Vehicle fault detection method and device and computer equipment
The fault index information is obtained through vehicle fault detection methods and automatically sent to the remote diagnosis platform. The decision tree model is used to determine the fault level and diagnosis results, which solves the problem of low fault detection efficiency in the existing technology, and achieves efficient and without manual participation. Fault detection improves user experience.
Patent Information
- Application Number
- CN202411388003.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-30
- Publication Date
- 2025-01-17
AI Technical Summary
In the prior art, the vehicle fault detection efficiency is low, the user experience is poor, and the offline after-sales service store resources are limited, resulting in untimely fault detection.
Through vehicle fault detection methods, vehicle fault indicator information is obtained, fault level is determined, and information is sent to the remote diagnostic platform when the fault level is higher than the threshold. The decision tree model and the remote diagnostic platform are used to automatically determine the fault diagnosis results, so as to achieve no manual operation Participated in fault detection.
Improves fault detection efficiency, saves costs, avoids the need to drive vehicles to offline service stores, and improves user experience.
Smart Images
Figure CN119322504A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of vehicle detection technology, and in particular to a vehicle fault detection method, device and computer equipment. Background Art
[0002] With the development of automobile technology, automobiles have gradually become more popular. In order to provide better user experience and safer and faster after-sales service, automobile manufacturers have also configured offline after-sales service stores (for example, 4S stores).
[0003] Although offline after-sales service stores have the function of offline vehicle fault detection, most vehicles are far away from the stores, fault detection is not convenient, and offline store resources are limited, fault detection is not timely. Therefore, the existing system only relies on offline after-sales service stores for fault detection, and the fault detection efficiency is low, which seriously affects the user service experience. Summary of the invention
[0004] Based on this, it is necessary to provide a vehicle fault detection method, device and computer equipment that can improve the efficiency of vehicle fault detection in response to the above technical problems.
[0005] In a first aspect, the present application provides a vehicle fault detection method. The method comprises:
[0006] In response to the fault detection operation, obtaining vehicle fault index information of the target vehicle;
[0007] Determine the vehicle fault level of the target vehicle according to the vehicle fault index information;
[0008] When the vehicle fault level is higher than the fault level threshold, the vehicle fault index information is sent to the remote diagnosis platform, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information.
[0009] In one embodiment, in response to a fault detection operation, obtaining vehicle fault index information of a target vehicle includes:
[0010] In response to the periodically triggered fault detection operation, acquiring vehicle operation data of the target vehicle;
[0011] Based on the vehicle operation data, obtain vehicle fault codes and freeze frame data of the target vehicle;
[0012] The vehicle fault code and freeze frame data are used as vehicle fault indicator information of the target vehicle.
[0013] In one embodiment, in response to a fault detection operation, obtaining vehicle fault index information of a target vehicle includes:
[0014] In response to a fault detection operation actively triggered by a user, obtaining fault description information of the target vehicle from the user through a microphone;
[0015] The fault description information is used as vehicle fault indicator information of the target vehicle.
[0016] In one embodiment, determining the vehicle fault level of the target vehicle according to the vehicle fault index information includes:
[0017] Based on the decision tree model, according to the vehicle fault index information, determine the first fault type of the target vehicle;
[0018] A vehicle fault level of the target vehicle is determined based on the first fault type.
[0019] In one embodiment, sending vehicle fault indicator information to a remote diagnostic platform so that the remote diagnostic platform determines a first fault diagnosis result based on the vehicle fault indicator information includes:
[0020] Send vehicle fault indicator information and a first fault type to a remote diagnostic platform, so that the remote diagnostic platform determines a second fault type based on the vehicle fault indicator information, and when the first fault type is the same as the second fault type, determines a first fault diagnosis result and a first fault solution based on the second fault type.
[0021] In one embodiment, the method further comprises:
[0022] When the vehicle fault level is not higher than the fault level threshold, determining a second fault solution according to the first fault type through a local fault diagnosis model;
[0023] Execute the second fault solution, and after the second fault solution is executed, return to perform the fault detection operation.
