Vehicle fault sensing and processing method and related product

Abstract

The invention discloses a vehicle fault sensing and processing method and related products, which can be applied to the technical field of computers, and the method comprises the following steps: obtaining message data representing vehicle fault information from a system cache; analyzing the message data to obtain key feature information corresponding to the vehicle; based on a preset fault processing rule, screening the key feature information, and determining target feature data conforming to subsequent circulation; and transmitting the target feature data to a platform processing system for an after-sales system to perform information return visit. Therefore, the key feature information corresponding to the vehicle fault is processed through the preset fault processing rule and is sent to the platform processing system, so that the utilization rate of the vehicle data is improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method for sensing and processing vehicle faults and related products. Background Art

[0002] Vehicle after-sales service typically includes vehicle inspection, maintenance, fault diagnosis, and repair. However, these services typically require users to proactively contact after-sales service. It's difficult for after-sales systems to remotely detect vehicle faults and provide timely and effective feedback and resolution.

[0003] With regard to the large amount of existing vehicle data, due to the lack of guiding processes and targeted processing engines, a lot of valuable data cannot be effectively utilized, related faults cannot be detected in a timely manner, and a good communication bridge cannot be established with the after-sales system, making it impossible for the after-sales system to conduct effective information feedback, and thus unable to provide timely and effective feedback on vehicle fault handling methods.

[0004] Therefore, how to improve the utilization rate of vehicle data is an issue that technical personnel in this field urgently need to solve. Summary of the Invention

[0005] Based on the above problems, the embodiments of the present application provide a method and related products for vehicle fault perception and processing, which processes the key feature information corresponding to the vehicle fault through preset fault processing rules and sends it to the platform processing system, thereby improving the utilization rate of vehicle data.

[0006] In a first aspect, an embodiment of the present application provides a method for sensing and handling vehicle faults, including:

[0007] Obtaining message data representing vehicle fault information from a system cache;

[0008] Parsing the message data to obtain key feature information corresponding to the vehicle;

[0009] Based on the preset fault handling rules, the key feature information is screened to determine the target feature data that meets the subsequent flow;

[0010] The target feature data is transmitted to the platform processing system for information feedback by the after-sales system.

[0011] Optionally, before obtaining the message data representing the vehicle fault information from the system cache, the method further includes:

[0012] Based on the vehicle's internal data flow message queue, the client monitors the data transmission channel to pull message data representing vehicle fault information;

[0013] The message data is stored in a system cache.

[0014] Optionally, parsing the message data to obtain key feature information corresponding to the vehicle includes:

[0015] Deserialize the message data using a deserialization tool;

[0016] The deserialized message data is parsed based on a preset data interaction protocol to extract key feature information corresponding to the vehicle; the key feature information includes vehicle identification code, fault type, fault code, fault collection time and vehicle location.

[0017] Optionally, the key feature information is screened based on preset fault handling rules to determine target feature data that meets the requirements for subsequent flow, including:

[0018] Perform rule query based on the key feature information to determine a preset fault handling rule corresponding to the vehicle fault;

[0019] parsing the preset fault handling rule, and processing the key feature information according to the preset fault handling rule to obtain first feature data;

[0020] A validity judgment is performed on the first feature data, and the first feature data that passes the validity judgment is used as target feature data.

[0021] Optionally, parsing the preset fault handling rule and processing the key feature information according to the preset fault handling rule to obtain the first feature data includes:

[0022] If the preset fault handling rule does not specify a handling frequency corresponding to the vehicle fault, determining the forwarding destination and the data information that needs to be additionally spliced ​​with the key feature information according to the preset fault handling rule;

[0023] Based on the internal basic service capabilities, the data information is obtained through a request-response protocol and is spliced ​​with the key feature information to obtain the first feature data.

[0024] Optionally, the method further includes:

[0025] If the preset fault handling rule specifies a processing frequency corresponding to a vehicle fault, the LUA script is used to control the frequency of the vehicle fault.

[0026] Optionally, before transmitting the characteristic data to the platform processing system for the after-sales system to conduct information feedback, the method further includes:

[0027] Establish a communication mechanism with the platform processing system through network connection.

[0028] In a second aspect, an embodiment of the present application provides a vehicle fault sensing and processing device, including:

[0029] An acquisition module, used to obtain message data representing vehicle fault information from a system cache;

[0030] A parsing module, configured to parse the message data to obtain key feature information corresponding to the vehicle;

[0031] A screening module is used to screen the key feature information based on preset fault handling rules to determine target feature data that meets the requirements for subsequent flow;

[0032] The transmission module is used to transmit the target feature data to the platform processing system for the after-sales system to conduct information feedback.

