Vehicle fault analysis method and device, computer equipment and storage medium

Abstract

The application relates to the technical field of vehicle fault analysis, and discloses a vehicle fault analysis method and device, computer equipment and a storage medium, the method comprising the following steps: when detecting that a target vehicle is abnormal based on vehicle condition information of the target vehicle, determining fault information of the target vehicle; performing word segmentation and label processing on the vehicle condition information and the fault information to obtain a first information type and a first information value; generating input text based on a preset language template, the first information type and the first information value; inputting the input text into a preset vehicle fault analysis model to obtain a vehicle fault analysis result. The application can respond to fault conditions in a timely manner, avoids dangerous consequences caused by the fact that vehicle abnormal information cannot be fed back in a timely manner due to negligence or lack of experience of a user, the input text is input into the preset vehicle fault analysis model to obtain the vehicle fault analysis result, vehicle fault analysis can be performed remotely and in real time, and a conclusion can be given, and human resources are saved.

Description

Technical Field

[0001] This invention relates to the field of automotive fault diagnosis technology, specifically to onboard fault analysis methods, devices, computer equipment, and storage media. Background Technology

[0002] Cars have become an indispensable tool for people's travel, and at the same time, users' requirements for car safety are increasing. However, vehicles inevitably experience malfunctions during use, such as engine failure, brake system failure, suspension system failure, and electrical system failure. To ensure driving safety, once a malfunction occurs, the cause should be identified and addressed promptly. Generally, when a vehicle malfunctions, it should be taken to a 4S dealership or auto repair shop for repair and maintenance as soon as possible. In some special circumstances, users may not be able to reach a 4S dealership or auto repair shop in time; in such cases, remote troubleshooting can usually be used.

[0003] Currently, there are two main methods for remote fault handling: one is for users to describe the fault information displayed on the vehicle's infotainment system and remotely consult with automotive after-sales staff or repair personnel to obtain repair suggestions. However, the fault information displayed on the vehicle's infotainment system is incomplete, and for some faults, repair personnel may find it difficult to derive a repair solution based solely on the information displayed. The other method is for users to search for fault information through search engines to obtain repair suggestions. This method requires significant effort and a high level of expertise from the user; for users lacking specialized technical skills, it is difficult to find professional fault diagnosis and repair methods. Therefore, as the professionalism of vehicle fault repair increases significantly, there is an urgent need to find a method and system that can provide professional in-vehicle fault repair suggestions in real time. Summary of the Invention

[0004] In view of this, the present invention provides a vehicle fault analysis method, device, computer equipment and storage medium to solve the problem that in the prior art, due to the incomplete fault information displayed by the vehicle's infotainment system and the lack of professional technical means by users, remote vehicle fault support is difficult.

[0005] In a first aspect, the present invention provides a fault analysis method, the method comprising: when an abnormality is detected in the target vehicle based on the vehicle condition information of the target vehicle, determining the fault information of the target vehicle; performing word segmentation and annotation processing on the vehicle condition information and the fault information to obtain a first information type and a first information value; generating input text based on a preset language template, the first information type and the first information value; and inputting the input text into a preset vehicle fault analysis model to obtain an in-vehicle fault analysis result.

[0006] The vehicle fault analysis method provided in this embodiment first detects whether the target vehicle is malfunctioning by using its vehicle condition information. This allows for timely response to fault situations and avoids dangerous consequences caused by user negligence or lack of experience leading to delayed feedback of vehicle malfunction information. Then, by performing word segmentation and annotation on the vehicle condition information and fault information, the first information type and the first information value are imported into a preset language template based on the annotations. This transforms the vehicle condition information and fault information into machine-readable language, simplifying the process of the user acting as an information relay center and improving the efficiency and accuracy of vehicle fault analysis. Finally, by inputting the input text into a preset vehicle fault analysis model, vehicle fault analysis results are obtained. This allows for remote and real-time vehicle fault analysis and conclusion delivery, saving human resources.

[0007] In one optional implementation, the process of detecting whether the target vehicle is abnormal based on the vehicle condition information of the target vehicle includes: acquiring the vehicle condition information of the target vehicle, the vehicle condition information including a second information type and a second information value; determining a fault rule corresponding to the second information type according to the second information type and a mapping relationship between the second information type and a preset fault rule; and detecting whether the vehicle condition information is abnormal according to the second information value and the fault rule.