[0024] In a second aspect, the present application also provides a vehicle fault detection device. The device comprises:
[0025] an acquisition module, for acquiring vehicle fault index information of a target vehicle in response to a fault detection operation;
[0026] A determination module, used to determine the vehicle fault level of the target vehicle according to the vehicle fault index information;
[0027] The sending module is used to send vehicle fault index information to a remote diagnosis platform when the vehicle fault level is higher than a fault level threshold, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information.
[0028] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:
[0029] In response to the fault detection operation, obtaining vehicle fault index information of the target vehicle;
[0030] Determine the vehicle fault level of the target vehicle according to the vehicle fault index information;
[0031] When the vehicle fault level is higher than the fault level threshold, the vehicle fault index information is sent to the remote diagnosis platform, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information.
[0032] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:
[0033] In response to the fault detection operation, obtaining vehicle fault index information of the target vehicle;
[0034] Determine the vehicle fault level of the target vehicle according to the vehicle fault index information;
[0035] When the vehicle fault level is higher than the fault level threshold, the vehicle fault index information is sent to the remote diagnosis platform, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information.
[0036] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:
[0037] In response to the fault detection operation, obtaining vehicle fault index information of the target vehicle;
[0038] Determine the vehicle fault level of the target vehicle according to the vehicle fault index information;
[0039] When the vehicle fault level is higher than the fault level threshold, the vehicle fault index information is sent to the remote diagnosis platform, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information.
[0040] The above-mentioned vehicle fault detection method, device and computer equipment obtain vehicle fault index information of the target vehicle in response to the fault detection operation. According to the vehicle fault index information, the vehicle fault level of the target vehicle is determined. When the vehicle fault level is higher than the fault level threshold, the vehicle fault index information is sent to the remote diagnosis platform so that the remote diagnosis platform determines the first fault diagnosis result based on the vehicle fault index information. In the present application, the vehicle fault index information of the target vehicle can be obtained by performing a fault detection operation, and the vehicle fault level can be determined based on the vehicle fault index information. When the vehicle fault level is higher than the fault level threshold, the remote diagnosis platform automatically determines the first fault diagnosis result based on the vehicle fault index information. This process does not require human participation, and there is no need to drive the target vehicle to an offline service store. It not only effectively saves the cost of fault detection, but also improves the efficiency of fault detection. BRIEF DESCRIPTION OF THE DRAWINGS
[0041] FIG1 is a diagram showing an application environment of a vehicle fault detection method provided by this embodiment;
[0042] FIG2 is a schematic diagram of a flow chart of a first vehicle fault detection method provided by this embodiment;
[0043] Figure 3 A schematic diagram of a flow chart for determining a vehicle fault level of a target vehicle provided in this embodiment;
[0044] Figure 4 A schematic diagram of a process for determining a first fault diagnosis result provided in this embodiment;
[0045] Figure 5 A schematic diagram of a process for determining a second fault solution provided in this embodiment;
[0046] Figure 6 A schematic diagram of a flow chart of a second vehicle fault detection method provided in this embodiment;
[0047] Figure 7 A structural block diagram of a vehicle fault detection device provided in this embodiment;
[0048] FIG8 is a diagram showing the internal structure of the computer device provided in this embodiment. DETAILED DESCRIPTION
[0049] 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.
[0050] The vehicle fault detection method provided in the embodiment of the present application can be executed by the vehicle, specifically, it can be executed by an on-board terminal configured on the vehicle or a controller on the vehicle. That is, the method can be applied in the application environment shown in Figure 1. Among them, taking the application to the on-board terminal as an example, the on-board terminal 102 obtains the vehicle fault index information of the target vehicle in response to the fault detection operation; and determines the vehicle fault level of the target vehicle based on the vehicle fault index information. When the vehicle fault level is higher than the fault level threshold, the on-board terminal 102 sends the vehicle fault index information to the remote diagnosis platform 104, and the remote diagnosis platform 104 determines the first fault diagnosis result based on the vehicle fault index information.
