Vehicle fault diagnosis method and device, electronic equipment and storage medium

Abstract

The invention provides a vehicle fault diagnosis method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining first message data of a vehicle; obtaining a database file and a fault information table of the vehicle; analyzing the first message data according to the database file to obtain second message data; obtaining a fault signal value in the second message data; and querying the fault information table according to the fault signal numerical value to obtain diagnosis information. According to the vehicle fault diagnosis method and device, the efficiency and flexibility of vehicle fault diagnosis can be improved, fault diagnosis in an off-line state is supported, professional requirements for operators are avoided, the diagnosis mode is simpler and more effective, and reliable help can be provided for vehicle development.

Description

Technical Field

[0001] The present application relates to the field of vehicle diagnosis technology, and in particular to a vehicle fault diagnosis method, device, electronic device and storage medium. Background Art

[0002] Vehicle diagnosis refers to the method of detecting, analyzing and judging the vehicle through a series of technical means to locate the source and cause of the fault. There are many common vehicle fault diagnosis methods.

[0003] However, the existing vehicle fault diagnosis method has many disadvantages. For example, fault reading can only be performed when connected to the Electronic Control Unit (ECU), and offline data cannot be processed; if a new model needs to be diagnosed, the diagnostic instrument needs to be redeveloped, which has a long development cycle and insufficient flexibility; all faults cannot be read; there are certain requirements for communication between the vehicle and the monitoring system, which is not suitable for non-professionals to diagnose a single vehicle; the number of remote monitoring signals is limited, and the cause of the fault cannot be analyzed for fault data that has not been uploaded. Summary of the invention

[0004] The purpose of this application is to provide a vehicle fault diagnosis method, device, electronic device and storage medium, which can improve the efficiency and flexibility of vehicle fault diagnosis, and support fault diagnosis in an offline state. There is no professional requirement for operators. The diagnosis method is simpler and more effective, and can provide reliability assistance for vehicle development.

[0005] In a first aspect, an embodiment of the present application provides a vehicle fault diagnosis method, the method comprising:

[0006] Obtaining first message data of the vehicle;

[0007] Obtaining a database file and a fault information table of the vehicle;

[0008] Parsing the first message data according to the database file to obtain second message data;

[0009] Obtaining a fault signal value in the second message data;

[0010] The fault information table is queried according to the fault signal value to obtain diagnostic information.

[0011] In the above implementation process, the first message data is parsed according to the database file to obtain the fault signal value, and then the fault signal value is queried, which can improve the efficiency and flexibility of vehicle fault diagnosis, and support fault diagnosis in an offline state. There is no professional requirement for operators, and the diagnosis method is simpler and more effective, which can provide reliability assistance for vehicle development.

[0012] Furthermore, the step of obtaining the database file and the fault information table of the vehicle includes:

[0013] Get the model project name of the vehicle;

[0014] Get the file path corresponding to the vehicle model project name;

[0015] The database file and the fault information table corresponding to the file path are extracted.

[0016] In the above implementation process, the corresponding file path can be accurately located according to the vehicle model project name, and then the database file and fault information table corresponding to the file path are obtained, which can improve the accuracy of fault location and reduce the location error.

[0017] Furthermore, the step of parsing the first message data according to the database file to obtain the second message data includes:

[0018] Processing the database file according to the first function to obtain a message period of the fault signal;

[0019] Extracting the message data containing the fault signal from the first message data according to the message period of the fault signal to obtain third message data;

[0020] Filter according to the third message data to obtain the second message data.

[0021] In the above implementation process, the database file is processed to obtain the message period of the fault signal. According to the message period of the fault signal, the message data containing the fault signal can be extracted, and the message data can be accurately distinguished, thereby improving the efficiency of fault diagnosis and facilitating timely diagnosis of faults.

[0022] Further, the step of filtering according to the third message data to obtain the second message data includes:

[0023] Extracting the message length corresponding to each message frame in the third message data;

[0024] Determine whether the message length meets the length threshold;

[0025] If not, it is determined that the message frame is an error frame;

[0026] If so, determine that the message frame is a normal frame;

[0027] Filter the error frames in the third message data to obtain the second message data.

