A diagnostic processing method, system, apparatus and electronic device

Abstract

The application discloses a diagnosis processing method, system, device and electronic equipment. After receiving a vehicle diagnosis request, a center node generates a fault analysis instruction, sends the fault analysis instruction to a first edge node, so that the first edge node performs fault analysis on a target vehicle based on a fault analysis model, obtains a fault analysis result, and sends the fault analysis result to the center node. The center node determines a target repair scheme matched with a fault change condition contained in the fault analysis result, and sends the target repair scheme to the first edge node, so that the target vehicle is repaired based on the target repair scheme. In this way, through the interaction between the edge node and the center node, the data transmission amount between the edge node and the center node is reduced, the fault analysis on the vehicle is realized on the edge node, the center node performs verification and determines a repair scheme, thereby avoiding the problem that the diagnosis timeliness is poor due to the transmission delay of vehicle monitoring data, and the diagnosis efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and more particularly to a diagnostic processing method, system, device, and electronic device. Background Technology

[0002] The current method for remote vehicle fault diagnosis is to remotely transmit various monitoring data, including those related to the engine, chassis, body and accessories, exhaust, and noise, during the actual operation of the vehicle to a data processing center for fault diagnosis and remote fault elimination. When the fault cannot be eliminated, the owner will be promptly alerted to the fault.

[0003] However, the diagnostic efficiency of remote fault diagnosis is limited by the rate at which real-time vehicle monitoring data is transmitted to the remote data processing center. When the capacity of vehicle monitoring data exceeds the maximum transmission capacity of the current network transmission rate, there will be transmission delay, affecting the timeliness of vehicle diagnosis.

[0004] Therefore, existing remote fault diagnosis methods for vehicles suffer from poor timeliness. Summary of the Invention

[0005] This application provides a diagnostic processing method, system, device, electronic device, and storage medium. Through the interaction between edge nodes and central nodes, the amount of data transmission between edge nodes and central nodes is reduced. This enables vehicle fault analysis to be performed on the edge nodes, while the central node performs verification and determines the repair plan. This avoids the problem of poor diagnostic timeliness caused by the transmission delay of vehicle monitoring data, thereby improving diagnostic efficiency.

[0006] This application provides a diagnostic processing method applied to a central node of a diagnostic processing system. The diagnostic processing system further includes multiple edge nodes connected to the central node. The central node manages each edge node, and each edge node corresponds to a vehicle for performing diagnostic control on the corresponding vehicle. The method includes:

[0007] Receive vehicle diagnostic requests for the target vehicle at the first edge node; Based on the vehicle diagnostic request, generate a fault analysis instruction for the target vehicle; The fault analysis command is sent to the first edge node so that, upon receiving the fault analysis command, the first edge node performs fault analysis on the target vehicle using the fault analysis model configured on the first edge node, obtains fault analysis results for the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node. After receiving the fault analysis results from the first edge node, a target maintenance plan that matches the fault changes contained in the fault analysis results is determined; The target repair plan is sent to the first edge node so that the abnormal parts in the target vehicle can be repaired based on the target repair plan.

[0008] Accordingly, this application provides a diagnostic processing system, which includes a central node and a plurality of edge nodes connected to the central node. The central node manages each edge node, and each edge node corresponds to a vehicle for performing diagnostic control of the corresponding vehicle. The central node receives a vehicle diagnostic request for the target vehicle of the first edge node; based on the vehicle diagnostic request, it generates a fault analysis instruction for the target vehicle and sends the fault analysis instruction to the first edge node. Upon receiving the fault analysis instruction, the first edge node performs fault analysis on the target vehicle using the fault analysis model configured on the first edge node, obtains fault analysis results for the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node. After receiving the fault analysis results from the first edge node, the central node determines a target maintenance plan that matches the fault changes contained in the fault analysis results. The central node sends the target repair plan to the first edge node so that the abnormal parts in the target vehicle can be repaired based on the target repair plan.

[0009] Accordingly, this application provides a diagnostic processing device applied to the central node of a diagnostic processing system. The diagnostic processing system further includes multiple edge nodes connected to the central node. The central node manages each edge node, and each edge node corresponds to a vehicle for performing diagnostic control of the corresponding vehicle. The device includes: The first receiving module is used to receive vehicle diagnostic requests for the target vehicle of the first edge node. The instruction generation module is used to generate fault analysis instructions for the target vehicle based on the vehicle diagnostic request. The instruction sending module is used to send the fault analysis instruction to the first edge node, so that when the first edge node receives the fault analysis instruction, it performs fault analysis on the target vehicle through the fault analysis model configured on the first edge node, obtains fault analysis results for the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node. The second receiving module is used to receive the fault analysis results from the first edge node and then determine a target maintenance plan that matches the fault changes contained in the fault analysis results. The repair module is used to send the target repair plan to the first edge node so as to repair the abnormal parts in the target vehicle based on the target repair plan.

[0010] Furthermore, this application also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the diagnostic processing method provided in this application.

[0011] Furthermore, this application embodiment also provides a storage medium storing a computer program. When the computer program is run on an electronic device, the computer program is used to cause the electronic device to execute any of the diagnostic processing methods provided in this application embodiment.

[0012] Furthermore, embodiments of this application also provide a computer program product, including a computer program or instructions, which, when executed by a processor, implement any of the diagnostic processing methods provided in embodiments of this application.

[0013] In this embodiment, a central node receives a vehicle diagnostic request for a target vehicle at a first edge node. Based on the vehicle diagnostic request, a fault analysis instruction for the target vehicle is generated. The fault analysis instruction is sent to the first edge node, enabling it to perform fault analysis on the target vehicle using its configured fault analysis model. The result shows the fault changes in abnormal components within the target vehicle, and the result is sent to the central node. Upon receiving the fault analysis result from the first edge node, a target repair plan matching the fault changes in the result is determined. The target repair plan is then sent to the first edge node for repair of the abnormal components in the target vehicle. This interaction between the edge and central nodes reduces data transmission volume, enabling fault analysis at the edge node and verification and repair plan determination at the central node. This avoids the problem of poor diagnostic timeliness due to transmission delays in vehicle monitoring data, thereby improving diagnostic efficiency. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] To gain a more complete understanding of this application and its beneficial effects, the following description will be provided in conjunction with the accompanying drawings, wherein the same reference numerals in the following description denote the same parts.