[0008] The vehicle fault analysis method provided in this embodiment determines the fault rule corresponding to the second information type by using the mapping relationship between the second information type and the preset fault rule. Based on various information types, it performs targeted fault anomaly judgment, thereby improving the accuracy of fault anomaly judgment.

[0009] In one optional implementation, determining the fault information of the target vehicle includes: determining a fault code based on the second information value and second information type corresponding to the abnormal vehicle condition information and the fault rule; and using the fault code as fault information.

[0010] The vehicle fault analysis method provided in this embodiment determines the fault code by using the second information value and second information type corresponding to the abnormal vehicle condition information and the fault rules, providing valuable reference data for the preset vehicle fault analysis model and improving the accuracy of the vehicle fault analysis results.

[0011] In one optional implementation, the step of performing word segmentation and tagging processing on the vehicle condition information and the fault information to obtain a first information type and a first information value includes: performing word segmentation processing on the vehicle condition information and the fault information to extract information type keywords and corresponding information value keywords; and tagging the information type keywords and the information value keywords with keyword tags to obtain the first information type and the first information value.

[0012] The vehicle fault analysis method provided in this embodiment lays the foundation for subsequent input text generation by labeling the information type keywords and information value keywords with keyword tags, thereby improving the data accuracy of the input text and thus improving the accuracy of the vehicle fault analysis results.

[0013] In one optional implementation, the preset language template includes text positions corresponding to the keyword tags; generating input text based on the preset language template, the first information type, and the first information value includes: filling the first information type and the first information value into the corresponding text positions in the preset language template based on the keyword tags, thereby generating the input text.

[0014] The fault analysis method provided by this invention improves the import efficiency by filling the first information type and the first information value into the corresponding text position in the preset language template through the keyword tags, thereby improving the efficiency of vehicle fault analysis results.

[0015] In one optional implementation, the step of inputting the input text into a preset vehicle fault analysis model to obtain the vehicle fault analysis result includes: calling the transmission interface of the preset vehicle fault analysis model, uploading the model key and the input text, and obtaining the vehicle fault analysis result output by the preset vehicle fault analysis model.

[0016] The fault analysis method provided by this invention obtains vehicle fault analysis results by inputting the input text into a preset vehicle fault analysis model. It can perform vehicle fault analysis remotely and in real time and give conclusions, saving human resources.

[0017] In one optional implementation, the method further includes: sending the vehicle fault analysis results and vehicle fault analysis data to the vehicle display screen; the vehicle fault analysis data includes at least one of the vehicle condition information or fault information.

[0018] The fault analysis method provided by this invention sends the vehicle fault analysis results and vehicle fault analysis data to the vehicle display screen for easy viewing by the user.

[0019] Secondly, the present invention provides an in-vehicle fault analysis device, the device comprising: a determination module, configured to determine fault information of the target vehicle when an abnormality is detected in the target vehicle based on the vehicle condition information of the target vehicle; a processing module, configured to perform word segmentation and annotation processing on the vehicle condition information and the fault information to obtain a first information type and a first information value; a generation module, configured to generate input text based on a preset language template, the first information type and the first information value; and an input module, configured to input the input text into a preset vehicle fault analysis model to obtain an in-vehicle fault analysis result.

[0020] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the vehicle fault analysis method of the first aspect or any corresponding embodiment described above.

[0021] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the vehicle fault analysis method of the first aspect or any corresponding embodiment described above.

[0022] The beneficial effects of this invention are:

[0023] 1. The vehicle fault analysis method provided in this embodiment first detects whether the target vehicle is abnormal by using the vehicle condition information, which can respond to fault situations in a timely manner and avoid dangerous consequences caused by the failure to promptly report vehicle abnormal information due to user negligence or lack of experience; then, by performing word segmentation and annotation processing on the vehicle condition information and the fault information, the first information type and the first information value are imported into a preset language template based on the annotation, making the vehicle condition information and the fault information into machine-recognizable language, simplifying the process of the user acting as an information relay center, and improving the efficiency and accuracy of vehicle fault analysis; finally, by inputting the input text into a preset vehicle fault analysis model, the vehicle fault analysis results are obtained, which can perform vehicle fault analysis and provide conclusions remotely and in real time, saving human resources.

[0024] 2. The vehicle fault analysis method provided in this embodiment determines the fault rule corresponding to the second information type by using the mapping relationship between the second information type and the preset fault rule. Based on various information types, it performs targeted fault anomaly judgment, thereby improving the accuracy of fault anomaly judgment.

