Vehicle fault diagnosis method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to a vehicle fault diagnosis method and device, computer equipment, a readable storage medium and a program product. The method comprises the steps of obtaining real-time data of a whole vehicle, obtaining key feature data according to the real-time data of the whole vehicle, establishing a 3D virtual model in a VR scene, mapping the real-time data of the whole vehicle to the VR scene so as to simulate the motion state of the vehicle in the VR scene, obtaining a vehicle potential fault fed back by a user in the process that the user views the VR scene through VR equipment, and obtaining the vehicle potential fault according to the vehicle potential fault. And performing fault diagnosis on the vehicle according to the potential fault of the vehicle. By adopting the method, various data and dynamic performance of the vehicle can be observed in real time in a virtual environment, so that potential faults can be quickly positioned and identified, and the efficiency and accuracy of fault diagnosis are improved.

Description

Technical Field

[0001] The present application relates to the technical field of new energy commercial vehicles, and in particular to a vehicle fault diagnosis method, device, computer equipment, readable storage medium and program product. Background Art

[0002] With the rapid development of automobile technology, the degree of electrification in the automobile industry is becoming increasingly higher, and the complexity and difficulty of automobile fault diagnosis is gradually increasing.

[0003] Traditional methods usually rely on professional technicians and complex testing equipment to locate problems by checking each component of the vehicle one by one. This method is not only time-consuming and labor-intensive, but also relatively inefficient. In addition, due to the complexity and diversity of vehicle data, traditional diagnostic methods often find it difficult to provide intuitive and accurate diagnostic results. Summary of the invention

[0004] Based on this, it is necessary to provide a vehicle fault diagnosis method, device, computer equipment, readable storage medium and program product that can accurately locate vehicle faults in response to the above technical problems.

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

[0006] Obtain the real-time data of the whole vehicle, and obtain key feature data based on the real-time data of the whole vehicle; the real-time data of the whole vehicle includes contact data and non-contact data; contact data is collected by sensors, and contact data is received from the cloud through wireless communication technology;

[0007] Establish a 3D virtual model in the VR scene, and map the real-time data of the whole vehicle to the VR scene to simulate the movement state of the vehicle in the VR scene; the 3D virtual model includes a vehicle virtual model and an environment virtual model;

[0008] When the user is viewing the VR scene through the VR device, the potential vehicle faults reported by the user are obtained, and the vehicle fault diagnosis is performed based on the potential vehicle faults.

[0009] In one embodiment, the step of acquiring key characteristic data according to the real-time data of the whole vehicle includes:

[0010] Perform data cleaning on the real-time data of the whole vehicle to remove noise values, abnormal values ​​and redundant values ​​in the real-time data of the whole vehicle, and normalize the cleaned data to obtain normalized data;

[0011] Extract key feature data from normalized data and perform quality verification on the key feature data;

[0012] When the quality verification is passed, the key feature data is saved in the database.

[0013] In one embodiment, the real-time data of the whole vehicle includes instrument data and status data; mapping the real-time data of the whole vehicle to the VR scene includes:

[0014] Mapping instrument data to the dashboard of the vehicle virtual model;

[0015] The vehicle virtual model is updated according to the status data, and the environment virtual model is updated according to the environment data.

[0016] In one embodiment, the step of diagnosing a vehicle fault according to a potential fault of the vehicle includes:

[0017] Locate the potential fault locations of the vehicle in the VR scene and mark the corresponding locations in the vehicle virtual model;

[0018] Determine the cause of vehicle failure based on potential vehicle failures, locations of failures, and historical failure data;

[0019] Generate a fault solution based on the cause of the fault and present the fault solution to the user.

[0020] In one embodiment, the method further comprises:

[0021] When the user views the VR scene through the VR device, the user's query request is obtained; the query request is obtained according to the user's voice command or gesture command;

[0022] Perform semantic analysis on the query request, obtain the analysis result, and perform data query based on the analysis result.