[0016] Figure 1 This is a schematic diagram of an implementation scenario provided in the embodiments of this application; Figure 2 This is a schematic flowchart of the diagnostic processing method provided in the embodiments of this application; Figure 3 This is a schematic diagram of the architecture of the diagnostic processing system provided in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of the diagnostic processing device provided in the embodiments of this application; Figure 5 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] Furthermore, in the embodiments of this application, "multiple" refers to two or more. The terms "first" and "second," etc., in the embodiments of this application are used for distinguishing descriptions and should not be construed as implying relative importance.

[0019] Research indicates that current vehicle diagnostic methods primarily utilize the self-diagnostic function of the vehicle's Electronic Control Unit (ECU) for fault diagnosis. This involves monitoring circuits to track various operating parameters of the vehicle's sensors, actuators, and microprocessors, comparing these parameters with pre-stored standard data. Based on the comparison results, a fault is determined. When operating parameters exceed the range of the standard data, a corresponding device is identified as faulty. The system then uses a pre-stored fault code table to locate the corresponding fault code and issue a warning.

[0020] Existing diagnostic methods can only identify fixed faults based on pre-set fault code tables and static fault code diagnostic conditions. For mechanical structural damage, new or unknown faults such as intermittent poor wiring connections—fault types not defined in the fault code table—accurate detection and diagnosis are difficult, easily leading to false alarms and missed alarms. Remote fault diagnosis, on the other hand, remotely transmits various vehicle monitoring data, including those from the engine, chassis, body and accessories, exhaust, and noise, to a data processing center for fault diagnosis and remote fault elimination. When faults cannot be eliminated, the owner is promptly alerted for a fault warning.

[0021] The speed of remote fault diagnosis is limited by the rate at which vehicle monitoring data is transmitted to the remote data processing center (including network transmission rate and vehicle monitoring data capacity). In actual fault diagnosis, it is often necessary to transmit historical operating data for a certain period of time as a reference sample to determine the time node and trend of the fault. If only data at a certain moment of the fault is transmitted for fault diagnosis, it is not easy to accurately grasp the time node of the fault. When the vehicle monitoring data capacity and the network transmission rate cannot be matched, that is, when the vehicle monitoring data capacity exceeds the maximum transmission capacity of the current network transmission rate, there will be transmission delay, affecting the timeliness of vehicle diagnosis.

[0022] To address at least some of the aforementioned problems, embodiments of this application provide a diagnostic processing method, system, apparatus, electronic device, storage medium, and computer program product.

[0023] Specifically, this embodiment will be described from the perspective of a diagnostic processing device, which can be integrated into an electronic device, meaning that the diagnostic processing method of this application embodiment can be executed by an electronic device. This electronic device can be a server for a diagnostic device, or a terminal device such as a diagnostic device.

[0024] The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, network acceleration services (Content Delivery Network, CDN), as well as big data and artificial intelligence platforms.

[0025] The terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and the server can be connected directly or indirectly through wired or wireless communication, which is not limited herein.

[0026] Please see Figure 1Taking the integration of diagnostic processing devices into electronic devices as an example, Figure 1 This is a schematic diagram illustrating an implementation scenario of the diagnostic processing method provided in this application. The electronic device can be a terminal device. It receives a vehicle diagnostic request for a target vehicle from a first edge node via a central node; generates a fault analysis command for the target vehicle based on the vehicle diagnostic request; sends the fault analysis command to the first edge node, enabling the first edge node to perform fault analysis on the target vehicle using its configured fault analysis model, obtaining fault analysis results on the fault changes of abnormal components in the target vehicle, and sending the fault analysis results to the central node; after receiving the fault analysis results from the first edge node, it determines a target repair plan that matches the fault changes contained in the fault analysis results; and sends the target repair plan to the first edge node so that the abnormal components in the target vehicle can be repaired based on the target repair plan. Thus, through the interaction between the edge node and the central node, the amount of data transmission between them is reduced, enabling vehicle fault analysis at the edge node, verification and repair plan determination at the central node, thereby avoiding the problem of poor diagnostic timeliness due to transmission delays in vehicle monitoring data and improving diagnostic efficiency.

[0027] It should be noted that, Figure 1 The illustrated scenario of the diagnostic processing method is merely an example. The implementation environment of the diagnostic processing method described in this application is for the purpose of more clearly illustrating the technical solution of this application and does not constitute a limitation on the technical solution provided in this application. Those skilled in the art will understand that with the evolution of diagnostic processing and the emergence of new business scenarios, the technical solution provided in this application is also applicable to similar technical problems. The solution provided in this application is specifically illustrated through the following embodiments. It should be noted that the order of description of the following embodiments is not intended to limit the preferred order of the embodiments.

[0028] This embodiment will be described from the perspective of a diagnostic processing device, which can be integrated into an electronic device, which can be a terminal device and / or a server, and this application does not impose any limitations on it.

[0029] This application provides a diagnostic processing method applied to the central node of a diagnostic processing system. The diagnostic processing system also includes multiple edge nodes connected to the central node. The central node is used to manage each edge node, and each edge node corresponds to a vehicle for performing diagnostic control of the corresponding vehicle.

[0030] The diagnostic processing system refers to a data transmission architecture consisting of a central node and multiple edge nodes, which is used to perform diagnostic processing on the vehicles corresponding to each edge node.

[0031] In this context, the central node refers to the remote data processing center within the diagnostic processing system. In existing technologies, this remote data processing center receives vehicle monitoring data from each vehicle to perform diagnostic control (including fault diagnosis and remote fault elimination) based on the vehicle monitoring data. However, in this application, the central node does not directly receive vehicle monitoring data from each vehicle; instead, it controls edge nodes to perform fault diagnosis and remote fault elimination on the vehicles based on the vehicle monitoring data it acquires.