[0025] 3. The vehicle fault analysis method provided in this embodiment determines the fault code by using the second information value and second information type corresponding to the abnormal vehicle condition information and the fault rules, providing valuable reference data for the preset vehicle fault analysis model and improving the accuracy of the vehicle fault analysis results.

[0026] 4. The vehicle fault analysis method provided in this embodiment, by labeling the information type keywords and the information value keywords with keyword tags, lays the foundation for the subsequent generation of input text, improves the data accuracy of the input text, and thus improves the accuracy of the vehicle fault analysis results.

[0027] 5. The fault analysis method provided by the present invention, by using the keyword tags, fills the first information type and the first information value into the corresponding text position in the preset language template, thereby improving the import efficiency and thus improving the efficiency of vehicle fault analysis results.

[0028] 6. The fault analysis method provided by the present invention obtains vehicle fault analysis results by inputting the input text into a preset vehicle fault analysis model. It can perform vehicle fault analysis remotely and in real time and give conclusions, saving human resources.

[0029] 7. The fault analysis method provided by the present invention sends the vehicle fault analysis results and vehicle fault analysis data to the vehicle display screen for easy viewing by the user. Attached Figure Description

[0030] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0031] Figure 1 This is a flowchart illustrating the vehicle-mounted fault analysis method according to an embodiment of the present invention;

[0032] Figure 2 This is a flowchart illustrating another vehicle-mounted fault analysis method according to an embodiment of the present invention;

[0033] Figure 3 This is a structural block diagram of an on-board fault analysis device according to an embodiment of the present invention;

[0034] Figure 4 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Under normal circumstances, when a vehicle malfunctions, it should be taken to a 4S store or auto repair shop for repair and maintenance in a timely manner. In some special cases, users may not be able to get to a 4S store or auto repair shop in time. In such cases, users can usually deal with the problem remotely.

[0037] Currently, there are two main methods for remote fault handling: one is for users to describe the fault information displayed on the vehicle's infotainment system and remotely consult with automotive after-sales staff or repair personnel to obtain repair suggestions. However, the fault information displayed on the vehicle's infotainment system is incomplete, and for some faults, repair personnel may find it difficult to derive a repair solution based solely on the information displayed. The other method is for users to search for fault information through a search engine to obtain repair suggestions. This method requires significant effort and a high level of expertise from the user; for users lacking specialized technical skills, it is difficult to find professional fault diagnosis and repair methods. Therefore, as the professionalism of vehicle fault repair increases, there is an urgent need to find a method and system that can provide professional in-vehicle fault repair suggestions in real time, thereby solving the problem of difficulties in providing remote vehicle fault support due to incomplete fault information displayed on the vehicle's infotainment system and the lack of professional technical skills among users.

[0038] According to an embodiment of the present invention, an embodiment of an on-board fault analysis method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0039] This embodiment provides a vehicle-mounted fault analysis method. Figure 1 This is a flowchart of an on-board fault analysis method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0040] Step S101: When an abnormality is detected in the target vehicle based on the vehicle condition information of the target vehicle, the fault information of the target vehicle is determined.

[0041] Specifically, vehicle condition information mainly includes one or more of the following: vehicle driving data information, body sensor data information, vehicle maintenance information, and vehicle upkeep information. Among them, the vehicle's built-in fault detection system generates fault codes based on the vehicle driving data information and body sensor data information, thereby determining the fault information of the target vehicle.

[0042] Step S102: Perform word segmentation and annotation processing on the vehicle condition information and the fault information to obtain the first information type and the first information value.

[0043] Specifically, the word segmentation and annotation process is based on natural language processing and is mainly used to segment text according to word boundaries and annotate the part-of-speech or other semantic information of each word. In this embodiment, word segmentation and annotation process is used to extract the information types and information values ​​from the vehicle condition information and the fault information, and then label them respectively to obtain the first information type and the first information value. Specifically, the first information type includes vehicle driving data information, vehicle body sensor data information, vehicle maintenance information and vehicle repair information, as well as information types in fault codes, such as fuel tank temperature, engine coolant temperature and fault codes. The first information value is the value corresponding to the first information type. The vehicle condition information and the fault information are segmented into words to extract keywords such as vehicle mileage A, repair time B[n][1] and record B[n][2], maintenance time C[n][1] and record C[n][2], and fault code D. According to the keyword type, each word is labeled with an identifiable tag. As an example, extract the "fuel tank temperature" from "fuel tank temperature 200 degrees Celsius" and label it with "fuel tank temperature information type". Extract "200 degrees Celsius" and label it with "fuel tank temperature information value".