[0051] The remote diagnosis platform 104 may be implemented by an independent server or a server cluster consisting of multiple servers.
[0052] The vehicle-mounted terminal 102 refers to an electronic device on the target vehicle that is used to collect vehicle data, execute vehicle control instructions, communicate with the outside and provide driving assistance information. The vehicle-mounted terminal 102 of the present application also integrates the functions of the vehicle fault detection method of the present application.
[0053] In one embodiment, as shown in FIG2 , a vehicle fault detection method is provided, and the method is applied to the vehicle in FIG1 as an example for description, as shown in FIG2 , including the following steps:
[0054] S201, in response to a fault detection operation, obtaining vehicle fault index information of a target vehicle.
[0055] The target vehicle refers to the vehicle that needs to be fault-checked. The vehicle fault index information refers to the relevant index information used to determine whether the vehicle has a fault.
[0056] As an optional implementation of the embodiment of the present application, in response to a periodically triggered fault detection operation, the vehicle operation data of the target vehicle is obtained. Based on the vehicle operation data, the vehicle fault code and freeze frame data of the target vehicle are obtained. The vehicle fault code and freeze frame data are used as the vehicle fault indicator information of the target vehicle. Among them, the vehicle fault code refers to a code recorded by the electronic control unit (ECU, such as the engine control unit, the transmission control unit, etc.) of the target vehicle when a problem is detected in the vehicle system. These codes are usually composed of a group of letters and numbers, which represent the type and location of the detected fault. Freeze frame data refers to a data snapshot of the moment of vehicle failure recorded by the electronic control unit (ECU) of the target vehicle, which includes engine speed, throttle position, oxygen sensor, etc. Among them, periodic triggering in this embodiment means that the vehicle terminal regularly triggers the vehicle self-inspection operation according to a preset period.
[0057] As another optional implementation of the embodiment of the present application, in response to the fault detection operation actively triggered by the user, the fault description information of the user for the target vehicle is obtained through the microphone. The fault description information is used as the vehicle fault index information of the target vehicle. Specifically, in response to the fault detection operation actively triggered by the user, for example, actively triggered by voice, exemplary, "someone, start the fault self-check mode", actively trigger the fault detection control (for example, a button) to realize the active triggering of the fault detection operation. Specifically, in response to the fault detection operation actively triggered by the user, the fault description information of the user for the target vehicle is obtained through the microphone. The fault description information is analyzed and extracted through a natural language model (for example, an NLP model), and the target description information after analysis and extraction is used as the vehicle fault index information of the target vehicle. Users only need to describe their vehicle problems in natural language. Based on the natural language model, the target vehicle asks about the specific problems and usage of the vehicle during the dialogue and communication between the person and the vehicle machine, obtains the owner's subjective description of the vehicle fault, and asks the user about the existing fault phenomenon according to the fuzzy points in the reasoning process of the component; helps to collect detailed information of the fault phenomenon.
[0058] S202: Determine the vehicle fault level of the target vehicle according to the vehicle fault index information.
[0059] The vehicle fault level refers to the severity level of the vehicle fault. A higher fault level means a more serious vehicle fault.
[0060] As an optional implementation of the embodiment of the present application, the vehicle fault index information is input into a fault prediction model, and the fault prediction model determines the vehicle fault level of the target vehicle based on the vehicle fault index information.
[0061] As another optional implementation of the embodiment of the present application, the fault type of the target vehicle is determined according to the vehicle fault index information. The vehicle fault level of the target vehicle is determined according to the fault type and fault level list. The fault level list records the mapping relationship between the fault type and the vehicle fault level.
[0062] S203, when the vehicle fault level is higher than the fault level threshold, sending vehicle fault indicator information to the remote diagnosis platform, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault indicator information.
