loss verification indicators;

[0061] The indicator status value includes a value of 0 or 1, indicating whether the indicator status of the corresponding response loss verification indicator is normal or abnormal;

[0062] Sorting and combining all indicator status values ​​obtained by processing the disconnection verification indicators to obtain a corresponding indicator status processing sequence;

[0063] In the embodiment of the present invention, by processing and digitally representing the indicator states of different reaction loss verification indicators, a reliable basis can be provided for the implementation of subsequent active processing solutions;

[0064] Perform data analysis on the indicator status processing sequence to determine the rescue implementation status corresponding to the vehicle computer response loss of connection;

[0065] Conduct traversal analysis on the indicator status processing sequence;

[0066] If the values ​​of the elements in the indicator status processing sequence are all 0, an active processing instruction is generated, and the system version number corresponding to the vehicle computer is obtained according to the active processing instruction, and the obtained system version number is traversed and matched with the pre-built version requirement database;

[0067] It can be understood that the element values ​​in the indicator status processing sequence are all 0, indicating that the indicator status corresponding to all reaction loss verification indicators are normal, so an active processing solution can be implemented to actively process abnormal reactions;

[0068] In addition, the version requirement database pre-stores several latest sample system version numbers, such as three sample system version numbers sorted by the latest update time, and the system versions corresponding to the several latest sample system version numbers can solve different anomalies that have occurred in the vehicle computer history;

[0069] If the version requirement database contains a sample system version number that is consistent with the obtained system version number, then necessary rescue implementation instructions are generated and a rescue implementation plan is prompted, and the reaction state index corresponding to the click reaction is set to -1; this means that the system version corresponding to the vehicle computer is not an old version, there is no abnormality at the system level, and manual intervention is required for processing;

[0070] If there is no sample system version number consistent with the obtained system version number in the version requirement database, a system update instruction is generated and the system version of the vehicle computer is autonomously controlled to be updated to the system version corresponding to the oldest sample system version number in the version requirement database, and the updated vehicle computer status is retroactively evaluated;

[0071] If the updated vehicle computer status responds normally, an active processing valid instruction is generated and the total number of active processing valid times is increased by one;

[0072] If the vehicle computer status response after the update is still abnormal, an active processing invalid instruction is generated and the total number of active processing invalid times is increased by one;

[0073] It is worth noting that in the embodiment of the present invention, by retrospectively evaluating the updated vehicle computer status, it is possible to obtain the corresponding processing results after the implementation of the active processing solution, and provide reliable local supervision analysis data support for the optimization management of the subsequent active processing solution, thereby improving the diversity of supervision data processing and expanded utilization;

[0074] If the value of an element in the indicator status processing sequence is 1, a rescue delay instruction is generated, and the reaction loss verification indicator corresponding to the element with a value of 1 is obtained and marked as an abnormal indicator. At the same time, the corresponding abnormal processing plan is implemented for the abnormal indicator, and the reaction state index corresponding to the click reaction is set to -2; for example, when the abnormal indicator is the real-time memory indicator of the vehicle computer, all software running on the vehicle computer is closed and restarted to increase the total amount of real-time memory available on the vehicle computer;

[0075] The reaction state indexes obtained by the supervision corresponding to different click reactions of the vehicle computer are arranged and combined according to the time sequence of the click timestamps to obtain the reaction state supervision processing sequence corresponding to all click reaction supervisions of the vehicle computer;

[0076] In the embodiment of the present invention, by monitoring and analyzing the reaction state of the vehicle computer each time it is clicked and implementing an active processing plan, and digitally processing the results of the monitoring and analysis and the processing results corresponding to the active processing plan, respectively, to obtain a corresponding reaction state index, it is possible to digitally represent the local reaction state of the vehicle computer each time it is clicked, and at the same time provide reliable local monitoring data support for the overall reaction state analysis and operation and maintenance dynamic management corresponding to the subsequent vehicle computer, thereby improving the autonomous abnormal analysis and processing effect of vehicle computer faults.