[0023] In one embodiment, the step of performing data query according to the parsing result includes:

[0024] According to the analysis results, locate the location of the query data in the VR scene;

[0025] The corresponding query data is displayed to users through VR scenes.

[0026] In a second aspect, the present application also provides a vehicle fault diagnosis device, comprising:

[0027] The data acquisition module is used to acquire the real-time data of the whole vehicle and obtain key feature data based on the real-time data of the whole vehicle; the real-time data of the whole vehicle includes contact data and non-contact data; the contact data is collected by sensors, and the contact data is received from the cloud through wireless communication technology;

[0028] The model building module is used to build a 3D virtual model in the VR scene and map the real-time data of the whole vehicle to the VR scene to simulate the movement state of the vehicle in the VR scene; the 3D virtual model includes a vehicle virtual model and an environment virtual model;

[0029] The fault diagnosis module is used to obtain potential vehicle faults reported by users when the users are viewing VR scenes through VR devices, and to perform fault diagnosis on the vehicle based on the potential vehicle faults.

[0030] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements any one of the method steps in the first aspect when executing the computer program.

[0031] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements any one of the method steps in the first aspect when the computer program is executed by a processor.

[0032] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which implements any one of the method steps in the first aspect when executed by a processor.

[0033] The above-mentioned vehicle fault diagnosis method, device, computer equipment, computer-readable storage medium and computer program product obtain real-time data of the whole vehicle and obtain key feature data based on the real-time data of the whole vehicle, establish a 3D virtual model in the VR scene, and map the real-time data of the whole vehicle to the VR scene to simulate the movement state of the vehicle in the VR scene. When the user views the VR scene through the VR device, the potential vehicle faults reported by the user are obtained, and the vehicle is diagnosed according to the potential vehicle faults. Various data and dynamic performances of the vehicle can be observed in real time in the virtual environment, so as to quickly locate and identify potential faults and improve the efficiency and accuracy of fault diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0035] FIG1 is an application environment diagram of a vehicle fault diagnosis method in one embodiment;

[0036] FIG2 is a schematic diagram of a flow chart of a vehicle fault diagnosis method in one embodiment;

[0037] FIG3 is a schematic flow chart of a vehicle fault diagnosis method in another embodiment;

[0038] FIG4 is a block diagram of a vehicle fault diagnosis device in one embodiment;

[0039] FIG. 5 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0041] The vehicle fault diagnosis method provided in the embodiment of the present application can be applied in the application environment shown in FIG. 1. The terminal 102 communicates with the cloud server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The terminal 102 is used to obtain the real-time data of the whole vehicle, and obtain the key feature data according to the real-time data of the whole vehicle, establish a 3D virtual model in the VR scene, and map the real-time data of the whole vehicle to the VR scene to simulate the motion state of the vehicle in the VR scene. In the process of the user viewing the VR scene through the VR device, the potential fault of the vehicle fed back by the user is obtained, and the vehicle is fault diagnosed according to the potential fault of the vehicle. The real-time data of the whole vehicle includes contact data and non-contact data; the contact data is collected by the sensor, and the contact data is received from the cloud 104 through wireless communication technology. The terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices, and the Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car devices, projection devices, etc. The portable wearable device may be a smart watch, a smart bracelet, a head mounted device, etc. The head mounted device may be a virtual reality (VR) device, an augmented reality (AR) device, smart glasses, etc. The cloud server 104 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0042] In an exemplary embodiment, as shown in FIG2 , a vehicle fault diagnosis method is provided, which is described by taking the method applied to the terminal 102 in FIG1 as an example, and includes the following steps 202 to 206. Among them:

[0043] S202: Acquire the real-time data of the whole vehicle, and acquire key characteristic data based on the real-time data of the whole vehicle; the real-time data of the whole vehicle includes contact data and non-contact data; the contact data is collected by sensors, and the contact data is received from the cloud through wireless communication technology.