[0028] In the above implementation process, the error frames and normal frames in the message frames are distinguished according to the message length of the message frames, and the error frames are filtered at the same time to obtain the second message data containing only normal frames. This can improve the processing speed of the second message data, reduce the error of the second message, and provide data support for subsequent fault diagnosis.

[0029] Furthermore, the step of obtaining the fault signal value in the second message data includes:

[0030] Parsing the second message data according to a second function to obtain signal data;

[0031] Traversing the signal data to obtain a signal value and a signal name of a fault signal;

[0032] The signal value is analyzed to obtain the fault signal value.

[0033] In the above implementation process, the second message data is parsed to obtain signal data, and then the signal data is processed, which can enhance the processing capability of the message data, refine the diagnosis of the fault, and improve the accuracy of the fault diagnosis.

[0034] Furthermore, the step of parsing the signal value to obtain the fault signal value includes:

[0035] Performing down-conversion on the signal value according to a third function to obtain a converted signal value;

[0036] Removing prefix information of the converted signal value to obtain a signal value without the prefix information;

[0037] The signal value without the prefix information is traversed to obtain the fault signal value.

[0038] In the above implementation process, the signal value is successively converted into a down-signal value and the prefix information is removed to obtain the fault signal value, which can improve the accuracy of the fault signal value and reduce the error caused by the signal value during the fault diagnosis process.

[0039] Furthermore, the step of querying the fault information table according to the fault signal value to obtain diagnostic information includes:

[0040] Extracting byte information of the fault signal value;

[0041] According to the byte information, the corresponding fault information in the fault information table is queried to obtain the diagnosis information.

[0042] In the above implementation process, by searching the corresponding fault information in the fault information table according to the byte information of the fault signal value, the specific type and location of the fault can be clarified, the fault can be accurately diagnosed, and the diagnostic information can be obtained.

[0043] In a second aspect, an embodiment of the present application further provides a vehicle fault diagnosis device, the device comprising:

[0044] An acquisition module, used for acquiring first message data of a vehicle;

[0045] A data acquisition module, used to obtain the database file and fault information table of the vehicle; and also used to obtain the fault signal value in the second message data;

[0046] A parsing module, used for parsing the first message data according to the database file to obtain second message data;

[0047] The query module is used to query the fault information table according to the fault signal value to obtain diagnostic information.

[0048] In the above implementation process, the first message data is parsed according to the database file to obtain the fault signal value, and then the fault signal value is queried, which can improve the efficiency and flexibility of vehicle fault diagnosis, and support fault diagnosis in an offline state. There is no professional requirement for operators, and the diagnosis method is simpler and more effective, which can provide reliability assistance for vehicle development.

[0049] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in any one of the first aspects when executing the computer program.

[0050] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which instructions are stored. When the instructions are executed on a computer, the computer executes the method as described in any one of the first aspects.

[0051] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when running on a computer, enables the computer to execute the method as described in any one of the first aspects.

[0052] Other features and advantages of the present disclosure will be set forth in the following description, or some features and advantages may be inferred or unambiguously determined from the description, or may be learned by implementing the above-mentioned technology of the present disclosure.

[0053] And it can be implemented according to the contents of the specification. The following is a detailed description of the preferred embodiments of the present application with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the range values. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0055] Figure 1 A schematic diagram of a flow chart of a vehicle fault diagnosis method provided in an embodiment of the present application;

[0056] Figure 2 A schematic diagram of the structure of a vehicle fault diagnosis device provided in an embodiment of the present application;

[0057] Figure 3 A schematic diagram of the structural composition of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0059] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0060] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application, but are not used to limit the scope of the present application.

[0061] Embodiment 1

[0062] Figure 1 is a flow chart of a vehicle fault diagnosis method provided by an embodiment of the present application, such as Figure 1 As shown, the method includes:

[0063] S1, obtaining the first message data of the vehicle;

[0064] S2, obtaining the database file and fault information table of the vehicle;

[0065] S3, parsing the first message data according to the database file to obtain second message data;

[0066] S4, obtaining a fault signal value in the second message data;

[0067] S5, querying the fault information table according to the fault signal value to obtain diagnostic information.