[0077] Embodiment 2: Based on the technical solution of Embodiment 1, it also includes:

[0078] The vehicle computer fault monitoring and analysis management module is used to perform vehicle computer abnormality impact analysis according to the reaction state supervision processing sequence corresponding to all click reaction supervision of the vehicle computer, and adaptively implement targeted operation and maintenance management for the vehicle computer according to the analysis results; including:

[0079] The reaction state supervision processing sequence corresponding to all click reaction supervisions of the vehicle computer is traversed and analyzed. If the element values ​​in the reaction state supervision processing sequence are all 0, an overall normal reaction instruction is generated without any prompt;

[0080] If there are non-zero elements in the reaction state supervision processing sequence, the total number of non-zero elements Ny is counted and the abnormal impact formula is used Calculate and obtain the abnormal impact index Yy corresponding to all abnormal elements; where e is a natural constant; N is the total number of all elements in the reaction state supervision processing sequence; α is the abnormal impact standard value, which is determined according to the operational abnormality design requirement data corresponding to the vehicle computer, or can be determined according to the median value of all historical abnormal impact indexes corresponding to different vehicle computers;

[0081] It should be noted that the abnormal impact index is used to calculate the abnormal data of all historical supervision corresponding to the individual vehicle computer to digitally represent the overall operating status of the vehicle computer;

[0082] Perform data analysis on the abnormal impact index to dynamically manage the operation and maintenance of the vehicle computers;

[0083] If the abnormal impact index is less than 1, a second operation and maintenance signal is generated and the existing operation and maintenance cycle of the vehicle computer is shortened; the specific shortening ratio may be half of the corresponding duration of the existing operation and maintenance cycle;

[0084] If the abnormal impact index is greater than 1, a first operation and maintenance signal is generated and the user is prompted to immediately perform operation and maintenance management on the vehicle computer;

[0085] In the embodiment of the present invention, by performing an extended processing on the reaction state supervision processing sequence obtained by the early processing of the individual vehicle computer, and performing data calculation on the abnormal data obtained by the extended processing and data analysis on the overall operation state of the vehicle computer, the operation and maintenance of the vehicle computer to which it belongs is dynamically managed according to the analysis results, thereby improving the autonomous fault management effect of the vehicle computer itself;

[0086] Embodiment 3: Based on the technical solutions of Embodiment 1 and Embodiment 2, it also includes:

[0087] The vehicle computer fault active processing management module is used to collect statistics based on the active processing results corresponding to all the same vehicle computers and implement active processing effectiveness analysis, and adaptively implement targeted optimization management of the existing active processing solutions based on the analysis results; including:

[0088] Count the total number of active processing valid times N1 and the total number of active processing invalid times N2 corresponding to all the same vehicle computers, and use the active processing valid formula Calculate and obtain the effective reliability index Kx corresponding to the existing active processing solution; where β is the effective standard value of active processing, which can be determined according to the active processing design requirements corresponding to the existing active processing solution, or can be customized by a specialist technician in this field according to the application requirements of the actual vehicle computer;

[0089] It should be noted that the effective reliability index is used to calculate and digitally represent the data of the effective status of the active treatment corresponding to the existing active treatment scheme;

[0090] When performing data analysis on the effective reliability index to determine the active processing status corresponding to the existing active processing solution;

[0091] If the effective reliability index is greater than or equal to 0, an overall effective instruction for active processing is generated and the existing active processing plan is maintained;

[0092] Otherwise, an active overall invalidation instruction is generated and the existing active processing solution is optimized and managed; wherein, the optimization management is specific to shortening the corresponding upgrade interval for the existing system version upgrade.

[0093] In the embodiment of the present invention, by statistically analyzing the active processing results corresponding to all the same vehicle computers and implementing active processing effectiveness analysis, and adaptively implementing targeted optimization management of the existing active processing solutions based on the analysis results, autonomous supervision analysis and automatic dynamic management of the active processing solutions are achieved, thereby improving the autonomous management effect of the exception processing support dimension.