[0044] Optionally, various sensors installed on the vehicle (such as speed sensors, acceleration sensors, temperature sensors, pressure sensors, etc.) can be used to collect physical quantities such as speed, acceleration, temperature, pressure, etc. during the operation of the vehicle in real time. These sensors are in direct contact with various vehicle systems (such as the engine, chassis, body, etc.) and can accurately capture changes in the vehicle's state. At the same time, data is received from the cloud or other remote systems through wireless communication technologies (such as GPS, Bluetooth, Wi-Fi, cellular networks, etc.), usually including vehicle location, navigation information, remote monitoring data, etc.

[0045] S204: Establishing a 3D virtual model in the VR scene, and mapping the real-time data of the whole vehicle to the VR scene, so as to simulate the motion state of the vehicle in the VR scene; the 3D virtual model includes a vehicle virtual model and an environment virtual model.

[0046] Optionally, in the 3D modeling software, a vehicle virtual model is established according to the actual size, shape and structure of the vehicle, and at the same time, an environmental virtual model is established according to the vehicle operating environment (such as roads, weather, traffic conditions, etc.). After that, the extracted real-time data of the whole vehicle is mapped with the 3D virtual model, and the data is dynamically bound through programming so that the virtual model can reflect the actual operating status of the vehicle in real time. The virtual scene is rendered using a rendering engine to generate realistic visual effects, and the virtual scene is made closer to the real environment by adjusting parameters such as lighting, material, and texture.

[0047] S206: While the user is viewing the VR scene through the VR device, a potential vehicle fault reported by the user is obtained, and a fault diagnosis is performed on the vehicle based on the potential vehicle fault.

[0048] Optionally, the user can view the vehicle's operating status in a virtual scene through VR devices (such as head-mounted displays, handles, etc.) and perform interactive operations (such as switching perspectives, observing details, etc.). The terminal captures the user's operating behavior and feedback information (such as voice commands, gesture recognition, etc.) through the VR device to understand the user's observation and judgment of potential vehicle faults. Afterwards, based on the potential fault information fed back by the user, combined with the real-time data of the whole vehicle and the status of the 3D virtual model, the fault diagnosis algorithm is used to analyze the vehicle fault. For example, by comparing the data difference between the normal state and the fault state, the fault type, location and cause are identified, and corresponding maintenance suggestions or solutions are given.

[0049] In the above vehicle fault diagnosis method, by acquiring real-time data of the whole vehicle and obtaining key feature data based on the real-time data of the whole vehicle, a 3D virtual model is established in the VR scene, and the real-time data of the whole vehicle is mapped to the VR scene to simulate the movement state of the vehicle in the VR scene. In the process of the user viewing the VR scene through the VR device, the potential vehicle faults reported by the user are obtained, and the vehicle fault diagnosis is performed based on the potential vehicle faults. The various data of the vehicle and its dynamic performance can be observed in real time in the virtual environment, so as to quickly locate and identify potential faults, thereby improving the efficiency and accuracy of fault diagnosis.

[0050] In an exemplary embodiment, the step of obtaining key feature data based on the real-time data of the whole vehicle includes: performing data cleaning on the real-time data of the whole vehicle to remove noise values, abnormal values ​​and redundant values ​​in the real-time data of the whole vehicle, and normalizing the cleaned data to obtain normalized data; extracting key feature data from the normalized data, and performing quality verification on the key feature data; if the quality verification passes, saving the key feature data to a database.

[0051] Optionally, data cleaning is an important step in data preprocessing, which can remove noise values, abnormal values ​​and redundant values ​​in the data to ensure the accuracy and reliability of the data. After that, the cleaned data is normalized and the data is scaled to fall into a small specific interval to eliminate the influence of different dimensions on data analysis. Furthermore, key feature data in the normalized data is extracted and the extracted key feature data is verified to further ensure the accuracy and reliability of the data.