[0068] In the above implementation process, the first message data is parsed according to the database file to obtain the fault signal value, and then the fault signal value is queried, which can improve the efficiency and flexibility of vehicle fault diagnosis, and support fault diagnosis in an offline state. There is no professional requirement for operators, and the diagnosis method is simpler and more effective, which can provide reliability assistance for vehicle development.

[0069] The embodiment of the present application is implemented based on Python and runs on a terminal. It can obtain online message data of each system of the vehicle through a controller area network (CAN) device, and can also perform fault diagnosis on existing offline message data.

[0070] In S1, the embodiment of the present application collects the vehicle message (first message data) through the CANoe device, and uses the can.interface.Bus() method in Python to configure the interface. The configuration information includes interface, channel, bitrate, and CAN / CANFD, etc. After the interface configuration is completed, the vehicle message is received through can.interface.Bus().recv().

[0071] In S2, the embodiment of the present application reads the path of the stored database file and fault information table through an Excel table, and the Excel table records all vehicle model items and their corresponding database files and fault information table paths. The pandas.read_excel() method in python is used to read all vehicle model item names in Excel. When the user selects the corresponding item, the corresponding database file and fault information table are obtained according to the relative position relationship of the cells.

[0072] For newly added vehicle model items, users only need to update the Excel table, which will be traversed each time it is opened to obtain the required files. Therefore, when the vehicle model item changes, there is no need to redo the fault diagnosis.

[0073] Furthermore, S2 includes:

[0074] Get the model project name of the vehicle;

[0075] Get the file path corresponding to the vehicle model project name;

[0076] Extract the database file and fault information table corresponding to the file path.

[0077] In the above implementation process, the corresponding file path can be accurately located according to the vehicle model project name, and then the database file and fault information table corresponding to the file path are obtained, which can improve the accuracy of fault location and reduce the location error.

[0078] Furthermore, S3 includes:

[0079] Processing the database file according to the first function to obtain the message period of the fault signal;

[0080] Extracting the message data containing the fault signal from the first message data according to the message period of the fault signal to obtain third message data;

[0081] Filter according to the third message data to obtain the second message data.

[0082] In the above implementation process, the database file is processed to obtain the message period of the fault signal. According to the message period of the fault signal, the message data containing the fault signal can be extracted, and the message data can be accurately distinguished, thereby improving the efficiency of fault diagnosis and facilitating timely diagnosis of faults.

[0083] The embodiment of the present application parses the first message data through a database file to obtain data such as the ID, signal name, and signal value of the fault signal of each system.

[0084] Since the size of the message data directly affects the diagnosis speed, the shorter the message collection time, the faster the diagnosis speed. The embodiment of the present application uses the first function cantools.db.load_file() to process the database file to obtain the message period of all fault signals. Based on the principle that all fault signals are collected and the data volume is as small as possible, the maximum period of the message data is the message collection time.

[0085] Further, the step of filtering according to the third message data to obtain the second message data includes:

[0086] Extracting the message length corresponding to each message frame in the third message data;

[0087] Determine whether the message length meets the length threshold;

[0088] If not, it is determined that the message frame is an error frame;

[0089] If so, determine that the message frame is a normal frame;

[0090] Filter the error frames in the third message data to obtain the second message data.

[0091] In the above implementation process, the error frames and normal frames in the message frames are distinguished according to the message length of the message frames, and the error frames are filtered at the same time to obtain the second message data containing only normal frames. This can improve the processing speed of the second message data, reduce the error of the second message, and provide data support for subsequent fault diagnosis.

[0092] Considering that there may be error frames in the third message data, since the message length of the error frame is generally different from that of the normal frame, the error frame can be filtered out according to the message length. Alternatively, other attributes can also be used to filter out the error frame to prevent problems after the program is run.

[0093] Furthermore, S4 includes:

[0094] Parsing the second message data according to the second function to obtain signal data;

[0095] Traverse the signal data to obtain the signal value and signal name of the fault signal;

[0096] The signal value is analyzed to obtain the fault signal value.