[0044] Step S103: Generate based on the preset language template, the first information type, and the first information value.

[0045] Specifically, the preset language template is pre-set, for example, "If you are an expert in the automotive diagnostics industry, please provide comprehensive diagnostic suggestions based on the following situation: A car has driven A kilometers, [repaired component B[n][1] at time B[n][2]]...n, [performed maintenance C[n][2] at time C[n][1]]...n, and now a fault code D has appeared." Based on the labeled tags, the first information type and the first information value are imported into the preset language template to generate input text, which is a machine-recognizable language.

[0046] Step S104: Input the input text into a preset vehicle fault analysis model to obtain the vehicle fault analysis result.

[0047] Specifically, the preset vehicle fault analysis model can be a neural network model trained based on vehicle condition information, fault information and expert database in the database. Commonly used models include multilayer perceptron (MLP), convolutional neural network (CNN) and recurrent neural network (RNN), etc., or it can be an external natural language model, such as ChatGPT.

[0048] The vehicle fault analysis method provided in this embodiment first detects whether the target vehicle is malfunctioning by using its vehicle condition information. This allows for timely response to fault situations and avoids dangerous consequences caused by user negligence or lack of experience leading to delayed feedback of vehicle malfunction information. Then, by performing word segmentation and annotation on the vehicle condition information and fault information, the first information type and the first information value are imported into a preset language template based on the annotations. This transforms the vehicle condition information and fault information into machine-readable language, simplifying the process of the user acting as an information relay center and improving the efficiency and accuracy of vehicle fault analysis. Finally, by inputting the input text into a preset vehicle fault analysis model, vehicle fault analysis results are obtained. This allows for remote and real-time vehicle fault analysis and conclusion delivery, saving human resources.

[0049] This embodiment provides a vehicle-mounted fault analysis method, which can be used in the aforementioned mobile terminals, such as mobile phones and tablets. Figure 2 This is a flowchart of an on-board fault analysis method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0050] Step S201: When an abnormality is detected in the target vehicle based on the vehicle condition information of the target vehicle, the fault information of the target vehicle is determined.

[0051] Specifically, the process of detecting whether a target vehicle is abnormal based on its vehicle condition information includes: acquiring the vehicle condition information of the target vehicle, the vehicle condition information including a second information type and a second information value; determining a fault rule corresponding to the second information type according to the mapping relationship between the second information type and a preset fault rule; and detecting whether the vehicle condition information is abnormal according to the second information value and the fault rule. For example, when the second information type is cylinder combustion data, a fault rule for the cylinder combustion data is determined, and according to the combustion data fault rule, it is detected whether the combustion data of each cylinder exceeds a preset threshold. If the combustion data of any cylinder exceeds the preset threshold, then the vehicle condition information is abnormal. Here, compared with the first information type mentioned above, the second information type does not include a fault code information type.

[0052] The vehicle fault analysis method provided in this embodiment determines the fault rule corresponding to the second information type by using the mapping relationship between the second information type and the preset fault rule. Based on various information types, it performs targeted fault anomaly judgment, thereby improving the accuracy of fault anomaly judgment.

[0053] Specifically, based on the second information value and second information type corresponding to the abnormal vehicle condition information and the aforementioned fault rules, a fault code is determined; this fault code is then used as fault information. Automotive fault codes, also known as OBD fault codes (On-Board Diagnostics), are a set of codes generated by the vehicle's electronic control unit (ECU) when a fault is detected in the vehicle. These codes describe the specific type of fault in the vehicle system. Each fault code consists of one letter and four digits, such as "P0301," where the letter indicates the faulty system or subsystem, and the numbers indicate the specific problem. Fault codes are generally read through the OBD-II (On-Board Diagnostics II) interface, which is typically equipped in modern vehicles. This interface allows communication with the vehicle's ECU to obtain fault code information. Fault codes are only indicative information and cannot be used alone to determine specific repair methods. For example, when cylinder combustion data exceeds a preset threshold, the fault code is determined to be P030. Fault code P030 typically indicates a misfire problem in the engine. Misfire refers to an abnormality in the combustion process in the cylinder, resulting in incomplete combustion or complete cessation of combustion of the air-fuel mixture in the cylinder.