[0052] In this embodiment, by preprocessing the real-time data of the whole vehicle and extracting key feature data, the data quality can be improved, the interference of erroneous data can be reduced, and a clean and accurate data basis can be provided for subsequent analysis, thereby improving the efficiency and accuracy of fault diagnosis.

[0053] In an exemplary embodiment, the real-time data of the whole vehicle includes instrument data and status data; the step of mapping the real-time data of the whole vehicle to the VR scene includes: mapping the instrument data to the dashboard of the vehicle virtual model; updating the vehicle virtual model according to the status data, and updating the environment virtual model according to the environment data.

[0054] Optionally, the real-time data of the whole vehicle includes instrument data and status data. When mapping the real-time data of the whole vehicle to the VR scene, it usually includes associating the real-time collected instrument data with the instrument panel component in the vehicle virtual model through a programming interface or data binding technology. When the instrument data changes, the corresponding display on the virtual instrument panel will also be updated in real time to reflect the actual status of the vehicle. At the same time, according to the environmental data, by adjusting the parameters in the virtual scene, the real environmental effect is simulated. When the environmental data changes, the environment in the virtual scene will also change accordingly to provide a more realistic driving experience.

[0055] In this embodiment, by mapping the instrument data, status data and environmental data to the vehicle virtual model and the environmental virtual model in real time, the instrument panel and status changes in the vehicle virtual model can be observed in real time, potential faults or abnormal conditions can be discovered in time, and preliminary diagnosis and analysis can be performed.

[0056] In an exemplary embodiment, the steps of diagnosing a vehicle fault based on a potential vehicle fault include: locating the occurrence site of the potential vehicle fault in a VR scene, and marking the corresponding occurrence site in a virtual model of the vehicle; determining the cause of the vehicle fault based on the potential vehicle fault, the occurrence site, and historical fault data; generating a fault solution based on the cause of the fault, and displaying the fault solution to the user.

[0057] Optionally, based on the potential vehicle failure reported by the user, the location of the problem can be accurately located in the VR scene, and the problem component can be highlighted in the VR scene by highlighting, flashing, etc. Afterwards, based on the vehicle's historical failure data, the cause of the vehicle failure is determined, and based on the cause of the failure, a targeted fault solution is formulated, and the immersive characteristics of VR technology are used to display the solution to the user in the VR scene in the form of animation, diagram or text description.

[0058] In this embodiment, by locating the occurrence site of potential vehicle faults in the VR scene, marking the corresponding occurrence site in the vehicle virtual model, and displaying the fault solution to the user, the user can intuitively understand the fault situation, cause and solution in the VR environment, thereby improving the efficiency of fault diagnosis and processing.

[0059] In an exemplary embodiment, the method further includes: obtaining a user's query request while the user is viewing a VR scene through a VR device; obtaining the query request according to the user's voice command or gesture command; semantically parsing the query request to obtain a parsing result, and performing data query based on the parsing result.

[0060] Optionally, the built-in voice recognition system of the VR device can convert the user's voice commands into text or command signals. At the same time, it can capture the user's hand movements through a camera or other sensors, and use image processing or machine learning algorithms to parse them, so as to identify the user's gesture commands, and perform semantic analysis on the received voice or gesture commands to understand the user's intentions and request content, and thus perform corresponding data query operations based on the results of the semantic analysis.

[0061] In this embodiment, voice and gesture commands are used to make the user's interaction with the VR environment more convenient, without relying on traditional physical controllers or keyboard input, thereby improving the efficiency of fault diagnosis and processing.

[0062] In an exemplary embodiment, the step of performing data query according to the analysis result includes: locating the location of the query data in the VR scene according to the analysis result; and displaying the corresponding query data to the user through the VR scene.

[0063] Optionally, based on the analysis results, the location of the query data is located in the VR scene, and the corresponding query data is displayed to the user through the VR scene. For example, when the query data is engine temperature data, the engine instrument is displayed to the user in the VR scene.

