Automobile CAN bus message analysis method and system based on similarity principle

Abstract

The invention relates to the technical field of vehicle CAN buses, in particular to a vehicle CAN bus message analysis method and system based on the similarity principle. Comprising the following steps: carrying out characteristic analysis on a vehicle signal, setting a characteristic working condition, respectively collecting physical information and CAN bus information of a vehicle under the characteristic working condition through a vehicle OBD interface, carrying out data processing on the two groups of information to obtain two groups of corresponding variables, calculating Pearson correlation of the two groups of variables, and calculating the Pearson correlation of the two groups of variables; calculating an analysis rule of the signal of which the correlation is greater than a correlation threshold value, writing an analysis file, importing the analysis file into data acquisition software, and comparing vehicle physical information with analyzed CAN bus information in real time; if yes, the message information analysis is correct; and if not, adjusting the analysis rule according to the inconsistency type. By means of the mode, the automobile CAN bus message can be interpreted and analyzed under the condition that the automobile is not damaged, and more automobile information can be obtained from the automobile CAN bus.

Description

Technical Field

[0001] The invention relates to the technical field of vehicle CAN bus, and in particular to a vehicle CAN bus message analysis method and system based on a similarity principle. Background Art

[0002] Controller Area Network (CAN or CAN bus) is a serial communication protocol bus for real-time applications. It can use twisted pair cables to transmit signals and is one of the most widely used field buses in the world. In automobiles, the CAN bus is used to connect various electronic control units (ECUs) to achieve the following functions: data transmission and sharing, real-time monitoring and diagnosis, reduced wiring and costs, and improved safety. CAN bus signal analysis refers to the analysis and interpretation of data transmitted by the CAN bus to obtain the information contained therein. In the CAN bus, data is transmitted in the form of frames, and each frame contains an identifier, a data field, a control field, and a check field. The identifier is used to identify the sending node and the receiving node, and the data field contains the actual transmitted data.

[0003] When analyzing the automobile CAN bus message, due to the rapid development of today's automobile industry, under the requirements of more and more functional aspects, the information contained in the vehicle CAN bus system is also gradually increasing. CAN2.0A and CAN2.0B have appeared one after another, and the amount of data that can be stored in the message has also increased from a maximum of 8 bytes in the standard CAN to a maximum of 64 bytes in CANFD. The difficulty of analyzing the automobile CAN bus message is also gradually increasing. In addition, due to the increasingly complex structure of vehicles, when obtaining vehicle information, we should also try our best to ensure that no damage is caused to the vehicle. Therefore, it is particularly important to develop a method for analyzing the automobile CAN bus message information without causing damage to the vehicle. Summary of the invention

[0004] In view of the above problems existing in the prior art, the present invention is proposed.

[0005] The main technical problem solved by the present invention is to provide a vehicle CAN bus message analysis method based on the similarity principle, which can interpret and analyze the vehicle CAN bus message without causing damage to the vehicle to obtain more vehicle information from the vehicle CAN bus.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a method for analyzing automobile CAN bus messages based on the similarity principle, comprising: analyzing vehicle signal characteristics and designing characteristic working conditions; synchronously collecting automobile physical information and CAN bus information, processing the collected information, calculating the Pearson correlation, and judging whether the correlation is greater than a relevant threshold; if it is greater than the relevant threshold, determining the analysis rules, writing an analysis file, importing the analysis file into a data acquisition software, comparing the vehicle physical information with the analyzed CAN bus information in real time, and judging whether the information is consistent.

[0007] As a preferred solution of the automobile CAN bus message analysis method based on the similarity principle described in the present invention, the synchronous collection of automobile physical information and CAN bus information includes: the collection time is determined according to the signal change speed, and the time axis is aligned when the two sets of information are processed; if the collection time is less than 1 minute, the sampling interval is 1 second; if the collection time is greater than 1 minute, the sampling interval is increased according to the length of the sampling time.