[0032] In this context, an edge node refers to a node used for vehicle diagnostics and control. An edge node can correspond to a single vehicle or a type of vehicle. For example, each vehicle's On-Board Diagnostics (OBD) system can be used as an edge node connected to the diagnostic processing system. Alternatively, on-board diagnostic systems belonging to the same type of vehicle can also be used as the same edge node connected to the diagnostic processing system.

[0033] Specifically, please refer to Figure 2 , Figure 2 This is a flowchart illustrating the diagnostic processing method provided in the embodiments of this application. The specific process can be summarized in the following steps S101 to S105: Step S101: Receive a vehicle diagnostic request for the target vehicle of the first edge node.

[0034] Here, the first edge node refers to the edge node that has vehicle diagnostic needs. The target vehicle refers to the vehicle for which the first edge node needs to perform vehicle diagnostics.

[0035] Specifically, during vehicle operation (including driving or testing), the target vehicle's controller (such as the vehicle controller or ECU) monitors and analyzes its operational data. This monitoring can be real-time or timed. When an anomaly is detected in the operational data, the edge node (i.e., the first edge node) of the target vehicle is triggered to generate a vehicle diagnostic request for that vehicle and send it to the central node. For example, during vehicle operation, the vehicle controller collects operational data 30 times per second, including but not limited to engine speed, pressure, battery voltage, and brake pad wear. The fault analysis model configured on the edge node of the vehicle is used to determine data anomalies. If an anomaly is detected (such as oil pressure below the normal threshold, battery range degradation rate exceeding the average threshold for the same vehicle model, or other operational data deviating from preset standard values), a vehicle diagnostic task is generated and sent to the central node via a wireless network (such as 4G / 5G).

[0036] The vehicle diagnostic request refers to a request to perform diagnostic control on the target vehicle. The vehicle diagnostic request can carry various information, including but not limited to the target vehicle identifier and the version information of the fault analysis model configured on the first edge node. These details can be adjusted according to actual circumstances and are not limited here. The vehicle identifier can be used to identify the vehicle model.

[0037] Step S102: Based on the vehicle diagnostic request, generate a fault analysis instruction for the target vehicle.

[0038] Among them, the fault analysis command refers to the command used to control the fault analysis model configured by the first edge node to perform fault analysis (also known as fault diagnosis) on the target vehicle.

[0039] Specifically, based on the target vehicle identifier carried in the vehicle diagnostic request, a fault analysis command is generated for the target vehicle controlled by the first edge node.

[0040] Step S103: Send a fault analysis command to the first edge node so that the first edge node, upon receiving the fault analysis command, performs fault analysis on the target vehicle using the fault analysis model configured on the first edge node, obtains fault analysis results on the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node.

[0041] Specifically, the central node sends the fault analysis command to the first edge node. After receiving the fault analysis command, the first edge node performs fault analysis on the target vehicle according to the fault analysis model configured on the first edge node, obtains the fault analysis results on the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node.

[0042] Among them, the fault analysis model refers to the model used for vehicle fault diagnosis.

[0043] The fault analysis model configured on the edge nodes is distributed through the central node.

[0044] Understandably, the central node is configured with multiple latest versions of fault analysis models, each with a different vehicle identifier. The vehicle identifier identifies the vehicle's type. The central node periodically, or under specific conditions (such as idle state), determines the target edge node to which the updated fault analysis model should be sent, based on the vehicle identifier corresponding to the fault analysis model and the vehicle identifiers of the vehicles controlled by the edge nodes. The central node then controls the transmission of the updated fault analysis model to the target edge node.

[0045] In some embodiments, the diagnostic control method includes: in response to a model update event, acquiring update data matching the model update event; determining a second fault analysis model to be updated that matches the model update event from multiple fault analysis models configured by the central node; and updating the second fault analysis model based on the update data to obtain an updated second fault analysis model.

[0046] The model update event is used to indicate events that update the fault analysis model configured on the central node. The model update event can be adjusted according to actual conditions and is not limited here. For example, the model update event can be triggered based on an operation on the model update control. The model update control can be provided through the diagnostic device interface or through other software devices connected to the diagnostic processing system.

[0047] The second fault analysis model refers to the fault analysis model that needs to be updated among the multiple fault analysis models configured in the central node. Updated data refers to the data that needs to be updated to the second fault analysis model. Updated data can include new data (such as new fault types, the corresponding failure status of the new fault type, and the corresponding maintenance plan for the new fault type) and changed data (such as the fault changes or maintenance plans in the fault types that need to be changed).

[0048] In other words, the embodiments of this application use incremental updates to update the fault analysis model. That is, the fault analysis model stored in the edge nodes is only updated when a new fault type or a new fault repair plan appears in the central node, or when the data of an existing repair plan changes.

[0049] Based on this, the above diagnostic processing method further includes: when the network status of the central node meets the preset network conditions, determining the second edge node that matches the vehicle identifier corresponding to the second fault analysis model from multiple edge nodes; sending the updated second fault analysis model to each second edge node, so that the second edge node can update the model based on the updated second fault analysis model.

[0050] The second edge node refers to the edge node that corresponds to the vehicle identifier and matches the vehicle identifier of the second fault analysis model.

[0051] In some embodiments, before sending the fault analysis command to the first edge node, the diagnostic processing method further includes the following steps: Identify the version information of the fault analysis model configured for the first edge node; When the version information indicates that the fault analysis model belongs to a non-latest version, based on the target vehicle identifier of the target vehicle carried in the vehicle diagnostic request, the first fault analysis model that matches the target vehicle identifier is determined from multiple fault analysis models configured in the central node. Send the first fault analysis model to the first edge node so that the first edge node can update the model based on the first fault analysis model.

[0052] The version information is used to indicate whether the fault analysis model configured on the first edge node is the latest version of the fault analysis model configured on the central node.