[0063] The first fault diagnosis result refers to the diagnosis result of the target vehicle determined by the remote diagnosis receipt based on the vehicle fault index information.
[0064] As an optional implementation of the embodiment of the present application, when the vehicle fault level is higher than the fault level threshold, a fault diagnosis request is sent to the remote diagnosis platform; wherein the fault diagnosis request carries the vehicle identification and vehicle fault index information of the target vehicle. The remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information. Specifically, the remote diagnosis platform determines the first fault diagnosis result based on the vehicle fault index information and the vehicle fault analysis model. Exemplarily, the vehicle fault index information is sent to the vehicle fault analysis model, and the first fault diagnosis result is determined by the vehicle fault analysis model. Among them, the vehicle fault analysis model adopts but is not limited to a neural network model. Among them, the first fault diagnosis result is vehicle fault information, and a second fault solution for the vehicle fault information. The third fault solution is used to instruct the user how to solve the fault of the target vehicle, such as instructing the user to repair the fault by himself, or to drive to an offline service store.
[0065] As another optional implementation of the embodiment of the present application, when the vehicle fault level is higher than the fault level threshold, the vehicle fault index information is sent to the remote diagnosis platform, so that the remote diagnosis platform initiates help from the expert team based on the vehicle fault index information, so that the expert team determines the first fault diagnosis result based on the vehicle fault index information. The expert team can be a network virtual function or a manual team.
[0066] The above-mentioned vehicle fault detection method obtains vehicle fault index information of the target vehicle in response to a fault detection operation. According to the vehicle fault index information, the vehicle fault level of the target vehicle is determined. When the vehicle fault level is higher than the fault level threshold, the vehicle fault index information is sent to the remote diagnosis platform so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information. In the present application, the vehicle fault index information of the target vehicle can be obtained by performing a fault detection operation, and the vehicle fault level can be determined based on the vehicle fault index information. When the vehicle fault level is higher than the fault level threshold, the remote diagnosis platform automatically determines the first fault diagnosis result based on the vehicle fault index information. This process does not require human participation, and there is no need to drive the target vehicle to an offline service store. It not only effectively saves the cost of fault detection, but also improves the efficiency of fault detection.
[0067] In one embodiment, in order to more accurately determine the vehicle fault level, such as Figure 3 As shown, an optional implementation of S202 includes:
[0068] S301, based on a decision tree model and according to vehicle fault index information, determining a first fault type of a target vehicle.
[0069] Among them, the decision tree model refers to a common machine learning algorithm, which is used for classification and regression tasks. The decision tree model in this embodiment can effectively classify and diagnose vehicle fault codes and freeze frames. Specifically, the decision tree model can automatically generate a series of decision rules and judgment criteria by analyzing and mining vehicle freeze frame data and vehicle fault codes, thereby realizing the classification and diagnosis of vehicle fault codes and freeze frame data. In the decision tree model, each internal node represents an attribute or feature, each branch represents a value, and each leaf node corresponds to a classification result. By recursively dividing the training data set into multiple subsets and building a decision tree on each subset, a complete decision tree model can be generated in the end. The first fault type refers to the fault information of the target vehicle determined by the decision tree model based on the vehicle fault indicator information.
[0070] Optionally, in this embodiment, the vehicle fault index information is input into a trained decision tree model, and the decision tree model classifies the vehicle fault of the target vehicle based on the vehicle fault index information, thereby determining the first fault type of the target vehicle.
[0071] S302: Determine a vehicle fault level of the target vehicle according to the first fault type.
[0072] Optionally, in this embodiment, the vehicle fault level of the target vehicle may be determined according to the first fault type and the fault list, wherein the fault list records a mapping relationship between the fault type and the vehicle fault level.
[0073] In this embodiment, based on the decision tree model, the first fault type of the target vehicle is determined according to the vehicle fault index information. According to the first fault type, the vehicle fault level of the target vehicle can be determined more accurately.