[0008] As a preferred solution of the automobile CAN bus message analysis method based on the similarity principle described in the present invention, wherein: the calculation of the Pearson correlation is expressed as,

[0009]

[0010] Among them, X represents the reference variable, Y represents the signal variable, n represents the recording time, r represents the correlation between X and Y, and i represents the indicator variable. is expressed as the mean value of the reference variable, Expressed as the mean value of the signal variable.

[0011] As a preferred solution of the automobile CAN bus message analysis method based on the similarity principle described in the present invention, the judgment of whether the correlation is greater than the correlation threshold includes: if the CAN bus signal correlation r is less than or equal to the correlation threshold r0, it is an unrelated signal and no verification is required; if the CAN bus signal correlation r is greater than the correlation threshold r0, it is a related signal and the next step of verification is performed, r0=0.9.

[0012] As a preferred solution of the automobile CAN bus message analysis method based on the similarity principle described in the present invention, wherein: the analysis rules include signal length, signal type, signal starting position, coefficient and offset;

[0013] The coefficient and offset are expressed as: physical value = signal value × coefficient + offset.

[0014] As a preferred solution of the automobile CAN bus message analysis method based on the similarity principle described in the present invention, the determination of whether the information is consistent includes importing the analysis rules into the data acquisition software, comparing the vehicle physical information with the analyzed CAN bus information, and when the physical signal analyzed by the vehicle remains stable, if the vehicle physical information is consistent with the analyzed CAN bus information, then operating the vehicle to change the physical information value, and if the vehicle physical information remains stable again, the vehicle physical information is consistent with the analyzed CAN bus information, then it is determined that the two information are consistent; if the information is inconsistent at any time, then it is determined that the two information are inconsistent.

[0015] As a preferred solution of the automobile CAN bus message analysis method based on the similarity principle described in the present invention, the judgment that the two information are inconsistent includes: when the vehicle physical information is inconsistent with the analyzed CAN bus information, if the two information values ​​change synchronously but the values ​​are different, it is an error in the calculation of the coefficient and offset information, and two sets of data are re-selected from the physical information acquisition device and the data acquisition software in real time, and the coefficients and offsets are calculated until the two information are consistent; if the two information values ​​are consistent within a certain range, and the information values ​​are inconsistent when exceeding a certain range, it is an error in the signal length, and the length of 1 bit is increased or decreased in turn, and the comparison and verification are performed again until the two information are consistent and the message analysis is completed.

[0016] Another object of the present invention is to provide an automobile CAN bus message analysis system based on the similarity principle. The system ensures the real-time and accuracy of CAN bus message analysis by accurately analyzing vehicle signal characteristics and designing characteristic working conditions, combined with the mechanism of synchronous acquisition and processing, so as to quickly identify changes in vehicle status and provide a reliable basis for fault diagnosis. Using Pearson correlation calculation, the system quantifies the relationship between vehicle physical information and CAN bus information, and automatically determines the correlation through a preset threshold, reducing human misjudgment, achieving a high degree of automation of the analysis process, and improving the overall reliability and efficiency of the system. The automated process and real-time comparison function can timely discover and report the inconsistencies between vehicle physical information and CAN bus information, providing strong support for vehicle fault detection and maintenance, and significantly improving the efficiency of vehicle maintenance. The system based on modular design is easy to expand and upgrade, has strong adaptability, can meet the needs of different models and complex analysis scenarios, and provides good adaptability for future technological progress and market demand.

[0017] As a preferred solution of the automobile CAN bus message analysis system based on the similarity principle described in the present invention, it includes: an analysis module, a calculation module, and a judgment module;

[0018] The analysis module analyzes vehicle signal characteristics and designs characteristic operating conditions;

[0019] The calculation module synchronously collects vehicle physical information and CAN bus information, processes the collected information, calculates the Pearson correlation, and determines whether the correlation is greater than a correlation threshold;

[0020] If the value is greater than the relevant threshold, the judgment module determines the analysis rules, writes the analysis file, imports the analysis file into the data acquisition software, compares the vehicle physical information with the analyzed CAN bus information in real time, and determines whether the information is consistent.