[0053] There are several ways to identify the version information of the fault analysis model configured on the first edge node, and the specific methods can be adjusted according to the actual situation; no restrictions are imposed here. For example, vehicle diagnostic requests can be parsed to obtain the parsing results, and the version information of the fault analysis model configured on the first edge node can be identified from the parsing results. That is, the vehicle diagnostic request carries the version information of the fault analysis model configured on the first edge node. Another example is that the model update status of each edge node can be recorded on the central node. When a vehicle diagnostic request for a target vehicle of the first edge node is received, the model update status corresponding to that first edge node can be obtained to identify the version information of the fault analysis model configured on the first edge node. The model update status includes a first status indicating that the fault analysis model belongs to a non-latest version and a second status indicating that the fault analysis model belongs to the latest version.

[0054] The first fault analysis model refers to the fault analysis model that matches the target vehicle identifier of the target vehicle belonging to the first edge node among the multiple latest versions of fault analysis models configured in the central node.

[0055] Specifically, the central node identifies the version information of the fault analysis model configured by the first edge node. If the version information indicates that the fault analysis model belongs to a non-latest version, based on the target vehicle identifier carried in the vehicle diagnostic request, the central node determines the first fault analysis model matching the target vehicle identifier from among multiple fault analysis models configured therein, and sends the first fault analysis model to the first edge node. Upon receiving the first fault analysis model, the first edge node updates its configured fault analysis model based on it. The model update process can be adjusted according to actual conditions; for example, the differences between two fault analysis models can be determined first, and the fault analysis model configured by the first edge node can be updated based on these differences to ensure that the updated fault analysis model is identical to the first fault analysis model.

[0056] Based on this, the above method further includes: after the first edge node updates the model based on the first fault analysis model, performing fault analysis on the target vehicle through the fault analysis model configured by the first edge node, obtaining fault analysis results on the fault changes of abnormal components in the target vehicle, and sending the fault analysis results to the central node.

[0057] In some embodiments, the method further includes sending a fault analysis instruction to the first edge node when the version information indicates that the fault analysis model belongs to the latest version.

[0058] It is understandable that the first fault analysis model and fault analysis instructions can be simultaneously issued from the central node to the first edge node, but model updates based on the first fault analysis model must occur before updates based on the fault analysis instructions. Therefore, the method further includes: when the version information indicates that the fault analysis model belongs to the latest version, performing fault analysis on the target vehicle using the fault analysis model configured on the first edge node, obtaining fault analysis results regarding the fault changes of abnormal components in the target vehicle, and sending the fault analysis results to the central node.

[0059] Specifically, the central node verifies the update status of the fault analysis model configured on the first edge node based on the vehicle diagnostic request. Specifically, it checks whether the fault analysis model configured on the first edge node is in the latest updated state or the latest version. If yes, it proceeds to the next step; otherwise, it updates the fault analysis model configured on the first edge node. The central node then sends a fault analysis command to the target vehicle corresponding to the first edge node, enabling the target vehicle's controller to collect historical and future operational data over a period before and after the abnormal state and perform fault trend analysis according to time sequence to obtain the fault analysis results.

[0060] The fault analysis results include abnormal components present in the target vehicle, as well as the fault changes (i.e., fault trends) of these abnormal components. For example, the fault analysis results may include the fault trend of brake pads whose wear condition is approaching a critical value, or the fault trend of battery charging efficiency declining. The specific results can be adjusted according to the actual situation and are not limited here.

[0061] Step S104: After receiving the fault analysis results from the first edge node, determine the target maintenance plan that matches the fault changes contained in the fault analysis results.

[0062] The target maintenance plan refers to the maintenance plan for the abnormal component under the condition of the fault change.

[0063] It is understandable that the central node is also configured with multiple preset fault types included in each fault analysis model, as well as the first correspondence between each preset fault type and the preset fault change, and the second correspondence between each preset fault type and the preset maintenance plan.

[0064] Based on this, the process of determining a target maintenance plan that matches the fault changes contained in the fault analysis results after receiving the fault analysis results from the first edge node may include the following steps: The preset fault types included in the first fault analysis model are used as candidate fault types; After receiving the fault analysis results from the first edge node, based on the first correspondence, a first fault type that matches the fault change in the fault analysis results is determined from multiple candidate fault types. Based on the second correspondence, the repair solution that matches the first fault type is obtained as the target repair solution.

[0065] Among them, candidate fault type refers to at least one fault type contained in the fault analysis model that matches the target vehicle identifier of the target vehicle.

[0066] The first fault type refers to the candidate fault type that matches the fault change.

[0067] Specifically, after receiving the fault analysis results from the first edge node, based on the first correspondence between preset fault types and preset fault change scenarios, a first fault type matching each fault change scenario included in the fault analysis results is determined from multiple candidate fault types. Based on the second correspondence between preset fault types and preset maintenance plans, a maintenance plan matching the first fault type is determined as the target maintenance plan.

[0068] Specifically, the central node uses multiple fault analysis models as references to verify the current fault trend of the target vehicle. If there is a fault trend of the same type and model (i.e., the target vehicle identifier), the fault type of the current vehicle (i.e., the existing fault type with the same fault trend) is determined. The fault repair task is generated by combining the fault diagnosis plan of the same type and model (i.e., the target repair plan) and sent to the first edge node.

[0069] Step S105: Send the target repair plan to the first edge node so that the abnormal parts in the target vehicle can be repaired based on the target repair plan.

[0070] Specifically, the target repair plan is run on the target vehicle at the first edge node to locate the fault and perform adaptive repair. The repair results are then fed back to the central node for verification. If the verification result indicates that the target repair plan has resolved the current fault, a diagnostic report is generated and sent to the vehicle driver. If the verification result indicates that the target repair plan cannot resolve the current fault, a warning message is generated to inform the vehicle driver to perform timely repairs.

[0071] The verification of the repair results involves obtaining vehicle operation data at the fault repair location within a certain period after the repair. If the vehicle operation data is within the normal operating range, it indicates that the current fault has been resolved; if the vehicle operation data is within the predicted range that matches the fault trend, it indicates that the current fault has not been resolved.