[0094] Example 4: Figure 2 As shown, the present invention is a vehicle fault monitoring method based on artificial intelligence, comprising:

[0095] Monitor and identify the real-time click response status of the vehicle computer, and actively perform abnormal processing analysis and digital processing of the abnormal operating status obtained through monitoring and identification in different dimensions, obtain the corresponding click supervision results and upload them to the vehicle fault supervision platform in real time;

[0096] According to the reaction status supervision processing sequence corresponding to all click reaction supervisions of the vehicle computer, the vehicle computer abnormality impact analysis is implemented, and the vehicle computer is adaptively implemented with targeted operation and maintenance management based on the analysis results.

[0097] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0098] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0099] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0100] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0101] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A vehicle fault monitoring system based on artificial intelligence, characterized in that: It includes a vehicle computer fault monitoring and identification processing module, which is used to monitor and identify the real-time click response status of the vehicle computer, and actively perform abnormal processing analysis and digital processing of the abnormal operating status obtained by monitoring and identification in different dimensions, obtain the corresponding click supervision results and upload them to the vehicle fault supervision platform in real time; Among them, the vehicle computer's reaction after each click is monitored, counted and processed to determine whether the vehicle computer's reaction after being clicked is normal, and actively implement multi-dimensional abnormal cause analysis and active processing solutions for vehicle computers with abnormal reactions; The reaction state obtained by monitoring and the processing results corresponding to the active processing scheme are digitally processed respectively to obtain the reaction state index of the click reaction; Sorting and combining the reaction state indexes obtained by the supervision corresponding to all clicks on the vehicle computer, and obtaining the reaction state supervision processing sequence corresponding to all click reaction supervisions on the vehicle computer; The vehicle computer fault monitoring and analysis management module is used to perform vehicle computer abnormality impact analysis according to the reaction state supervision processing sequence corresponding to all click reaction supervision of the vehicle computer, and adaptively implement targeted operation and maintenance management for the vehicle computer according to the analysis results; Among them, the reaction state supervision processing sequence corresponding to all click reaction supervisions of the vehicle computer is traversed and analyzed. If the element values ​​in the reaction state supervision processing sequence are all 0, an overall normal reaction instruction is generated without any prompt; If there are non-zero elements in the reaction state supervision processing sequence, the total number of non-zero elements Ny is counted and the abnormal impact formula is used Calculate and obtain the abnormal impact index Yy corresponding to all abnormal elements; where e is a natural constant; N is the total number of all elements in the reaction state supervision processing sequence; α is the abnormal impact standard value; Data analysis of the abnormal impact index is performed to dynamically manage the operation and maintenance of the vehicle's onboard computers.

2. The vehicle fault monitoring system based on artificial intelligence according to claim 1 is characterized in that: When monitoring and counting the reaction of the vehicle computer after each click, a click supervision signal is generated when the user clicks the vehicle computer, and a click timestamp corresponding to the click supervision signal is obtained; And, monitoring and counting the reaction of the vehicle computer after being clicked, if the vehicle computer reacts, generating a reaction implementation signal, and obtaining a reaction timestamp corresponding to the reaction implementation signal; Calculate the reaction time difference Tf between the reaction timestamp and the click timestamp, and obtain the reaction state index Fz corresponding to the vehicle computer being clicked by the formula Fz=[Tf / Tf0]; where Tf0 is the standard reaction time difference corresponding to the vehicle computer; [] is the rounding function.