[0054] The vehicle fault analysis method provided in this embodiment determines the fault code by using the second information value and second information type corresponding to the abnormal vehicle condition information and the fault rules, providing valuable reference data for the preset vehicle fault analysis model and improving the accuracy of the vehicle fault analysis results.

[0055] Step S202: Perform word segmentation and annotation processing on the vehicle condition information and the fault information to obtain the first information type and the first information value.

[0056] Specifically, step S202 includes:

[0057] Step S2021: Perform word segmentation on the vehicle condition information and the fault information, and extract information type keywords and corresponding information value keywords.

[0058] Specifically, the vehicle condition information and the fault information are segmented into words, and then the keywords corresponding to the information types and information values ​​in the vehicle condition information and the fault information are extracted. Specifically, the first information type includes vehicle driving data information, vehicle sensor data information, vehicle repair information, vehicle maintenance information, and information types in fault codes, such as fuel tank temperature, engine coolant temperature, and fault codes. The first information value is the value corresponding to the first information type. The vehicle condition information and the fault information are segmented into words, and keywords such as vehicle mileage A, repair time B[n][1] and record B[n][2], maintenance time C[n][1] and record C[n][2], and fault code D are extracted.

[0059] Step S2022: Tag the information type keywords and the information value keywords with keyword tags to obtain the first information type and the first information value.

[0060] Specifically, each word is labeled with an identifiable tag based on its keyword type. For example, "fuel tank temperature" is extracted from "fuel tank temperature 200 degrees Celsius" and labeled with the "fuel tank temperature information type" tag, while "200 degrees Celsius" is extracted and labeled with the "fuel tank temperature information value" tag, thus obtaining the first information type and the first information value.

[0061] The vehicle fault analysis method provided in this embodiment lays the foundation for subsequent input text generation by labeling the information type keywords and information value keywords with keyword tags, thereby improving the data accuracy of the input text and thus improving the accuracy of the vehicle fault analysis results.

[0062] Step S203: Generate input text based on the preset language template, the first information type, and the first information value.

[0063] Specifically, step S203 includes:

[0064] Step S2031: Based on the keyword tags, fill the first information type and the first information value into the corresponding text position in the preset language template to generate the input text.

[0065] Specifically, the preset language template is pre-set, for example, "If you are an expert in the automotive diagnostics industry, please provide comprehensive diagnostic suggestions based on the following situation: A car has driven A kilometers, [repaired component B[n][1] at time B[n][2]]...n, [performed maintenance C[n][2] at time C[n][1]]...n, and now a fault code D has appeared." The preset language template includes text positions corresponding to the keyword tags. Based on the keyword tags and the text positions, the first information type and the first information value are imported into the preset language template to generate input text. The input text is machine-recognizable language.

[0066] The fault analysis method provided by this invention improves the import efficiency by filling the first information type and the first information value into the corresponding text position in the preset language template through the keyword tags, thereby improving the efficiency of vehicle fault analysis results.

[0067] Step S204: Input the input text into a preset vehicle fault analysis model to obtain the vehicle fault analysis result.

[0068] Specifically, step S204 includes:

[0069] Step S2041: Call the transmission interface of the preset vehicle fault analysis model, upload the model key and the input text, and obtain the vehicle fault analysis result output by the preset vehicle fault analysis model.

[0070] Specifically, when using ChatGPT as the preset vehicle fault analysis model, the chatgpt interface is called, passing in OPENAI_API_KEY and the input text to obtain the on-board fault analysis results and fault repair suggestions from chatgpt.

[0071] The fault analysis method provided by this invention obtains vehicle fault analysis results by inputting the input text into a preset vehicle fault analysis model. It can perform vehicle fault analysis remotely and in real time and give conclusions, saving human resources.

[0072] In some optional embodiments, the method further includes: sending the vehicle fault analysis results and vehicle fault analysis data to the vehicle infotainment display screen; the vehicle fault analysis data includes at least one of the vehicle condition information or fault information. Specifically, the vehicle fault analysis results and fault repair suggestions displayed on the user's vehicle infotainment display screen are not limited to fault repair suggestions, but also include professional maintenance suggestions, driving suggestions, etc., provided by the preset vehicle fault analysis model based on the vehicle condition information and fault information.

[0073] The fault analysis method provided by this invention sends the vehicle fault analysis results and vehicle fault analysis data to the vehicle display screen for easy viewing by the user.