[0064] In this embodiment, by locating the location of the query data in the VR scene and displaying the corresponding query data to the user through the VR scene, the query data can be displayed more intuitively, improving the convenience of interaction between the user and the VR scene, thereby improving the efficiency of fault diagnosis and processing.

[0065] In an exemplary embodiment, as shown in FIG3 , a vehicle fault diagnosis method is provided, the method comprising the following steps:

[0066] Acquire the real-time data of the whole vehicle, perform data cleaning on the real-time data of the whole vehicle to remove noise values, abnormal values ​​and redundant values ​​in the real-time data of the whole vehicle, and normalize the data after data cleaning to obtain normalized data; extract key feature data from the normalized data, and perform quality verification on the key feature data; if the quality verification passes, save the key feature data to the database.

[0067] Among them, the real-time data of the whole vehicle includes contact data and contactless data; the contact data is collected through sensors, and the contact data is received from the cloud through wireless communication technology.

[0068] A 3D virtual model is established in a VR scene, and instrument data is mapped to the dashboard of the vehicle virtual model; the vehicle virtual model is updated according to the status data, and the environment virtual model is updated according to the environment data to simulate the movement state of the vehicle in the VR scene; the 3D virtual model includes a vehicle virtual model and an environment virtual model.

[0069] When users view VR scenes through VR devices, the system obtains potential vehicle faults reported by users, locates the occurrence sites of potential vehicle faults in the VR scene, and marks the corresponding occurrence sites in the vehicle virtual model; determines the cause of the vehicle fault based on the potential vehicle faults, occurrence sites, and historical fault data; generates a fault solution based on the cause of the fault, and displays the fault solution to the user.

[0070] When a user views a VR scene through a VR device, a query request of the user is obtained; the query request is obtained according to a voice command or a gesture command of the user; the query request is semantically parsed to obtain a parsing result, and the location of the query data is located in the VR scene according to the parsing result; and the corresponding query data is displayed to the user through the VR scene.

[0071] In this embodiment, by acquiring real-time data of the entire vehicle and obtaining key feature data based on the real-time data of the entire vehicle, a 3D virtual model is established in the VR scene, and the real-time data of the entire vehicle is mapped to the VR scene to simulate the movement state of the vehicle in the VR scene. In the process of the user viewing the VR scene through a VR device, the potential vehicle faults reported by the user are obtained, and the vehicle is diagnosed based on the potential vehicle faults. The various data of the vehicle and its dynamic performance can be observed in real time in a virtual environment, so as to quickly locate and identify potential faults, thereby improving the efficiency and accuracy of fault diagnosis.

[0072] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0073] Based on the same inventive concept, the embodiment of the present application also provides a vehicle fault diagnosis device for implementing the vehicle fault diagnosis method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more vehicle fault diagnosis device embodiments provided below can refer to the limitations of the vehicle fault diagnosis method above, and will not be repeated here.

[0074] In an exemplary embodiment, as shown in FIG4 , a vehicle fault diagnosis device is provided, comprising: a data acquisition module 10, a model building module 20 and a fault diagnosis module 30, wherein:

[0075] The data acquisition module 10 is used to acquire the real-time data of the whole vehicle and acquire key characteristic data based on the real-time data of the whole vehicle; the real-time data of the whole vehicle includes contact data and non-contact data; the contact data is collected by sensors, and the contact data is received from the cloud through wireless communication technology.

[0076] The model building module 20 is used to build a 3D virtual model in the VR scene and map the real-time data of the whole vehicle to the VR scene to simulate the movement state of the vehicle in the VR scene; the 3D virtual model includes a vehicle virtual model and an environment virtual model.

[0077] The fault diagnosis module 30 is used to obtain potential vehicle faults reported by users when the users view VR scenes through VR devices, and perform fault diagnosis on the vehicle according to the potential vehicle faults.