[0074] Based on the above embodiments, Figure 4 As shown, the optional implementation of sending the vehicle fault index information to the remote diagnosis platform in S203 so that the remote diagnosis platform determines the first fault diagnosis result based on the vehicle fault index information includes:
[0075] S401, sending vehicle fault indicator information and a first fault type to a remote diagnostic platform, so that the remote diagnostic platform determines a second fault type based on the vehicle fault indicator information, and when the first fault type is the same as the second fault type, determines a first fault diagnosis result and a first fault solution based on the second fault type.
[0076] Optionally, in this embodiment, the fault indicator information and the first fault type are sent to the remote diagnosis platform, and the remote diagnosis platform determines the second fault type based on the fault indicator information and the fault analysis model, and when the first fault type is the same as the second fault type, determines the first fault diagnosis result and the first fault solution based on the second fault type. Specifically, the fault indicator information is input into the fault analysis model, and the second fault type is determined by the fault analysis model.
[0077] Optionally, in this embodiment, when the first fault type and the second fault type are different, the first fault type, the second fault type and the fault indicator information are sent to the advanced diagnostic model, and the advanced diagnostic model determines the third fault type based on the first fault type, the second fault type and the fault indicator information. If the third fault type is the same as the first fault type, the first fault solution is determined based on the first fault type. If the third fault type is the same as the second fault type, the first fault solution is determined based on the second fault type.
[0078] In one embodiment, if Figure 5 As shown, an optional implementation method of vehicle fault detection includes:
[0079] S501, when the vehicle fault level is not higher than the fault level threshold, determine a second fault solution according to the first fault type through a local fault diagnosis model.
[0080] The local fault diagnosis model refers to a fault diagnosis model installed in the vehicle terminal. The second fault solution refers to a solution for modifying the first fault type corresponding to the first fault type.
[0081] Optionally, in this embodiment, when the vehicle fault level is not higher than the fault level threshold, the first fault type is input into the local fault diagnosis model, and the second fault solution is determined by the local fault diagnosis model.
[0082] S502, executing a second fault solution, and after the second fault solution is executed, returning to perform a fault detection operation.
[0083] Optionally, in this embodiment, the vehicle-mounted terminal automatically executes the second fault solution, and after the second fault solution is executed, controls the vehicle to return to perform the fault detection operation.
[0084] In this embodiment, when the vehicle fault level is not higher than the fault level threshold, the second fault solution is determined according to the first fault type through the local fault diagnosis model. The second fault solution is executed, and after the second fault solution is executed, the fault detection operation is returned to be executed, which not only improves the fault detection efficiency and the fault repair efficiency, but also detects the repair effect by returning to execute the fault detection operation.
[0085] In one embodiment, if Figure 6 As shown, an optional implementation of the vehicle fault detection method is:
[0086] S601, in response to a periodically triggered fault detection operation, obtaining vehicle operation data of a target vehicle.
[0087] S602, based on the vehicle operation data, obtaining the vehicle fault code and freeze frame data of the target vehicle.
[0088] S603, using the vehicle fault code and the freeze frame data as vehicle fault index information of the target vehicle.
[0089] S604, based on the decision tree model and according to the vehicle fault index information, determining a first fault type of the target vehicle.
[0090] S605: Determine a vehicle fault level of the target vehicle according to the first fault type.
[0091] S606: When the vehicle fault level is not higher than the fault level threshold, determine a second fault solution according to the first fault type through a local fault diagnosis model.
[0092] S607, executing the second fault solution, and after the second fault solution is executed, returning to perform the fault detection operation.
[0093] S608, when the vehicle fault level is higher than the fault level threshold, sending vehicle fault indicator information to the remote diagnosis platform, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault indicator information.