[0072] Based on this, the above diagnostic and treatment method also includes the following steps: In response to a fault warning event, the central node generates a fault warning message based on the fault analysis results to prompt maintenance personnel to perform maintenance on the target vehicle under the condition of abnormal component fault changes. Obtain repair plans from maintenance personnel for target vehicles under varying fault conditions of abnormal components; Determine the second fault type to which the fault changes in the fault analysis results belong; Establish a first target correspondence between the fault changes in the fault analysis results and the second fault type to which the fault changes belong, and establish a second target correspondence between the maintenance plan for resolving the fault changes and the second fault type to which the fault changes belong; To add a second fault type, a first target correspondence, and a second target correspondence to the target fault analysis model that matches the target vehicle's identifier.

[0073] Among them, a fault warning event refers to an event that requires the generation of fault warning information to prompt maintenance personnel to perform repairs on a target vehicle under conditions of abnormal component fault changes. Fault warning events can be triggered based on actual circumstances, without limitation here. For example, a fault warning event is triggered if the target repair plan matching the fault changes contained in the fault analysis results fails. Another example is triggered if, after repairing the abnormal component in the target vehicle based on the target repair plan, a repair feedback result sent from the first edge node based on the target repair plan is received, and the repair feedback result indicates repair failure.

[0074] The second fault type refers to the fault type to which the fault changes in the fault analysis results belong. This second fault type is distinct from the fault type in the fault analysis model corresponding to the first edge node; it is a newly added fault type. The second fault type can be obtained through manual or other methods of analyzing the fault changes in the fault analysis results; no restrictions are placed here.

[0075] Among them, the repair plan for the target vehicle under the condition of abnormal component failure changes can be obtained through manual input or information collection, and there are no restrictions here.

[0076] The diagnostic processing method provided in this application embodiment can receive vehicle diagnostic requests for a target vehicle at a first edge node through a central node; generate fault analysis instructions for the target vehicle based on the vehicle diagnostic requests; send the fault analysis instructions to the first edge node, so that the first edge node, upon receiving the fault analysis instructions, performs fault analysis on the target vehicle using its configured fault analysis model, obtains fault analysis results on the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node; after receiving the fault analysis results from the first edge node, determine a target repair plan that matches the fault changes contained in the fault analysis results; and send the target repair plan to the first edge node so that the abnormal components in the target vehicle can be repaired based on the target repair plan. In this way, through the interaction between the edge node and the central node, the amount of data transmission between the edge node and the central node is reduced, enabling vehicle fault analysis at the edge node, verification and repair plan determination at the central node, thereby avoiding the problem of poor diagnostic timeliness caused by the transmission delay of vehicle monitoring data, and thus improving diagnostic efficiency.

[0077] To facilitate a better understanding of the diagnostic processing method provided in the embodiments of this application, this application also provides a diagnostic processing system, wherein the meanings of the terms are the same as those in the diagnostic processing method described above, and specific implementation details can be found in the description in the method embodiments.

[0078] For example, such as Figure 3As shown in the embodiment of this application, the diagnostic processing system 20 includes a central node 201 and multiple edge nodes 202 connected to the central node 201. The central node 201 manages each edge node 202, and each edge node 202 corresponds to a vehicle for performing diagnostic control on the corresponding vehicle. The central node 201 receives a vehicle diagnostic request for the target vehicle of the first edge node; based on the vehicle diagnostic request, it generates a fault analysis command for the target vehicle and sends the fault analysis command to the first edge node. Upon receiving a fault analysis command, the first edge node performs fault analysis on the target vehicle using the fault analysis model configured in the first edge node, obtains fault analysis results on the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node 201. After receiving the fault analysis results from the first edge node, the central node 201 determines the target maintenance plan that matches the fault changes contained in the fault analysis results. The target repair plan is sent to the first edge node through the central node 201, so that the abnormal parts in the target vehicle can be repaired based on the target repair plan.

[0079] Among them, the first edge node is edge node 20 that initiates a vehicle diagnostic request to the central node 201.

[0080] The central node 201 in the aforementioned diagnostic processing system 20 can be used to execute various steps in the aforementioned diagnostic processing method. For example, the central node 201 identifies the version information of the fault analysis model configured by the first edge node; when the version information indicates that the fault analysis model belongs to a non-latest version, based on the target vehicle identifier carried in the vehicle diagnostic request, it determines a first fault analysis model matching the target vehicle identifier from among the multiple fault analysis models configured by the central node; and sends the first fault analysis model to the first edge node so that the first edge node can update the model based on the first fault analysis model. Another example is that the central node 201 responds to a model update event, obtains update data matching the model update event; determines a second fault analysis model to be updated from among the multiple fault analysis models configured by the central node that matches the model update event; and updates the second fault analysis model based on the update data to obtain the updated second fault analysis model. For details, please refer to the above description; further elaboration is not provided here.

[0081] Thus, a one-to-many remote vehicle diagnostic framework, or diagnostic processing system, is constructed through cloud-edge collaboration. A remote data processing center serves as the sole central node, managing multiple edge nodes corresponding to various vehicle terminals. The remote data processing center constructs multiple data models for the same vehicle model (which can be understood as fault analysis models matched with different vehicle identifiers, where the vehicle identifier identifies different vehicle models), and synchronizes these models to the corresponding edge nodes. The edge nodes perform local autonomous processing of vehicle monitoring and fault prediction using their data models. The central node verifies the effectiveness of fault diagnosis results and repair solutions, and promptly alerts vehicle occupants. This approach helps reduce the workload of the remote data processing center in data processing, computation, and execution through the local autonomy of the edge nodes. When facing new or unknown faults that have not yet been defined, it can also use similar faults from other vehicles as a reference for diagnosis and fault warning. This offloads a large amount of vehicle operation data processing to the edge nodes, reducing data transmission latency and improving the timeliness of vehicle diagnostics.