[0097] In the above implementation process, the second message data is parsed to obtain signal data, and then the signal data is processed, which can enhance the processing capability of the message data, refine the diagnosis of the fault, and improve the accuracy of the fault diagnosis.

[0098] After obtaining the second message data, it is necessary to parse it. The database file contains information such as message ID and signal name, length, start bit, precision and offset. Use the second function (decode_message() method of cantools) to parse the second message data to obtain signal data.

[0099] The vehicle CAN network contains many signals. When performing fault diagnosis, only the signals related to the fault need to be extracted. Therefore, it is necessary to traverse the acquired signal data to extract the signal name and signal value related to the fault.

[0100] Furthermore, the step of parsing the signal value to obtain the fault signal value includes:

[0101] Performing down-conversion on the signal value according to the third function to obtain a converted signal value;

[0102] Removing prefix information of the converted signal value to obtain a signal value without the prefix information;

[0103] The signal values ​​without prefix information are traversed to obtain the fault signal value.

[0104] In the above implementation process, the signal value is successively converted into a down-signal value and the prefix information is removed to obtain the fault signal value, which can improve the accuracy of the fault signal value and reduce the error caused by the signal value during the fault diagnosis process.

[0105] A signal value stores multiple fault information, so data processing is required for the signal value. First, use the third function (bin() function) to reduce the signal value, convert the decimal into binary, then remove the '0b' prefix in front of the binary string, traverse the binary string, find all the bytes set to 1, and get the fault signal value.

[0106] Furthermore, S5 includes:

[0107] Extract the byte information of the fault signal value;

[0108] According to the byte information, the corresponding fault information in the fault information table is queried to obtain the diagnostic information.

[0109] In the above implementation process, by searching the corresponding fault information in the fault information table according to the byte information of the fault signal value, the specific type and location of the fault can be clarified, the fault can be accurately diagnosed, and the diagnostic information can be obtained.

[0110] Query the corresponding fault information in the fault information table according to the byte information.

[0111] Optionally, the present application can implement user interface display based on PyQt. The interface uses Label tag controls to identify objects on the form, such as "project", "database file path", etc. The ComboBox drop-down combo box control is used to display all items after Excel traversal, providing users with project selection. The LineEdit single-line text box control displays the path of the database file and fault information table for user verification, and is also used to input collected message data. The PushButton button control is used to call related slot functions after the motor to obtain fault information, and the TextEdit multi-line text box displays fault information.

[0112] When the fault diagnosis is online diagnosis, select the corresponding vehicle model through the UI interface and click online diagnosis to display the motor fault information.

[0113] When the fault diagnosis is offline, select the vehicle model item and the local message data to display all fault information.

[0114] Embodiment 2

[0115] In order to execute the method corresponding to the above embodiment 1 to achieve the corresponding functions and technical effects, a vehicle fault diagnosis device is provided below, such as Figure 2 As shown, the device comprises:

[0116] An acquisition module 1 is used to acquire first message data of a vehicle;

[0117] Data acquisition module 2, used to obtain the database file and fault information table of the vehicle; and also used to obtain the fault signal value in the second message data;

[0118] The parsing module 3 is used to parse the first message data according to the database file to obtain the second message data;

[0119] The query module 4 is used to query the fault information table according to the fault signal value to obtain the diagnosis information.

[0120] In the above implementation process, the first message data is parsed according to the database file to obtain the fault signal value, and then the fault signal value is queried, which can improve the efficiency and flexibility of vehicle fault diagnosis, and support fault diagnosis in an offline state. There is no professional requirement for operators, and the diagnosis method is simpler and more effective, which can provide reliability assistance for vehicle development.

[0121] Furthermore, the data acquisition module 2 is also used for:

[0122] Get the model project name of the vehicle;

[0123] Get the file path corresponding to the vehicle model project name;

[0124] Extract the database file and fault information table corresponding to the file path.