[0094] In this embodiment, in response to a fault detection operation, vehicle fault index information of the target vehicle is obtained. Based on the vehicle fault index information, the vehicle fault level of the target vehicle is determined. When the vehicle fault level is higher than the fault level threshold, the vehicle fault index information is sent to the remote diagnostic platform so that the remote diagnostic platform determines a first fault diagnosis result based on the vehicle fault index information. In the present application, the vehicle fault index information of the target vehicle can be obtained by performing a fault detection operation, and the vehicle fault level can be determined based on the vehicle fault index information. When the vehicle fault level is higher than the fault level threshold, the remote diagnostic platform automatically determines the first fault diagnosis result based on the vehicle fault index information. This process does not require human participation, and there is no need to drive the target vehicle to an offline service store. This not only effectively saves the cost of fault detection, but also improves the efficiency of fault detection.
[0095] Based on the same inventive concept, the embodiment of the present application also provides a vehicle fault detection device for implementing the vehicle fault detection 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 the embodiment of a vehicle fault detection device provided below can refer to the limitations of the vehicle fault detection method above, and will not be repeated here.
[0096] In one embodiment, if Figure 7 As shown, a vehicle fault detection device 1 is provided, comprising:
[0097] An acquisition module 10, for acquiring vehicle fault index information of a target vehicle in response to a fault detection operation;
[0098] A determination module 20, for determining a vehicle fault level of a target vehicle according to the vehicle fault index information;
[0099] The sending module 30 is used to send vehicle fault index information to the remote diagnosis platform when the vehicle fault level is higher than the fault level threshold, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information.
[0100] In one embodiment, the Figure 7 The acquisition module 10 is also specifically used for:
[0101] In response to the periodically triggered fault detection operation, acquiring vehicle operation data of the target vehicle;
[0102] Based on the vehicle operation data, obtain vehicle fault codes and freeze frame data of the target vehicle;
[0103] The vehicle fault code and freeze frame data are used as vehicle fault indicator information of the target vehicle.
[0104] In one embodiment, the Figure 7 The acquisition module 10 is also specifically used for:
[0105] In response to a fault detection operation actively triggered by a user, obtaining fault description information of the target vehicle from the user through a microphone;
[0106] The fault description information is used as vehicle fault indicator information of the target vehicle.
[0107] In one embodiment, the Figure 7 The determination module 20 is also specifically used for:
[0108] Based on the decision tree model, according to the vehicle fault index information, determine the first fault type of the target vehicle;
[0109] A vehicle fault level of the target vehicle is determined based on the first fault type.
[0110] In one embodiment, the Figure 7 The sending module 30 is also specifically used for:
[0111] Send vehicle fault indicator information and a first fault type to a remote diagnostic platform, so that the remote diagnostic platform determines a second fault type based on the vehicle fault indicator information, and when the first fault type is the same as the second fault type, determines a first fault diagnosis result and a first fault solution based on the second fault type.
[0112] In one embodiment, a vehicle fault detection device 1 further includes:
[0113] A diagnostic model, for determining a second fault solution according to the first fault type by using a local fault diagnostic model when the fault level of the vehicle is not higher than a fault level threshold;
[0114] The execution module is used to execute the second fault solution and return to execute the fault detection operation after the second fault solution is executed.
[0115] Each module in the above vehicle fault detection 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.
[0116] In one embodiment, a computer device is provided, and its internal structure diagram can be shown in FIG8. 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 through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through 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 can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a vehicle fault detection method is implemented. The display unit of the computer device is used to form a visually visible picture, which can 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.
[0117] Those skilled in the art will understand that the structure shown in FIG. 8 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.
[0118] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:
[0119] In response to the fault detection operation, obtaining vehicle fault index information of the target vehicle;
[0120] Determine the vehicle fault level of the target vehicle according to the vehicle fault index information;
[0121] When the vehicle fault level is higher than the fault level threshold, the vehicle fault index information is sent to the remote diagnosis platform, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information.