[0021] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of any one of the methods for analyzing automobile CAN bus messages based on the similarity principle are implemented.

[0022] A computer-readable storage medium stores a computer program thereon, characterized in that when the computer program is executed by a processor, the steps of any one of the methods for analyzing automobile CAN bus messages based on the similarity principle are implemented.

[0023] Beneficial effects of the present invention: The present invention can interpret and analyze automobile CAN bus messages without causing damage to the vehicle to obtain more vehicle information from the automobile CAN bus. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0025] Figure 1 A schematic diagram of an automobile CAN bus message analysis method based on the similarity principle provided by an embodiment of the present invention.

[0026] Figure 2 A schematic diagram of data acquisition equipment connection and technical flow of an automobile CAN bus message analysis method based on the similarity principle provided in one embodiment of the present invention.

[0027] Figure 3 A signal matrix schematic diagram of a rule file for writing an automobile CAN bus message analysis method based on the similarity principle provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0029] Example 1

[0030] Reference Figure 1-Figure 3 , which is the first embodiment of the present invention, provides a method for analyzing automobile CAN bus messages based on the similarity principle, comprising:

[0031] like Figure 1 As shown, the vehicle signal is characteristically analyzed, and characteristic working conditions are set. The physical information and CAN bus information of the vehicle under the characteristic working conditions are collected through the vehicle OBD interface respectively. The two sets of information are processed to obtain two sets of corresponding variables, and the Pearson correlation of the two sets of variables is calculated. The signal calculation and analysis rules with correlation greater than the correlation threshold are taken, and the analysis file is written and imported into the data acquisition software to compare the vehicle physical information with the analyzed CAN bus information in real time; if they are consistent, the message information analysis is correct; if they are inconsistent, the analysis rules are adjusted according to the inconsistency type. The method can be applied to fuel vehicles, new energy vehicles and other types of vehicles with OBD diagnostic interfaces. The characteristic working conditions of vehicle signals are customized according to the signal characteristics. The value of the vehicle signal to be analyzed under the characteristic working conditions will change, and it has a certain regularity and recognition compared with other vehicle signals.

[0032] Perform feature analysis on vehicle signals and set feature working conditions. As long as the collected signals are recognizable and regular, it will be fine. For example, if you want to analyze vehicle speed signals, you can design a vehicle speed that increases from zero and then decreases, so that the vehicle speed signal has a regular change process.

[0033] Figure 2 The figure shows a data acquisition device connection and technical flow diagram of a preferred embodiment of the automobile CAN bus message analysis method based on the similarity principle of the present invention, wherein the solid line portion is a data acquisition device connection diagram of this embodiment, and the dotted line portion is a technical flow diagram of the analysis method of this embodiment.

[0034] Step 1: Analyze the required vehicle signal characteristics, and customize the characteristic working conditions of the vehicle signal according to the signal characteristics. The following conditions should be met: the vehicle signal value under the characteristic working conditions will undergo certain changes, and compared with other vehicle signals, it has certain regularity and recognition. This embodiment takes the analysis of a certain vehicle accelerator pedal depth signal Accpedal as an example. The range of the vehicle accelerator pedal depth signal Accpedal is [0%, 100%], and the characteristic working conditions are set as follows: the vehicle is stationary and put into P gear, and the accelerator pedal is slowly pressed until it is fully pressed and then slowly released.

[0035] Step 2: Connect the physical information acquisition device and the CAN bus information acquisition device to the vehicle through the vehicle OBD interface to synchronously acquire the vehicle physical information and CAN bus information. In this embodiment, a certain automobile diagnostic instrument is used as the physical information acquisition device, and Vector's CAN bus information device VN1640A is used as the bus information acquisition device to synchronously acquire the vehicle physical information and CAN bus information. The acquisition time is 20 seconds.