[0082] To facilitate better implementation of the diagnostic processing method provided in the embodiments of this application, the embodiments of this application also provide an apparatus based on the above-described diagnostic processing method. The meanings of the terms used are the same as in the above-described diagnostic processing method, and specific implementation details can be found in the descriptions in the method embodiments.

[0083] For example, such as Figure 4 As shown, this application provides an apparatus based on the above-described diagnostic processing method, applied to the central node of a diagnostic processing system. The diagnostic processing system further includes multiple edge nodes connected to the central node. The central node manages each edge node, and each edge node corresponds to a vehicle for performing diagnostic control of the corresponding vehicle. The diagnostic processing apparatus may include: The first receiving module 301 is used to receive a vehicle diagnostic request for the target vehicle of the first edge node. The instruction generation module 302 is used to generate fault analysis instructions for the target vehicle based on the vehicle diagnostic request. The instruction sending module 303 is used to send a fault analysis instruction to the first edge node, so that when the first edge node receives the fault analysis instruction, it performs fault analysis on the target vehicle through the fault analysis model configured on the first edge node, obtains the fault analysis results for the fault changes of abnormal parts in the target vehicle, and sends the fault analysis results to the central node. The second receiving module 304 is used to receive the fault analysis results from the first edge node and determine the target maintenance plan that matches the fault changes contained in the fault analysis results. Repair module 305 is used to send the target repair plan to the first edge node so as to repair the abnormal parts in the target vehicle based on the target repair plan.

[0084] In some embodiments, the central node is configured with multiple latest versions of fault analysis models, and different fault analysis models correspond to different vehicle identifiers. Before the instruction sending module 303 sends the fault analysis instruction to the first edge node, the diagnostic processing device further includes: The information identification unit is used to identify the version information of the fault analysis model configured in the first edge node; The first model determining unit is used to determine the first fault analysis model that matches the target vehicle identifier from multiple fault analysis models configured in the central node, based on the target vehicle identifier of the target vehicle carried in the vehicle diagnostic request, when the version information indicates that the version of the fault analysis model is not the latest version. The first update unit is used to send the first fault analysis model to the first edge node so that the first edge node can update the model based on the first fault analysis model.

[0085] In some embodiments, the central node is further configured with multiple preset fault types included in each fault analysis model, a first correspondence between each preset fault type and preset fault change, and a second correspondence between each preset fault type and preset maintenance plan.

[0086] Based on this, after receiving the fault analysis results from the first edge node, the second receiving module 304 determines a target maintenance plan that matches the fault changes contained in the fault analysis results, including: The first type determination unit is used to select the preset fault types contained in the first fault analysis model as candidate fault types. The second type determination unit is used to, after receiving the fault analysis results from the first edge node, determine the first fault type that matches the fault change in the fault analysis results from multiple candidate fault types according to the first correspondence relationship; The first determining unit of the scheme is used to obtain a maintenance scheme that matches the first fault type as the target maintenance scheme based on the second correspondence relationship.

[0087] In some embodiments, the diagnostic processing apparatus further includes: The early warning unit is used to respond to fault warning events and generate fault warning information based on fault analysis results through the central node to prompt maintenance personnel to carry out maintenance on the target vehicle under the condition of abnormal component fault changes. The second determination unit of the scheme is used to obtain the maintenance plan of the maintenance personnel for the target vehicle under the condition of abnormal component failure change; The third type determination unit is used to determine the second fault type to which the fault change in the fault analysis results belong; The relationship establishment unit is used to establish a target first correspondence between the fault change situation in the fault analysis results and the second fault type to which the fault change situation belongs, and to establish a target second correspondence between the maintenance plan for solving the fault change situation and the second fault type to which the fault change situation belongs; The information addition unit is used to add a second fault type, a first target correspondence, and a second target correspondence to the target fault analysis model that matches the target vehicle identifier to which the target vehicle belongs.

[0088] In some embodiments, the above-mentioned fault warning event is triggered based on at least one of the following conditions: The acquisition of a target repair solution that matches the fault changes contained in the fault analysis results failed. Alternatively, after repairing the abnormal parts in the target vehicle based on the target repair plan, the system receives repair feedback results sent by the first edge node based on the target repair plan, and the repair feedback results indicate that the repair failed.

[0089] In some embodiments, the diagnostic processing apparatus further includes: The data acquisition unit is used to acquire updated data that matches the model update event in response to the model update event; The second model determination unit is used to determine the second fault analysis model to be updated that matches the model update event from among the multiple fault analysis models configured in the central node. The second update unit is used to update the second fault analysis model based on the updated data to obtain the updated second fault analysis model.

[0090] In some embodiments, the diagnostic processing apparatus further includes: The node determination unit is used to determine the second edge node that matches the vehicle identifier corresponding to the second fault analysis model from multiple edge nodes, provided that the network status of the central node meets the preset network conditions. The third update unit is used to send the updated second fault analysis model to each second edge node, so that the second edge nodes can update their models based on the updated second fault analysis model.

[0091] The diagnostic processing apparatus of this application embodiment can receive a vehicle diagnostic request for a target vehicle at a first edge node via a first receiving module 301; an instruction generation module 302 generates a fault analysis instruction for the target vehicle based on the vehicle diagnostic request; an instruction sending module 303 sends the fault analysis instruction to the first edge node, so that the first edge node, upon receiving the fault analysis instruction, performs fault analysis on the target vehicle using its configured fault analysis model, obtains fault analysis results on the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node; a second receiving module 304, after receiving the fault analysis results from the first edge node, determines a target repair plan that matches the fault changes contained in the fault analysis results; and a repair module 305 sends the target repair plan to the first edge node to repair the abnormal components in the target vehicle based on the target repair plan. In this way, through the interaction between the edge node and the central node, the amount of data transmission between the edge node and the central node is reduced, enabling vehicle fault analysis at the edge node, verification and repair plan determination at the central node, thereby avoiding the problem of poor diagnostic timeliness caused by the transmission delay of vehicle monitoring data, and thus improving diagnostic efficiency.