[0078] In an exemplary embodiment, the data acquisition module 10 is also used to perform data cleaning on the real-time data of the whole vehicle to remove noise values, abnormal values ​​and redundant values ​​in the real-time data of the whole vehicle, and normalize the data after data cleaning to obtain normalized data; extract key feature data in the normalized data, and perform quality verification on the key feature data; if the quality verification passes, the key feature data is saved to the database.

[0079] In an exemplary embodiment, the model building module 20 is further used to map the instrument data to the instrument panel of the vehicle virtual model; update the vehicle virtual model according to the status data, and update the environment virtual model according to the environment data.

[0080] In an exemplary embodiment, the fault diagnosis module 30 is also used to locate the occurrence site of potential vehicle faults in the VR scene and mark the corresponding occurrence site in the vehicle virtual model; determine the cause of the vehicle failure based on the potential vehicle faults, the occurrence site, and historical fault data; generate a fault solution based on the cause of the fault, and display the fault solution to the user.

[0081] In an exemplary embodiment, the fault diagnosis module 30 is also used to obtain a user's query request when the user views a VR scene through a VR device; the query request is obtained according to the user's voice command or gesture command; the query request is semantically parsed to obtain a parsing result, and data query is performed based on the parsing result.

[0082] In an exemplary embodiment, the fault diagnosis module 30 is also used to locate the location of the query data in the VR scene according to the analysis results; and display the corresponding query data to the user through the VR scene.

[0083] Each module in the above vehicle fault diagnosis device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0084] In an exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in FIG5. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a vehicle fault diagnosis method is implemented. The display unit of the computer device is used to form a visually visible picture, which may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0085] Those skilled in the art will understand that the structure shown in FIG. 5 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0086] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: obtaining real-time data of the whole vehicle, and obtaining key feature data based on the real-time data of the whole vehicle; the real-time data of the whole vehicle includes contact data and non-contact data; the contact data is collected by sensors, and the contact data is received from the cloud through wireless communication technology; a 3D virtual model is established in a VR scene, and the real-time data of the whole vehicle is mapped to the VR scene to simulate the movement state of the vehicle in the VR scene; the 3D virtual model includes a vehicle virtual model and an environment virtual model; in the process of a user viewing a VR scene through a VR device, potential vehicle faults reported by the user are obtained, and fault diagnosis of the vehicle is performed based on the potential vehicle faults.

[0087] In one embodiment, the processor executes a computer program that involves obtaining key feature data based on the real-time data of the whole vehicle, including: performing data cleaning on the real-time data of the whole vehicle to remove noise values, abnormal values ​​and redundant values ​​in the real-time data of the whole vehicle, and normalizing the cleaned data to obtain normalized data; extracting key feature data from the normalized data, and performing quality verification on the key feature data; and saving the key feature data to a database if the quality verification passes.

[0088] In one embodiment, the real-time data of the whole vehicle involved when the processor executes the computer program includes instrument data and status data; the real-time data of the whole vehicle is mapped to the VR scene, including: mapping the instrument data to the dashboard of the vehicle virtual model; updating the vehicle virtual model according to the status data, and updating the environment virtual model according to the environment data.

[0089] In one embodiment, the processor executes a computer program that involves diagnosing a vehicle fault based on potential vehicle faults, including: locating the location of the vehicle's potential fault in a VR scene, and marking the corresponding location in the vehicle virtual model; determining the cause of the vehicle's fault based on the vehicle's potential fault, the location, and historical fault data; generating a fault solution based on the cause of the fault, and displaying the fault solution to the user.

[0090] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining a user's query request while the user is viewing a VR scene through a VR device; obtaining the query request based on the user's voice command or gesture command; performing semantic parsing on the query request to obtain a parsing result, and performing data query based on the parsing result.

[0091] In one embodiment, the data query based on the analysis results involved in the processor executing the computer program includes: locating the location of the query data in the VR scene according to the analysis results; and displaying the corresponding query data to the user through the VR scene.