[0036] Step 3: Process the collected physical information and CAN bus information separately, align the time axes of the two sets of information, if the collection time is less than 1 minute, the sampling interval is 1 second; if the collection time is greater than 1 minute, increase the sampling interval according to the length of the sampling time; after the CAN bus information is processed, the message information is segmented and reorganized according to different signal lengths and byte orders, the processed physical information is used as the reference variable X for calculating the Pearson correlation, and the processed CAN bus information is used as the signal variable Y for calculating the Pearson correlation. The Pearson correlation of the two sets of variables is calculated using the calculation formula:

[0037]

[0038] The two variables mentioned in the present invention: the reference variable and the signal variable, if matched, the relationship between the two should be linearly correlated, that is, the relationship of y=ax+b. The Pearson correlation is a statistical indicator used to measure the strength and direction of the linear relationship between two variables. The size of its value reflects the size of the correlation between the signal variable and the reference variable. Therefore, the closer the calculated value is to 1, the more likely it is that the signal is the signal to be found. The problem to be solved is that the amount of data on the CAN bus is extremely large and is expressed in hexadecimal. It is difficult to determine the signal position directly by observation, so such an indicator is used for judgment.

[0039] Wherein, X is the reference variable, Y is the signal variable, n is the recording time, r is the Pearson correlation between the variable X and the variable Y, the range is [-1, 1], the correlation threshold r0 = 0.9, if the signal similarity r> correlation threshold r0, it is a correlated signal, and the next step of verification is performed; if the signal similarity r≤ correlation threshold r0, it is an uncorrelated signal, and no verification is required; in this embodiment, matlab software is used for data processing and calculation of Pearson correlation, the sampling interval is 1 second, and the physical information after data processing, i.e., the reference variable X, is shown in the following table:

[0040] Time(s) 1 2 3 4 5 6 7 8 9 10 Physical value (%) 0 7.1 11.4 17 20.4 27.7 36.6 53.6 72.1 87.8 Time(s) 11 12 13 14 15 16 17 18 19 20 Physical value (%) 100 100 64.2 47.8 34.8 22.1 15.5 4.2 0 0

[0041] The calculation shows that the signal similarity r=0.935>r0=0.9 composed of the 5th and 6th bytes of the ID 7EB in the CAN bus information is related. The signal is verified in the next step. The signal information after data processing, i.e., variable Y, is shown in the following table:

[0042] Time(s) 1 2 3 4 5 6 7 8 9 10 Signal value 0 0 114 125 170 204 277 536 611 721 Time(s) 11 12 13 14 15 16 17 18 19 20 Signal value 878 1000 1000 642 478 348 221 155 42 0

[0043] It should be noted that the signal values ​​described in the table are the decimal values ​​converted after the 5th byte and the 6th byte signal values ​​are reorganized.

[0044] Step 4: Determine the signal analysis rules based on the vehicle signal characteristics, analysis experience and the signal information to be verified. The specific determination method is as follows: signal length: signal length = number of bytes × 8, for example, the single-byte signal length is 8 bits, and the double-byte signal length is 16 bits; signal type: Motorola with high byte at the end, Intel with high byte at the front; signal starting position: Motorola type signal starting position is the low bit of the high byte, Intel type signal starting position is the low bit of the low byte. Coefficient and offset: Take any two sets of data from the reference variable and signal variable, and calculate their coefficients and offsets according to the following formula: physical value = signal value × coefficient + offset; write a signal analysis file according to the above rules.