[0092] In practice, each of the above modules can be implemented as an independent entity or can be combined arbitrarily to be implemented as the same or several entities. For the specific implementation methods and corresponding beneficial effects of each of the above modules, please refer to the previous method embodiments, which will not be repeated here.

[0093] This application also provides an electronic device, such as... Figure 5 As shown, it illustrates a structural schematic diagram of the electronic device involved in the embodiments of this application, specifically: The electronic device may include components such as a processor 401 with one or more processing cores, a memory 402 with one or more storage media, a power supply 403, and an input unit 404. Those skilled in the art will understand that... Figure 5 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein: The processor 401 is the control center of the electronic device, connecting various parts of the device via various interfaces and lines. It executes computer programs and / or modules stored in the memory 402, and calls data stored in the memory 402, to perform various functions and process data. Optionally, the processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 401.

[0094] The memory 402 can be used to store computer programs and modules. The processor 401 executes various functional applications and diagnostic schemes by running the computer programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, computer programs required for at least one function (such as voice prompt function, text input function, voice input function, scheme selection function, etc.), etc.; the data storage area may store data created according to the use of the electronic device. In addition, the memory 402 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 402 may also include memory electronics to provide the processor 401 with access to the memory 402.

[0095] The electronic device also includes a power supply 403 that supplies power to the various components. Preferably, the power supply 403 can be logically connected to the processor 401 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 403 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0096] The electronic device may also include an input unit 404, which can be used to receive input digital or character information, and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0097] Although not shown, the electronic device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 401 in the electronic device loads the executable files corresponding to the processes of one or more computer programs into the memory 402 according to the following instructions, and the processor 401 runs the computer programs stored in the memory 402 to realize various functions. For example: Receive vehicle diagnostic requests for the target vehicle at the first edge node; Based on the vehicle diagnostic request, generate fault analysis instructions for the target vehicle; A fault analysis command is sent to the first edge node so that, upon receiving the fault analysis command, the first edge node performs fault analysis on the target vehicle using the fault analysis model configured on the first edge node, obtains fault analysis results on the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node. After receiving the fault analysis results from the first edge node, a target maintenance plan that matches the fault changes contained in the fault analysis results is determined. The target repair plan is sent to the first edge node so that the abnormal parts in the target vehicle can be repaired based on the target repair plan.

[0098] Therefore, the electronic device provided in this application embodiment can receive vehicle diagnostic requests for a target vehicle at a first edge node through a central node; generate fault analysis instructions for the target vehicle based on the vehicle diagnostic requests; send the fault analysis instructions to the first edge node, so that the first edge node, upon receiving the fault analysis instructions, performs fault analysis on the target vehicle using its configured fault analysis model, obtains fault analysis results on the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node; after receiving the fault analysis results from the first edge node, determines a target repair plan that matches the fault changes contained in the fault analysis results; and sends the target repair plan to the first edge node so that the abnormal components in the target vehicle can be repaired based on the target repair plan. In this way, through the interaction between the edge node and the central node, the amount of data transmission between the edge node and the central node is reduced, enabling vehicle fault analysis at the edge node, verification and repair plan determination at the central node, thereby avoiding the problem of poor diagnostic timeliness caused by the transmission delay of vehicle monitoring data, and thus improving diagnostic efficiency.

[0099] For details on the specific implementation methods and corresponding beneficial effects of the above operations, please refer to the detailed description of the diagnostic and treatment methods above, which will not be repeated here.

[0100] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by a computer program, or by a computer program controlling related hardware. The computer program can be stored in a storage medium and loaded and executed by a processor.

[0101] Therefore, embodiments of this application provide a storage medium storing a computer program that can be loaded by a processor to execute steps in any of the diagnostic processing methods provided in embodiments of this application. For example, the computer program can execute the following steps: Receive vehicle diagnostic requests for the target vehicle at the first edge node; Based on the vehicle diagnostic request, generate fault analysis instructions for the target vehicle; A fault analysis command is sent to the first edge node so that, upon receiving the fault analysis command, the first edge node performs fault analysis on the target vehicle using the fault analysis model configured on the first edge node, obtains fault analysis results on the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node. After receiving the fault analysis results from the first edge node, a target maintenance plan that matches the fault changes contained in the fault analysis results is determined. The target repair plan is sent to the first edge node so that the abnormal parts in the target vehicle can be repaired based on the target repair plan.

[0102] Therefore, the storage medium provided in this application embodiment can receive vehicle diagnostic requests for a target vehicle at a first edge node through a central node; generate fault analysis instructions for the target vehicle based on the vehicle diagnostic requests; send the fault analysis instructions to the first edge node, so that the first edge node, upon receiving the fault analysis instructions, performs fault analysis on the target vehicle using its configured fault analysis model, obtains fault analysis results on the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node; after receiving the fault analysis results from the first edge node, determines a target repair plan that matches the fault changes contained in the fault analysis results; and sends the target repair plan to the first edge node so that the abnormal components in the target vehicle can be repaired based on the target repair plan. In this way, through the interaction between the edge node and the central node, the amount of data transmission between the edge node and the central node is reduced, enabling vehicle fault analysis at the edge node, verification and repair plan determination at the central node, thereby avoiding the problem of poor diagnostic timeliness caused by the transmission delay of vehicle monitoring data, and thus improving diagnostic efficiency.

[0103] For details on the specific implementation methods and corresponding beneficial effects of the above operations, please refer to the previous embodiments, which will not be repeated here.

[0104] The storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0105] Since the computer program stored in the storage medium can execute the steps in any of the diagnostic processing methods provided in the embodiments of this application, the beneficial effects that any of the diagnostic processing methods provided in the embodiments of this application can achieve can be realized, as detailed in the preceding embodiments, and will not be repeated here.

[0106] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a storage medium. A processor of a computer device reads the computer instructions from the storage medium and executes the computer instructions, causing the computer device to perform the aforementioned diagnostic processing method.