[0125] In the above implementation process, the corresponding file path can be accurately located according to the vehicle model project name, and then the database file and fault information table corresponding to the file path are obtained, which can improve the accuracy of fault location and reduce the location error.

[0126] Furthermore, the parsing module 3 is also used for:

[0127] Processing the database file according to the first function to obtain the message period of the fault signal;

[0128] Extracting the message data containing the fault signal from the first message data according to the message period of the fault signal to obtain third message data;

[0129] Filter according to the third message data to obtain the second message data.

[0130] In the above implementation process, the database file is processed to obtain the message period of the fault signal. According to the message period of the fault signal, the message data containing the fault signal can be extracted, and the message data can be accurately distinguished, thereby improving the efficiency of fault diagnosis and facilitating timely diagnosis of faults.

[0131] Furthermore, the parsing module 3 is also used for:

[0132] Extracting the message length corresponding to each message frame in the third message data;

[0133] Determine whether the message length meets the length threshold;

[0134] If not, it is determined that the message frame is an error frame;

[0135] If so, determine that the message frame is a normal frame;

[0136] Filter the error frames in the third message data to obtain the second message data.

[0137] In the above implementation process, the error frames and normal frames in the message frames are distinguished according to the message length of the message frames, and the error frames are filtered at the same time to obtain the second message data containing only normal frames. This can improve the processing speed of the second message data, reduce the error of the second message, and provide data support for subsequent fault diagnosis.

[0138] Furthermore, the data acquisition module 2 is also used for:

[0139] Parsing the second message data according to the second function to obtain signal data;

[0140] Traverse the signal data to obtain the signal value and signal name of the fault signal;

[0141] The signal value is analyzed to obtain the fault signal value.

[0142] In the above implementation process, the second message data is parsed to obtain signal data, and then the signal data is processed, which can enhance the processing capability of the message data, refine the diagnosis of the fault, and improve the accuracy of the fault diagnosis.

[0143] Furthermore, the data acquisition module 2 is also used for:

[0144] Performing down-conversion on the signal value according to the third function to obtain a converted signal value;

[0145] Removing prefix information of the converted signal value to obtain a signal value without the prefix information;

[0146] The signal values ​​without prefix information are traversed to obtain the fault signal value.

[0147] In the above implementation process, the signal value is successively converted into a down-signal value and the prefix information is removed to obtain the fault signal value, which can improve the accuracy of the fault signal value and reduce the error caused by the signal value during the fault diagnosis process.

[0148] Furthermore, the query module 4 is also used for:

[0149] Extract the byte information of the fault signal value;

[0150] According to the byte information, the corresponding fault information in the fault information table is queried to obtain the diagnostic information.

[0151] In the above implementation process, by searching the corresponding fault information in the fault information table according to the byte information of the fault signal value, the specific type and location of the fault can be clarified, the fault can be accurately diagnosed, and the diagnostic information can be obtained.

[0152] The above-mentioned vehicle fault diagnosis device can implement the method of the above-mentioned embodiment 1. The options in the above-mentioned embodiment 1 are also applicable to this embodiment and will not be described in detail here.

[0153] The rest of the contents of the embodiments of the present application can refer to the contents of the above-mentioned embodiment 1, and will not be repeated in this embodiment.

[0154] Embodiment 3

[0155] An embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the vehicle fault diagnosis method of embodiment 1.

[0156] Optionally, the above-mentioned electronic device may be a server.

[0157] See also Figure 3 , Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include a processor 31, a communication interface 32, a memory 33 and at least one communication bus 34. The communication bus 34 is used to realize direct connection and communication between these components. The communication interface 32 of the device in the embodiment of the present application is used to communicate signaling or data with other node devices. The processor 31 may be an integrated circuit chip with signal processing capabilities.

[0158] The processor 31 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor 31 can also be any conventional processor, etc.

[0159] The memory 33 may be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), etc. The memory 33 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 31, the device can execute the above-mentioned Figure 1 The method embodiment involves various steps.

[0160] Optionally, the electronic device may further include a storage controller and an input / output unit. The memory 33, the storage controller, the processor 31, the peripheral interface, and the input / output unit are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components may be electrically connected to each other via a communication bus 34. The processor 31 is used to execute executable modules stored in the memory 33, such as software function modules or computer programs included in the device.