[0045] Figure 3The figure shows a schematic diagram of a signal matrix for writing analysis rules of the present invention. In this embodiment, the CANdb++Editor tool of the CANoe software is used to write an analysis file. It is calculated that the signal with a similarity greater than the correlation threshold r0 is composed of the 5th and 6th bytes of the ID 7EB in the CAN bus information. The signal consists of 2 bytes and the signal length is 2×8=16 bits. The high byte of the signal is the 6th byte at the end, so it is in Motorola format, and the starting position of the signal is the low bit of the high byte, that is, 40. Take two groups of reference data: 11.4, 53.6, and the corresponding signal data are: 114, 536. The coefficient is calculated to be 0.1, the offset is 0, the msb low byte, and ACCpedal is the signal name.

[0046] Step 5, import the signal analysis file written in step 4 into the data acquisition software, you can view the CAN bus information after the analysis file is interpreted in real time, compare the vehicle physical information with the analyzed CAN bus information, when the analyzed physical signal remains stable, if the vehicle physical information is consistent with the analyzed CAN bus information, then operate the vehicle to change the physical information value to ensure that its physical information value has a certain range of variation, if the vehicle physical information remains stable again, the vehicle physical information and the analyzed CAN bus information are consistent, then it is determined that the two information are consistent, and the message analysis is completed; in this embodiment, CANoe software is used to load the analysis file, and the vehicle physical information and the analyzed CAN bus information are viewed and compared in real time. After comparison and verification, each time the vehicle accelerator pedal depth remains stable, the vehicle physical information is consistent with the analyzed CAN bus information, so the signal is the vehicle accelerator pedal depth signal, and the message analysis is completed; if any of the above information is inconsistent, it is determined that the two information are inconsistent, and the next step is performed.

[0047] It has a certain range of variation. Different signals have different ranges, and the specific range of the signal is unknown when performing CAN bus analysis. For example, the vehicle speed signal is assumed to have a range of [-100,200]. As long as it is consistent in any range such as [0,60], [20,50]..., and inconsistent outside this range, it belongs to this situation.

[0048] Step six, when the vehicle physical information is inconsistent with the analyzed CAN bus information, if the two information values ​​change synchronously but the values ​​are different, it is an error in the calculation of the coefficient and offset information. Reselect two sets of data from the physical information acquisition device and the data acquisition software in real time, and calculate their coefficients and offsets until the two information are consistent; if the two information values ​​are consistent within a certain range, and the information values ​​are inconsistent when they exceed a certain range, it is an error in the signal length. Try to increase or decrease the length by 1 bit in turn, and compare and verify again until the two information are consistent and the message analysis is completed.

[0049] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. 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 solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0050] Example 2

[0051] The second embodiment of the present invention is different from the previous embodiment in that:

[0052] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0053] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0054] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0055] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0056] Example 3

[0057] The third embodiment of the present invention provides an automobile CAN bus message analysis system based on the similarity principle, which is characterized by comprising an analysis module, a calculation module, and a judgment module;

[0058] The analysis module analyzes vehicle signal characteristics and designs characteristic operating conditions;

[0059] The calculation module synchronously collects vehicle physical information and CAN bus information, processes the collected information, calculates the Pearson correlation, and determines whether the correlation is greater than a correlation threshold;

[0060] If the value is greater than the relevant threshold, the judgment module determines the analysis rules, writes the analysis file, imports the analysis file into the data acquisition software, compares the vehicle physical information with the analyzed CAN bus information in real time, and determines whether the information is consistent.

[0061] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. 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 solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for analyzing automobile CAN bus messages based on the similarity principle, characterized in that: include, Analyze vehicle signal characteristics and design characteristic working conditions; Synchronously collect vehicle physical information and CAN bus information, process the collected information, calculate the Pearson correlation, and determine whether the correlation is greater than the correlation threshold; If it is greater than the relevant threshold, the analysis rules are determined, the analysis file is written, the analysis file is imported into the data acquisition software, the vehicle physical information is compared with the analyzed CAN bus information in real time, and it is determined whether the information is consistent.