[0033] In a third aspect, an embodiment of the present application provides a vehicle fault sensing and processing device, including:

[0034] Memory for storing computer programs;

[0035] A processor is used to implement the steps of the method for vehicle fault perception and processing as described above when executing the computer program.

[0036] In a fourth aspect, an embodiment of the present application provides a readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method for vehicle fault perception and processing as described above are implemented.

[0037] It can be seen from the above technical solutions that compared with the existing technology, this application has the following advantages:

[0038] This application first obtains message data representing vehicle fault information from the system cache and parses the message data to obtain key feature information corresponding to the vehicle. Then, based on preset fault handling rules, the key feature information is screened to determine target feature data that meets the requirements for subsequent circulation. Finally, the target feature data is transmitted to the platform processing system for information feedback by the after-sales system. In this way, the key feature information corresponding to the vehicle fault is processed by the preset fault handling rules and sent to the platform processing system, thereby improving the utilization rate of vehicle data. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A flowchart of a method for sensing and handling vehicle faults provided in an embodiment of the present application;

[0040] Figure 2 A flowchart of a fault signal acquisition and data extraction process provided in an embodiment of the present application;

[0041] Figure 3 A flowchart of fault analysis and multi-platform forwarding processing provided in an embodiment of the present application;

[0042] Figure 4 A data flow diagram provided in an embodiment of the present application;

[0043] Figure 5 A schematic diagram of the structure of a vehicle fault sensing and processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0044] As mentioned above, existing methods suffer from low utilization of vehicle data. Specifically, in the era of the rapid development of the Internet of Vehicles, a vast amount of vehicle data is transmitted across the network, including data on vehicle failures. Due to the lack of a guiding process and targeted processing engine, much of this valuable data cannot be effectively utilized, related failures cannot be detected promptly, and a good communication bridge with after-sales systems cannot be established. This prevents the after-sales system from providing effective feedback and, consequently, provides ineffective and timely feedback on vehicle failure resolution methods.

[0045] To address the aforementioned issues, embodiments of the present application provide a method for vehicle fault perception and processing. The method comprises first obtaining message data representing vehicle fault information from a system cache and parsing the message data to obtain key characteristic information corresponding to the vehicle. This key characteristic information is then filtered based on preset fault handling rules to determine target characteristic data that meets the requirements for subsequent flow. Finally, this target characteristic data is transmitted to a platform processing system for information feedback by the after-sales system.

[0046] In this way, the key feature information corresponding to the vehicle fault is processed through preset fault handling rules and sent to the platform processing system, thereby improving the utilization rate of vehicle data.

[0047] It should be noted that the vehicle fault sensing and processing method and related products provided in this application can be applied in the field of computer technology. The above is only an example and does not limit the application field of the vehicle fault sensing and processing method and related products provided in this application.

[0048] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0049] Figure 1 A flow chart of a method for sensing and handling vehicle faults provided in an embodiment of the present application. Figure 1 As shown, a method for sensing and handling vehicle faults provided in an embodiment of the present application may include:

[0050] S101: Acquire message data representing vehicle fault information from a system cache.

[0051] In practical applications, the system cache stores a large amount of vehicle information (message data) collected in real time via TCP / MQTT channels. The intelligent sensing and data processing engine (the device that senses and processes vehicle faults) retrieves the current vehicle's message data from the system cache and processes it. This captured message data includes messages that indicate vehicle faults.

[0052] In addition, since the methods of obtaining message data are different, this application implements a description of a possible acquisition method.

[0053] In one embodiment, before obtaining the message data representing the vehicle fault information from the system cache, the method further includes:

[0054] Based on the vehicle's internal data flow message queue, the client monitors the data transmission channel to pull message data representing vehicle fault information;

[0055] The message data is stored in a system cache.

[0056] In actual applications, the intelligent perception and data processing engine connects to the internal data flow message queue, Kafka. Kafka is an essential data transfer middleware for massive data flow in non-blocking cloud scenarios. It provides a non-blocking and efficient message queue implementation. The message queue's broker uses a client-side listening mechanism to pull and collect binary message data collected from TCP / MQTT channels in real time and finally store it in the system cache.

[0057] Figure 2 This is a flowchart of a fault signal acquisition and data extraction process provided by an embodiment of the present application. Figure 2 As shown in the figure, vehicle data collection, storage, and retrieval are all implemented based on message queues. During the data collection process, a binary byte stream (message data representing vehicle fault information) undergoes authentication, data decryption, and data encapsulation before being converted into a byte stream and sent to the message queue or even stored in the system cache. The intelligent perception and data processing engine pulls this message data from the message queue or system cache and deserializes it into a byte stream and string to obtain the original data.