[0122] In one embodiment, when the processor executes the computer program, the following steps are further implemented: in response to the fault detection operation, obtaining vehicle fault index information of the target vehicle, including:
[0123] In response to the periodically triggered fault detection operation, acquiring vehicle operation data of the target vehicle;
[0124] Based on the vehicle operation data, obtain vehicle fault codes and freeze frame data of the target vehicle;
[0125] The vehicle fault code and freeze frame data are used as vehicle fault indicator information of the target vehicle.
[0126] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:
[0127] In response to a fault detection operation actively triggered by a user, obtaining fault description information of the target vehicle from the user through a microphone;
[0128] The fault description information is used as vehicle fault indicator information of the target vehicle.
[0129] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:
[0130] Based on the decision tree model, according to the vehicle fault index information, determine the first fault type of the target vehicle;
[0131] A vehicle fault level of the target vehicle is determined based on the first fault type.
[0132] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:
[0133] Send vehicle fault indicator information and a first fault type to a remote diagnostic platform, so that the remote diagnostic platform determines a second fault type based on the vehicle fault indicator information, and when the first fault type is the same as the second fault type, determines a first fault diagnosis result and a first fault solution based on the second fault type.
[0134] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:
[0135] When the vehicle fault level is not higher than the fault level threshold, determining a second fault solution according to the first fault type through a local fault diagnosis model;
[0136] Execute the second fault solution, and after the second fault solution is executed, return to perform the fault detection operation.
[0137] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:
[0138] In response to the fault detection operation, obtaining vehicle fault index information of the target vehicle;
[0139] Determine the vehicle fault level of the target vehicle according to the vehicle fault index information;
[0140] When the vehicle fault level is higher than the fault level threshold, the vehicle fault index information is sent to the remote diagnosis platform, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information.
[0141] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: in response to the fault detection operation, obtaining vehicle fault index information of the target vehicle, including:
[0142] In response to the periodically triggered fault detection operation, acquiring vehicle operation data of the target vehicle;
[0143] Based on the vehicle operation data, obtain vehicle fault codes and freeze frame data of the target vehicle;
[0144] The vehicle fault code and freeze frame data are used as vehicle fault indicator information of the target vehicle.
[0145] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0146] In response to a fault detection operation actively triggered by a user, obtaining fault description information of the target vehicle from the user through a microphone;
[0147] The fault description information is used as vehicle fault indicator information of the target vehicle.
[0148] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining the vehicle fault level of the target vehicle according to the vehicle fault index information, including:
[0149] Based on the decision tree model, according to the vehicle fault index information, determine the first fault type of the target vehicle;
[0150] A vehicle fault level of the target vehicle is determined based on the first fault type.
[0151] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: sending vehicle fault index information to the remote diagnosis platform so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information, including:
[0152] Send vehicle fault indicator information and a first fault type to a remote diagnostic platform, so that the remote diagnostic platform determines a second fault type based on the vehicle fault indicator information, and when the first fault type is the same as the second fault type, determines a first fault diagnosis result and a first fault solution based on the second fault type.
[0153] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0154] When the vehicle fault level is not higher than the fault level threshold, determining a second fault solution according to the first fault type through a local fault diagnosis model;
[0155] Execute the second fault solution, and after the second fault solution is executed, return to perform the fault detection operation.
[0156] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:
[0157] In response to the fault detection operation, obtaining vehicle fault index information of the target vehicle;
[0158] Determine the vehicle fault level of the target vehicle according to the vehicle fault index information;
[0159] When the vehicle fault level is higher than the fault level threshold, the vehicle fault index information is sent to the remote diagnosis platform, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information.
[0160] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: in response to the fault detection operation, obtaining vehicle fault index information of the target vehicle, including:
[0161] In response to the periodically triggered fault detection operation, acquiring vehicle operation data of the target vehicle;
[0162] Based on the vehicle operation data, obtain vehicle fault codes and freeze frame data of the target vehicle;
[0163] The vehicle fault code and freeze frame data are used as vehicle fault indicator information of the target vehicle.