2. The automobile CAN bus message analysis method based on the similarity principle as claimed in claim 1 is characterized in that: The synchronous collection of automobile physical information and CAN bus information includes: determining the collection time according to the signal change speed, and aligning the time axis when processing the two sets of information; If the acquisition time is less than 1 minute, the sampling interval is 1 second; If the collection time is longer than 1 minute, increase the sampling interval according to the length of the sampling time.

3. The automobile CAN bus message analysis method based on the similarity principle as claimed in claim 2 is characterized in that: The calculated Pearson correlation is expressed as, Among them, X represents the reference variable, Y represents the signal variable, n represents the recording time, r represents the correlation between X and Y, and i represents the indicator variable. is expressed as the mean value of the reference variable, Expressed as the mean value of the signal variable.

4. The automobile CAN bus message analysis method based on the similarity principle as claimed in claim 3 is characterized in that: The determination of whether the correlation is greater than the correlation threshold includes: if the CAN bus signal correlation r is less than or equal to the correlation threshold r0, it is an uncorrelated signal and no verification is required; if the CAN bus signal correlation r is greater than the correlation threshold r0, it is a correlated signal and verification is performed according to the analysis rule, r0=0.

9.

5. The automobile CAN bus message analysis method based on the similarity principle as claimed in claim 4 is characterized in that: The analysis rules include signal length, signal type, signal starting position, coefficient and offset; The signal length is expressed as, D=B×8 Among them, B represents the number of bytes, and D represents the signal length; The signal type includes: Motorola with high byte at the end, and Intel with high byte at the beginning; the signal starting position includes: the starting position of Motorola type signal is the low bit of high byte, and the starting position of Intel type signal is the low bit of low byte; the coefficient and offset are randomly selected from two groups of numbers of reference variable and signal variable, and the calculated coefficient and offset are expressed as, P value =S value ×Factor+Offset Among them, P value Expressed as a physical value, S value It is expressed as signal value, Factor is expressed as coefficient, and Offset is expressed as offset.

6. The automobile CAN bus message analysis method based on the similarity principle as claimed in claim 5 is characterized in that: The determination of whether the information is consistent includes importing the analysis rules into the data acquisition software, comparing the physical information of the vehicle with the analyzed CAN bus information, and when the physical signal analyzed by the vehicle remains stable, if the physical information of the vehicle is consistent with the analyzed CAN bus information, operating the vehicle to change the physical information value, and if the physical information of the vehicle remains stable again, the physical information of the vehicle is consistent with the analyzed CAN bus information, then determining that the two information are consistent; if the information is inconsistent at any time, determining that the two information are inconsistent.

7. The automobile CAN bus message analysis method based on the similarity principle as claimed in claim 6 is characterized in that: The judgment that the two information are inconsistent includes: when the vehicle physical information is inconsistent with the analyzed CAN bus information, if the two information values ​​change synchronously but the values ​​are different, it is a calculation error of the coefficient and offset information, and two sets of data are re-selected from the physical information acquisition device and the data acquisition software in real time, and the coefficients and offsets are calculated until the two information are consistent; if the two information values ​​are consistent within a certain range, and the information values ​​are inconsistent when they exceed the preset range, it is a signal length error, and the length is increased or decreased by 1 bit in turn, and comparison and verification are performed again until the two information are consistent and the message analysis is completed.

8. A system based on the automobile CAN bus message analysis method based on the similarity principle according to any one of claims 1 to 7, characterized in that: Including, analysis module, calculation module, judgment module; The analysis module analyzes vehicle signal characteristics and designs characteristic operating conditions; The calculation module synchronously collects vehicle physical information and CAN bus information, processes the collected information, calculates the Pearson correlation, and determines whether the correlation is greater than a correlation threshold; If the value is greater than the relevant threshold, the judgment module determines the analysis rules, writes the analysis file, imports the analysis file into the data acquisition software, compares the vehicle physical information with the analyzed CAN bus information in real time, and determines whether the information is consistent.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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