[0074] This embodiment also provides an on-board fault analysis device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0075] This embodiment provides an on-board fault analysis device, such as... Figure 3 As shown, it includes:

[0076] The determination module 301 is used to determine the fault information of the target vehicle when an abnormality is detected in the target vehicle based on the vehicle condition information of the target vehicle.

[0077] Processing module 302 is used to perform word segmentation and annotation processing on the vehicle condition information and the fault information to obtain a first information type and a first information value;

[0078] The generation module 303 is used to generate input text based on a preset language template, the first information type, and the first information value;

[0079] The input module 304 is used to input the input text into a preset vehicle fault analysis model to obtain the vehicle fault analysis result.

[0080] The vehicle fault analysis device provided in this embodiment first detects whether the target vehicle is malfunctioning by using its vehicle condition information. This allows for timely response to fault situations, avoiding dangerous consequences caused by user negligence or lack of experience leading to delayed feedback of vehicle malfunction information. Then, by performing word segmentation and annotation on the vehicle condition information and fault information, the device imports the first information type and the first information value into a preset language template based on the annotations. This transforms the vehicle condition information and fault information into machine-readable language, simplifying the process of the user acting as an information relay center and improving the efficiency and accuracy of vehicle fault analysis. Finally, by inputting the input text into a preset vehicle fault analysis model, the device obtains vehicle fault analysis results. This allows for remote and real-time vehicle fault analysis and conclusion generation, saving human resources.

[0081] In some alternative implementations, the determining module 301 includes:

[0082] The vehicle condition information acquisition unit is used to acquire the vehicle condition information of the target vehicle, wherein the vehicle condition information includes a second information type and a second information value.

[0083] The fault rule determination unit is used to determine the fault rule corresponding to the second information type based on the second information type and the mapping relationship between the second information type and the preset fault rule.

[0084] The vehicle condition information detection unit is used to detect whether the vehicle condition information is abnormal based on the second information value and the fault rule.

[0085] The vehicle fault analysis device provided in this embodiment determines the fault rule corresponding to the second information type by means of the mapping relationship between the second information type and the preset fault rule. Based on various information types, it performs targeted fault anomaly judgment, thereby improving the accuracy of fault anomaly judgment.

[0086] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0087] In some alternative implementations, the determining module 301 further includes:

[0088] The fault code determination unit is used to determine the fault code based on the second information value and second information type corresponding to the abnormal vehicle condition information and the fault rule.

[0089] As a unit, it is used to treat the fault code as fault information.

[0090] The vehicle fault analysis device provided in this embodiment determines the fault code by using the second information value and second information type corresponding to the abnormal vehicle condition information and the fault rules, providing valuable reference data for the preset vehicle fault analysis model and improving the accuracy of the vehicle fault analysis results.

[0091] In some optional implementations, the processing module 302 further includes:

[0092] The keyword extraction unit is used to perform word segmentation on the vehicle condition information and the fault information, and extract information type keywords and corresponding information value keywords.

[0093] The keyword tagging unit is used to tag the information type keywords and the information value keywords with keyword labels to obtain the first information type and the first information value.

[0094] The vehicle fault analysis device provided in this embodiment lays the foundation for subsequent input text generation by labeling the information type keywords and information value keywords with keyword tags, thereby improving the data accuracy of the input text and thus improving the accuracy of the vehicle fault analysis results.

[0095] In some alternative implementations, the generation module 303 further includes:

[0096] The input text generation unit is used to fill the first information type and the first information value into the corresponding text position in the preset language template based on the keyword tags, thereby generating the input text.

[0097] The fault analysis method provided by this invention improves the import efficiency by filling the first information type and the first information value into the corresponding text position in the preset language template through the keyword tags, thereby improving the efficiency of vehicle fault analysis results.

[0098] In some alternative implementations, the input module 304 further includes:

[0099] The calling unit is used to call the transmission interface of the preset vehicle fault analysis model, upload the model key and the input text, and obtain the vehicle fault analysis results output by the preset vehicle fault analysis model.

[0100] The fault analysis method provided by this invention obtains vehicle fault analysis results by inputting the input text into a preset vehicle fault analysis model. It can perform vehicle fault analysis remotely and in real time and give conclusions, saving human resources.