[0092] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: obtaining real-time data of the entire vehicle, and obtaining key feature data based on the real-time data of the entire vehicle; the real-time data of the entire vehicle includes contact data and non-contact data; the contact data is collected by sensors, and the contact data is received from the cloud through wireless communication technology; a 3D virtual model is established in a VR scene, and the real-time data of the entire vehicle is mapped to the VR scene to simulate the movement state of the vehicle in the VR scene; the 3D virtual model includes a vehicle virtual model and an environment virtual model; in the process of a user viewing a VR scene through a VR device, potential vehicle faults reported by the user are obtained, and fault diagnosis of the vehicle is performed based on the potential vehicle faults.

[0093] In one embodiment, the computer program executed by the processor involves obtaining key feature data based on the real-time data of the whole vehicle, including: performing data cleaning on the real-time data of the whole vehicle to remove noise values, abnormal values ​​and redundant values ​​in the real-time data of the whole vehicle, and normalizing the cleaned data to obtain normalized data; extracting key feature data from the normalized data, and performing quality verification on the key feature data; and saving the key feature data to a database if the quality verification passes.

[0094] In one embodiment, the real-time data of the entire vehicle involved when the computer program is executed by the processor includes instrument data and status data; the real-time data of the entire vehicle is mapped to the VR scene, including: mapping the instrument data to the dashboard of the vehicle virtual model; updating the vehicle virtual model according to the status data, and updating the environment virtual model according to the environment data.

[0095] In one embodiment, the computer program executed by the processor involves diagnosing a vehicle fault based on potential vehicle faults, including: locating the location of the potential vehicle fault in a VR scene, and marking the corresponding location in the vehicle virtual model; determining the cause of the vehicle fault based on the potential vehicle fault, the location, and historical fault data; generating a fault solution based on the cause of the fault, and displaying the fault solution to the user.

[0096] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the user views the VR scene through the VR device, the user's query request is obtained; the query request is obtained according to the user's voice command or gesture command; the query request is semantically parsed to obtain the parsing result, and data query is performed according to the parsing result.

[0097] In one embodiment, the computer program executed by the processor involves performing data query based on the analysis results, including: locating the location of the query data in the VR scene based on the analysis results; and displaying the corresponding query data to the user through the VR scene.

[0098] In one embodiment, a computer program product is provided, including a computer program, which implements the following steps when executed by a processor: obtaining real-time data of the entire vehicle, and obtaining key feature data based on the real-time data of the entire vehicle; the real-time data of the entire vehicle includes contact data and non-contact data; the contact data is collected by sensors, and the contact data is received from the cloud through wireless communication technology; a 3D virtual model is established in a VR scene, and the real-time data of the entire vehicle is mapped to the VR scene to simulate the movement state of the vehicle in the VR scene; the 3D virtual model includes a vehicle virtual model and an environment virtual model; in the process of a user viewing a VR scene through a VR device, potential vehicle faults reported by the user are obtained, and fault diagnosis of the vehicle is performed based on the potential vehicle faults.

[0099] In one embodiment, the computer program executed by the processor involves obtaining key feature data based on the real-time data of the whole vehicle, including: performing data cleaning on the real-time data of the whole vehicle to remove noise values, abnormal values ​​and redundant values ​​in the real-time data of the whole vehicle, and normalizing the cleaned data to obtain normalized data; extracting key feature data from the normalized data, and performing quality verification on the key feature data; and saving the key feature data to a database if the quality verification passes.

[0100] In one embodiment, the real-time data of the entire vehicle involved when the computer program is executed by the processor includes instrument data and status data; the real-time data of the entire vehicle is mapped to the VR scene, including: mapping the instrument data to the dashboard of the vehicle virtual model; updating the vehicle virtual model according to the status data, and updating the environment virtual model according to the environment data.