3. The vehicle fault monitoring system based on artificial intelligence according to claim 2 is characterized in that: When the reaction state index is analyzed to determine the reaction state corresponding to the click reaction, if the reaction state index is 0, a normal reaction instruction is generated and a prompt indicating a normal reaction is given; If the reaction state index is not 0, a reaction abnormality instruction is generated and a reaction abnormality prompt is given; If the vehicle computer does not respond, a response loss signal is generated, and all response loss verification indicators YBi,i={1, 2, 3, ..., n} corresponding to the vehicle computer are obtained according to the response loss signal monitoring, where n is a positive integer; All acquired reaction loss verification indicators are analyzed through the indicator state recognition function, and the indicator state values ​​ZZi corresponding to different reaction loss verification indicators are output; The indicator status value includes a value of 0 or 1, indicating whether the indicator status of the corresponding response loss verification indicator is normal or abnormal; All indicator status values ​​obtained from the processing of the response loss verification indicators are sorted and combined to obtain the corresponding indicator status processing sequence.

4. The vehicle fault monitoring system based on artificial intelligence according to claim 3 is characterized in that: The expression of the indicator state identification function is Where Ui is the standard range of verification indicators corresponding to different reaction loss verification indicators.

5. The vehicle fault monitoring system based on artificial intelligence according to claim 3 is characterized in that: Perform data analysis on the indicator status processing sequence to determine the rescue implementation status corresponding to the vehicle computer response loss of connection; Conduct traversal analysis on the indicator status processing sequence; If the element values ​​in the indicator status processing sequence are all 0, an active processing instruction is generated, and the system version number corresponding to the vehicle computer is obtained according to the active processing instruction, and the obtained system version number is traversed and matched with the pre-built version requirement database.

6. The vehicle fault monitoring system based on artificial intelligence according to claim 5 is characterized in that: If the version requirement database contains a sample system version number that is consistent with the obtained system version number, then necessary instructions for implementing the rescue are generated and a prompt is given to implement the rescue implementation plan, and at the same time, the reaction state index corresponding to the click reaction is set to -1; If there is no sample system version number consistent with the obtained system version number in the version requirement database, a system update instruction is generated and the system version of the vehicle computer is autonomously controlled to be updated to the system version corresponding to the oldest sample system version number in the version requirement database, and the updated vehicle computer status is retroactively evaluated.

7. The vehicle fault monitoring system based on artificial intelligence according to claim 6 is characterized in that: If the updated vehicle computer status responds normally, an active processing valid instruction is generated and the total number of active processing valid times is increased by one; If the vehicle computer status response after the update is still abnormal, an active processing invalid instruction is generated and the total number of active processing invalid times is increased by one.

8. The vehicle fault monitoring system based on artificial intelligence according to claim 5 is characterized in that: If the value of an element in the indicator status processing sequence is 1, a rescue delay instruction is generated, and the reaction loss verification indicator corresponding to the element with a value of 1 is obtained and marked as an abnormal indicator. At the same time, the corresponding abnormal processing plan is implemented for the abnormal indicator, and the reaction state index corresponding to the click reaction is set to -2; The reaction state indexes obtained by the supervision corresponding to different click reactions of the vehicle computer are arranged and combined in the time sequence of the click timestamps to obtain the reaction state supervision processing sequence corresponding to all click reaction supervisions of the vehicle computer.

9. The vehicle fault monitoring system based on artificial intelligence according to claim 1, characterized in that: If the abnormal impact index is less than 1, a second operation and maintenance signal is generated and the existing operation and maintenance cycle of the vehicle computer is shortened; If the abnormal impact index is greater than 1, a first operation and maintenance signal is generated and the user is prompted to immediately perform operation and maintenance management on the vehicle computer.

10. A vehicle fault monitoring method based on artificial intelligence, using a vehicle fault monitoring system based on artificial intelligence as claimed in any one of claims 1 to 9, characterized in that: include: Monitor and identify the real-time click response status of the vehicle computer, and actively perform abnormal processing analysis and digital processing of the abnormal operating status obtained through monitoring and identification in different dimensions, obtain the corresponding click supervision results and upload them to the vehicle fault supervision platform in real time; According to the reaction status supervision processing sequence corresponding to all click reaction supervisions of the vehicle computer, the vehicle computer abnormality impact analysis is implemented, and the vehicle computer is adaptively implemented with targeted operation and maintenance management based on the analysis results.

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