[0107] The above provides a detailed description of a diagnostic processing method, system, device, electronic device, storage medium, and computer program product provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A diagnostic treatment method, characterized in that, A central node is applied to a diagnostic processing system, which further includes multiple edge nodes connected to the central node. The central node manages each edge node, and each edge node corresponds to a vehicle for performing diagnostic control of that vehicle. The method includes: Receive vehicle diagnostic requests for the target vehicle at the first edge node; Based on the vehicle diagnostic request, generate a fault analysis instruction for the target vehicle; The fault analysis command is sent to the first edge node so that, upon receiving the fault analysis command, the first edge node performs fault analysis on the target vehicle using the fault analysis model configured on the first edge node, obtains fault analysis results for the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node. After receiving the fault analysis results from the first edge node, a target maintenance plan that matches the fault changes contained in the fault analysis results is determined; The target repair plan is sent to the first edge node so that the abnormal parts in the target vehicle can be repaired based on the target repair plan.

2. The diagnostic processing method according to claim 1, characterized in that, The central node is configured with multiple latest versions of fault analysis models, and different fault analysis models correspond to different vehicle identifiers. Before sending the fault analysis command to the first edge node, the process further includes: Identify the version information of the fault analysis model configured for the first edge node; If the version information indicates that the fault analysis model belongs to a non-latest version, based on the target vehicle identifier of the target vehicle carried in the vehicle diagnostic request, a first fault analysis model matching the target vehicle identifier is determined from multiple fault analysis models configured in the central node. The first fault analysis model is sent to the first edge node so that the first edge node can update its model based on the first fault analysis model.

3. The diagnostic processing method according to claim 2, characterized in that, The central node is also configured with multiple preset fault types included in each fault analysis model, a first correspondence between each preset fault type and preset fault change, and a second correspondence between each preset fault type and preset maintenance plan; After receiving the fault analysis result from the first edge node, determining a target maintenance plan that matches the fault change information contained in the fault analysis result includes: The preset fault types included in the first fault analysis model are used as candidate fault types; After receiving the fault analysis result from the first edge node, based on the first correspondence, a first fault type that matches the fault change in the fault analysis result is determined from the plurality of candidate fault types; Based on the second correspondence, a repair solution that matches the first fault type is obtained as the target repair solution.

4. The diagnostic processing method according to claim 3, characterized in that, The method further includes: In response to a fault warning event, the central node generates a fault warning message based on the fault analysis results to prompt maintenance personnel to perform maintenance on the target vehicle under the condition of fault changes in the abnormal component. Obtain the repair plan proposed by the maintenance personnel for the target vehicle under the condition of changes in the fault of the abnormal component; Determine the second fault type to which the fault changes in the fault analysis results belong; Establish a first target correspondence between the fault changes in the fault analysis results and the second fault type to which the fault changes belong, and establish a second target correspondence between the maintenance plan for resolving the fault changes and the second fault type to which the fault changes belong; To add the second fault type, the first correspondence of the target, and the second correspondence of the target to the target fault analysis model that matches the target vehicle identifier of the target vehicle.

5. The diagnostic processing method according to claim 4, characterized in that, The fault warning event is triggered based on at least one of the following conditions: The acquisition of a target repair plan that matches the fault changes contained in the fault analysis results failed. Alternatively, after repairing the abnormal component in the target vehicle based on the target repair plan, a repair feedback result sent from the first edge node based on the target repair plan is received, and the repair feedback result indicates that the repair failed.

6. The diagnostic treatment method according to any one of claims 1 to 5, characterized in that, The method further includes: In response to a model update event, obtain update data that matches the model update event; From the multiple fault analysis models configured in the central node, determine the second fault analysis model to be updated that matches the model update event; Based on the updated data, the second fault analysis model is updated to obtain the updated second fault analysis model.

7. The diagnostic processing method according to claim 6, characterized in that, The method further includes: When the network status of the central node meets the preset network conditions, a second edge node that matches the vehicle identifier corresponding to the second fault analysis model is determined from multiple edge nodes. The updated second fault analysis model is sent to each of the second edge nodes, so that the second edge nodes can update their models based on the updated second fault analysis model.

8. A diagnostic processing system, characterized in that, The diagnostic processing system includes a central node and multiple edge nodes connected to the central node. The central node manages each edge node, and each edge node corresponds to a vehicle for performing diagnostic control on that vehicle. The central node receives a vehicle diagnostic request for the target vehicle of the first edge node; based on the vehicle diagnostic request, it generates a fault analysis instruction for the target vehicle and sends the fault analysis instruction to the first edge node. Upon receiving the fault analysis instruction, the first edge node performs fault analysis on the target vehicle using the fault analysis model configured on the first edge node, obtains fault analysis results for the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node. After receiving the fault analysis results from the first edge node, the central node determines a target maintenance plan that matches the fault changes contained in the fault analysis results. The central node sends the target repair plan to the first edge node so that the abnormal parts in the target vehicle can be repaired based on the target repair plan.

9. A diagnostic processing device, characterized in that, A central node is used in a diagnostic processing system, which also includes multiple edge nodes connected to the central node. The central node manages each edge node, and each edge node corresponds to a vehicle for performing diagnostic control on that vehicle. The device includes: The first receiving module is used to receive vehicle diagnostic requests for the target vehicle of the first edge node. The instruction generation module is used to generate fault analysis instructions for the target vehicle based on the vehicle diagnostic request. The instruction sending module is used to send the fault analysis instruction to the first edge node, so that when the first edge node receives the fault analysis instruction, it performs fault analysis on the target vehicle through the fault analysis model configured on the first edge node, obtains fault analysis results for the fault changes of abnormal components in the target vehicle, and sends the fault analysis results to the central node. The second receiving module is used to receive the fault analysis results from the first edge node and then determine a target maintenance plan that matches the fault changes contained in the fault analysis results. The repair module is used to send the target repair plan to the first edge node so as to repair the abnormal parts in the target vehicle based on the target repair plan.

10. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of the diagnostic processing method according to any one of claims 1 to 7.

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