[0101] In one embodiment, the computer program executed by the processor involves diagnosing a vehicle fault based on potential vehicle faults, including: locating the location of the potential vehicle fault in a VR scene, and marking the corresponding location in the vehicle virtual model; determining the cause of the vehicle fault based on the potential vehicle fault, the location, and historical fault data; generating a fault solution based on the cause of the fault, and displaying the fault solution to the user.

[0102] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the user views the VR scene through the VR device, the user's query request is obtained; the query request is obtained according to the user's voice command or gesture command; the query request is semantically parsed to obtain the parsing result, and data query is performed according to the parsing result.

[0103] In one embodiment, the computer program executed by the processor involves performing data query based on the analysis results, including: locating the location of the query data in the VR scene based on the analysis results; and displaying the corresponding query data to the user through the VR scene.

[0104] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0105] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0106] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A vehicle fault diagnosis method, characterized in that: The method comprises: Acquire the real-time data of the whole vehicle, and acquire key characteristic data according to the real-time data of the whole vehicle; the real-time data of the whole vehicle includes contact data and contactless data; the contact data is collected by sensors, and the contact data is received from the cloud through wireless communication technology; Establishing a 3D virtual model in a VR scene, and mapping the real-time data of the whole vehicle to the VR scene, so as to simulate the motion state of the vehicle in the VR scene; the 3D virtual model includes a vehicle virtual model and an environment virtual model; When the user views the VR scene through the VR device, the potential vehicle fault reported by the user is obtained, and the vehicle is diagnosed based on the potential vehicle fault.

2. The method according to claim 1, characterized in that The step of acquiring key characteristic data according to the real-time data of the whole vehicle includes: Performing data cleaning on the real-time data of the whole vehicle to remove noise values, abnormal values ​​and redundant values ​​in the real-time data of the whole vehicle, and performing normalization processing on the cleaned data to obtain normalized data; Extracting key feature data from the normalized data, and performing quality verification on the key feature data; When the quality verification is passed, the key feature data is saved in the database.

3. The method according to claim 1, characterized in that The real-time data of the whole vehicle includes instrument data and status data; and mapping the real-time data of the whole vehicle to the VR scene includes: Mapping the instrument data onto the instrument panel of the virtual model of the vehicle; The vehicle virtual model is updated according to the state data, and the environment virtual model is updated according to the environment data.

4. The method according to claim 1, characterized in that: The performing fault diagnosis on the vehicle according to the potential fault of the vehicle includes: Locating the occurrence location of the potential fault of the vehicle in the VR scene, and marking the corresponding occurrence location in the virtual model of the vehicle; Determining the cause of the vehicle failure according to the potential vehicle failure, the occurrence location, and historical failure data; A fault solution is generated according to the cause of the fault, and the fault solution is displayed to the user.

5. The method according to claim 1, characterized in that The method further comprises: In the process of the user viewing the VR scene through the VR device, obtaining a query request of the user; the query request is obtained according to a voice command or a gesture command of the user; The query request is semantically parsed to obtain a parsing result, and data query is performed according to the parsing result.

6. The method according to claim 5, characterized in that The performing of data query according to the analysis result includes: According to the analysis result, locating the location of the query data in the VR scene; The corresponding query data is displayed to the user through the VR scene.

7. A vehicle fault diagnosis device, characterized in that: The device comprises: A data acquisition module is used to acquire real-time data of the whole vehicle, and to acquire key characteristic data according to the real-time data of the whole vehicle; the real-time data of the whole vehicle includes contact data and non-contact data; the contact data is collected by sensors, and the contact data is received from the cloud through wireless communication technology; A model building module, used to build a 3D virtual model in a VR scene, and map the real-time data of the whole vehicle to the VR scene, so as to simulate the motion state of the vehicle in the VR scene; the 3D virtual model includes a vehicle virtual model and an environment virtual model; The fault diagnosis module is used to obtain the potential vehicle fault reported by the user when the user views the VR scene through the VR device, and perform fault diagnosis on the vehicle according to the potential vehicle fault.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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