[0161] The input and output unit is used to provide users with the task creation and to create an optional time period or preset execution time for the task to enable interaction between the user and the server. The input and output unit can be, but is not limited to, a mouse and a keyboard.

[0162] Understandably, Figure 3 The structure shown is for illustration only. The electronic device may also include Figure 3 More or fewer components as shown, or with Figure 3 Different configurations are shown. Figure 3 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0163] In addition, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the vehicle fault diagnosis method of embodiment 1.

[0164] The embodiment of the present application also provides a computer program product, which, when running on a computer, enables the computer to execute the method described in the method embodiment.

[0165] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flowchart, and the combination of boxes in the block diagram and / or the flowchart, can be implemented with a dedicated hardware-based device that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0166] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0167] If the functions are implemented in the form of software function modules 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 application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard drives, ROM, RAM, magnetic disks, or optical disks.

[0168] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application. It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0169] The above is only a specific implementation of the present application, but the protection range of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical range disclosed in the present application, which should be included in the protection range of the present application. Therefore, the protection range of the present application should be based on the protection range of the claims.

[0170] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

Claims

1. A vehicle fault diagnosis method, characterized in that: The method comprises: Obtaining first message data of the vehicle; Obtaining a database file and a fault information table of the vehicle; Parsing the first message data according to the database file to obtain second message data; Obtaining a fault signal value in the second message data; The fault information table is queried according to the fault signal value to obtain diagnostic information.

2. The vehicle fault diagnosis method according to claim 1, characterized in that: The step of obtaining the database file and the fault information table of the vehicle comprises: Get the model project name of the vehicle; Get the file path corresponding to the vehicle model project name; The database file and the fault information table corresponding to the file path are extracted.

3. The vehicle fault diagnosis method according to claim 1, characterized in that: The step of parsing the first message data according to the database file to obtain the second message data includes: Processing the database file according to the first function to obtain a message period of the fault signal; Extracting the message data containing the fault signal from the first message data according to the message period of the fault signal to obtain third message data; Filter according to the third message data to obtain the second message data.

4. The vehicle fault diagnosis method according to claim 3, characterized in that: The step of filtering according to the third message data to obtain the second message data includes: Extracting the message length corresponding to each message frame in the third message data; Determine whether the message length meets the length threshold; If not, it is determined that the message frame is an error frame; If so, determine that the message frame is a normal frame; Filter the error frames in the third message data to obtain the second message data.

5. The vehicle fault diagnosis method according to claim 1, characterized in that: The step of obtaining the fault signal value in the second message data comprises: Parsing the second message data according to a second function to obtain signal data; Traversing the signal data to obtain a signal value and a signal name of a fault signal; The signal value is analyzed to obtain the fault signal value.

6. The vehicle fault diagnosis method according to claim 5, characterized in that: The step of analyzing the signal value to obtain the fault signal value includes: Performing down-conversion on the signal value according to a third function to obtain a converted signal value; Removing prefix information of the converted signal value to obtain a signal value without the prefix information; The signal value without the prefix information is traversed to obtain the fault signal value.

7. The vehicle fault diagnosis method according to claim 1, characterized in that: The step of querying the fault information table according to the fault signal value to obtain diagnostic information comprises: Extracting byte information of the fault signal value; According to the byte information, the corresponding fault information in the fault information table is queried to obtain the diagnosis information.

8. A vehicle fault diagnosis device, characterized in that: The device comprises: An acquisition module, used for acquiring first message data of a vehicle; A data acquisition module, used to obtain the database file and fault information table of the vehicle; and also used to obtain the fault signal value in the second message data; A parsing module, used for parsing the first message data according to the database file to obtain second message data; The query module is used to query the fault information table according to the fault signal value to obtain diagnostic information.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the vehicle fault diagnosis method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: A computer program is stored therein, and when the computer program is executed by a processor, a fault diagnosis method for a vehicle as claimed in any one of claims 1 to 7 is implemented.

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