[0101] In some alternative implementations, the on-board fault analysis device further includes:

[0102] The sending module is used to send the vehicle fault analysis results and vehicle fault analysis data to the vehicle display screen; the vehicle fault analysis data includes at least one of the vehicle condition information or fault information.

[0103] In this embodiment, the vehicle-mounted fault analysis device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0104] This invention also provides a computer device having the above-described features. Figure 3 The vehicle-mounted fault analysis device shown.

[0105] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 4As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 4 Take a processor 10 as an example.

[0106] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0107] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0108] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0109] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0110] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0111] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded via a network and stored on a remote storage medium or a non-transitory machine-readable storage medium and to be stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium may also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0112] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A vehicle-mounted fault analysis method, characterized in that, The method includes: When an anomaly is detected in the target vehicle based on its vehicle condition information, the fault information of the target vehicle is determined. The vehicle condition information and the fault information are segmented and labeled to obtain a first information type and a first information value. The input text is generated based on the preset language template, the first information type, and the first information value. Input the input text into a preset vehicle fault analysis model to obtain the vehicle fault analysis results; The step of performing word segmentation and annotation processing on the vehicle condition information and the fault information to obtain a first information type and a first information value includes: performing word segmentation processing on the vehicle condition information and the fault information to extract information type keywords and corresponding information value keywords; annotating the information type keywords and the information value keywords with keyword tags to obtain the first information type and the first information value; the preset language template includes text positions corresponding to the keyword tags; the step of generating input text based on the preset language template, the first information type, and the first information value includes: filling the first information type and the first information value into the corresponding text positions in the preset language template based on the keyword tags to generate the input text; The process of detecting whether the target vehicle is abnormal based on the vehicle condition information of the target vehicle includes: acquiring the vehicle condition information of the target vehicle, the vehicle condition information including a second information type and a second information value; determining a fault rule corresponding to the second information type according to the second information type and the mapping relationship between the second information type and a preset fault rule; and detecting whether the vehicle condition information is abnormal according to the second information value and the fault rule. Determining the fault information of the target vehicle includes: determining a fault code based on the second information value and second information type corresponding to the abnormal vehicle condition information and the fault rule; and using the fault code as fault information.

2. The vehicle-mounted fault analysis method according to claim 1, characterized in that, The step of inputting the input text into a preset vehicle fault analysis model to obtain vehicle fault analysis results includes: Call the transmission interface of the preset vehicle fault analysis model, upload the model key and the input text, and obtain the vehicle fault analysis results output by the preset vehicle fault analysis model.

3. The vehicle-mounted fault analysis method according to claim 1, characterized in that, The method further includes: The vehicle fault analysis results and vehicle fault analysis data are sent to the vehicle display screen; the vehicle fault analysis data includes at least one of the vehicle condition information or fault information.

4. An on-board fault analysis device, characterized in that, The device includes: The determination module is used to determine the fault information of the target vehicle when an abnormality is detected in the target vehicle based on the vehicle condition information of the target vehicle. The processing module is used to perform word segmentation and annotation processing on the vehicle condition information and the fault information to obtain a first information type and a first information value; The generation module is used to generate input text based on a preset language template, the first information type, and the first information value; The input module is used to input the input text into a preset vehicle fault analysis model to obtain vehicle fault analysis results; The step of performing word segmentation and tagging on the vehicle condition information and the fault information to obtain a first information type and a first information value includes: performing word segmentation on the vehicle condition information and the fault information to extract information type keywords and corresponding information value keywords; and tagging the information type keywords and the information value keywords with keyword tags to obtain the first information type and the first information value. The preset language template includes text positions corresponding to the keyword tags; generating input text based on the preset language template, the first information type, and the first information value includes: filling the first information type and the first information value into the corresponding text positions in the preset language template based on the keyword tags, and generating the input text; The process of detecting whether the target vehicle is abnormal based on the vehicle condition information of the target vehicle includes: acquiring the vehicle condition information of the target vehicle, the vehicle condition information including a second information type and a second information value; determining a fault rule corresponding to the second information type according to the second information type and the mapping relationship between the second information type and a preset fault rule; and detecting whether the vehicle condition information is abnormal according to the second information value and the fault rule. Determining the fault information of the target vehicle includes: determining a fault code based on the second information value and second information type corresponding to the abnormal vehicle condition information and the fault rule; and using the fault code as fault information.

5. A computer device, characterized in that, include: The system includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the vehicle fault analysis method according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the vehicle fault analysis method according to any one of claims 1 to 3.

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