[0164] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: in response to the fault detection operation, obtaining vehicle fault index information of the target vehicle, including:
[0165] In response to a fault detection operation actively triggered by a user, obtaining fault description information of the target vehicle from the user through a microphone;
[0166] The fault description information is used as vehicle fault indicator information of the target vehicle.
[0167] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining the vehicle fault level of the target vehicle according to the vehicle fault index information, including:
[0168] Based on the decision tree model, according to the vehicle fault index information, determine the first fault type of the target vehicle;
[0169] A vehicle fault level of the target vehicle is determined based on the first fault type.
[0170] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: sending vehicle fault index information to the remote diagnosis platform so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information, including:
[0171] Send vehicle fault indicator information and a first fault type to a remote diagnostic platform, so that the remote diagnostic platform determines a second fault type based on the vehicle fault indicator information, and when the first fault type is the same as the second fault type, determines a first fault diagnosis result and a first fault solution based on the second fault type.
[0172] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0173] When the vehicle fault level is not higher than the fault level threshold, determining a second fault solution according to the first fault type through a local fault diagnosis model;
[0174] Execute the second fault solution, and after the second fault solution is executed, return to perform the fault detection operation.
[0175] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods 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 this application can include at least one of non-volatile 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), magnetoresistive 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, etc., but are not limited to this.
[0176] 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 specification.
[0177] 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 detection method, characterized in that: The method comprises: In response to the fault detection operation, obtaining vehicle fault index information of the target vehicle; Determining a vehicle fault level of the target vehicle according to the vehicle fault index information; In a case where the vehicle fault level is higher than a fault level threshold, the vehicle fault index information is sent to a remote diagnosis platform, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information.
2. The method according to claim 1, characterized in that The step of obtaining vehicle fault index information of the target vehicle in response to the fault detection operation includes: In response to the periodically triggered fault detection operation, acquiring vehicle operation data of the target vehicle; Based on the vehicle operation data, obtaining vehicle fault codes and freeze frame data of the target vehicle; The vehicle fault code and the freeze frame data are used as vehicle fault index information of the target vehicle.
3. The method according to claim 1, characterized in that The step of obtaining vehicle fault index information of the target vehicle in response to the fault detection operation includes: In response to a fault detection operation actively triggered by a user, obtaining fault description information of the user for the target vehicle through a microphone; The fault description information is used as vehicle fault index information of the target vehicle.
4. The method according to claim 1, characterized in that Determining the vehicle fault level of the target vehicle according to the vehicle fault index information includes: Based on the decision tree model, determining the first fault type of the target vehicle according to the vehicle fault index information; A vehicle fault level of the target vehicle is determined according to the first fault type.
5. The method according to claim 4, characterized in that The sending the vehicle fault index information to the remote diagnosis platform so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information includes: The vehicle fault indicator information and the first fault type are sent to a remote diagnostic platform, so that the remote diagnostic platform determines a second fault type based on the vehicle fault indicator information, and when the first fault type is the same as the second fault type, determines the first fault diagnosis result and a first fault solution based on the second fault type.
6. The method according to claim 4, characterized in that The method further comprises: In a case where the vehicle fault level is not higher than a fault level threshold, determining a second fault solution according to the first fault type through a local fault diagnosis model; Execute the second fault solution, and after the second fault solution is executed, return to perform the fault detection operation.
7. A vehicle fault detection device, characterized in that: The device comprises: an acquisition module, for acquiring vehicle fault index information of a target vehicle in response to a fault detection operation; A determination module, used to determine the vehicle fault level of the target vehicle according to the vehicle fault index information; The sending module is used to send the vehicle fault index information to the remote diagnosis platform when the vehicle fault level is higher than the fault level threshold, so that the remote diagnosis platform determines a first fault diagnosis result based on the vehicle fault index information.
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 vehicle fault detection 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 vehicle fault detection 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 vehicle fault detection method according to any one of claims 1 to 6 are implemented.