[0058] S102: Analyze the message data to obtain key feature information corresponding to the vehicle.

[0059] In practical applications, collected message data is in binary format, and the data fed back to the after-sales system for review by after-sales personnel must be in a universally understandable format. Similarly, to facilitate subsequent extraction and use, the intelligent perception and data processing engine needs to parse the message data and extract key feature information corresponding to the faulty vehicle.

[0060] In addition, since the methods of parsing message data are different, the embodiments of the present application can illustrate a possible parsing method.

[0061] In one case, S102: parsing the message data to obtain key feature information corresponding to the vehicle may specifically include:

[0062] Deserialize the message data using a deserialization tool;

[0063] The deserialized message data is parsed based on a preset data interaction protocol to extract key feature information corresponding to the vehicle; the key feature information includes vehicle identification code, fault type, fault code, fault collection time and vehicle location.

[0064] In practical applications, a deserialization tool refers to a tool or program that helps users convert serialized objects into usable objects in Java or other programming languages. The binary message data that the intelligent perception and data processing engine listens to and pulls from the system cache is a serialized data that is easy to save and transmit. Therefore, the intelligent perception and data processing engine needs to use a deserialization tool to parse the message data, such as deserializing byte streams and deserializing strings based on the established data interaction protocol, and finally obtain the key feature information of the faulty vehicle and save it in a custom data entity container for easy later extraction and use. It is understandable that the key feature information of the faulty vehicle should include vehicle identification code, fault category, fault code, fault collection time, and vehicle location, etc.

[0065] S103: Based on preset fault handling rules, the key feature information is screened to determine target feature data that meets the requirements for subsequent flow.

[0066] In actual applications, technicians will upload fault handling rules corresponding to different faults of different vehicle models. Once the intelligent perception and data processing engine detects and determines the fault type of the faulty vehicle, it will filter key feature information based on the preset fault handling rules corresponding to the fault, and select high-value data (target feature data) for subsequent data flow.

[0067] In addition, since the methods for screening key feature information are different, the embodiments of the present application can illustrate a possible screening method.

[0068] In one case, S103: based on a preset fault handling rule, the key feature information is screened to determine target feature data that meets the requirements for subsequent flow, which may specifically include:

[0069] Perform rule query based on the key feature information to determine a preset fault handling rule corresponding to the vehicle fault;

[0070] parsing the preset fault handling rule, and processing the key feature information according to the preset fault handling rule to obtain first feature data;

[0071] A validity judgment is performed on the first feature data, and the first feature data that passes the validity judgment is used as target feature data.

[0072] In actual applications, fault handling rules for different models and different faults are generally designed separately by technical personnel and input into the processing engine server. By turning on and off the corresponding rules, the forwarding of different faults can be turned on or off. Fault handling rules generally need to include several aspects such as determining the fault to be handled, the fault handling frequency, additional information that needs to be spliced, and the forwarding destination, and the data content in the fault handling rules corresponding to different faults is generally different. Specifically, the key feature information obtained is processed through a chain plus concurrent data stream processing mode. The intelligent perception and data processing engine first determines the preset fault handling rules corresponding to the vehicle fault based on key feature information such as vehicle model, vehicle identification code, and fault type. The key feature information is then processed according to the preset fault handling rules, such as data splicing, to obtain the first feature data. The extracted key feature information is then incorporated into the preset fault handling rules. The vehicle master data is pre-loaded into the cache REDIS. The extracted vehicle identification code is validated in the cache, and distributed frequency control is performed to avoid repeated and multiple processing due to data concurrency. Fault rule logic is then determined in memory, and the key feature information that has passed the processing flow is transferred to the forwarding process engine as a backup for high-value data (target feature data) to be processed. It is understandable that the cache REDIS is crucial in massive data and high-concurrency scenarios, and is the key to implementing data judgment and distributed judgment.

[0073] In addition, since the methods for processing key feature information are different, the embodiments of the present application can illustrate a possible processing method.

[0074] In one case, the parsing of the preset fault handling rule and processing the key feature information according to the preset fault handling rule to obtain the first feature data includes:

[0075] If the preset fault handling rule does not specify a handling frequency corresponding to the vehicle fault, determining the forwarding destination and the data information that needs to be additionally spliced ​​with the key feature information according to the preset fault handling rule;

[0076] Based on the internal basic service capabilities, the data information is obtained through a request-response protocol and is spliced ​​with the key feature information to obtain the first feature data.

[0077] In actual applications, combined with the above, the fault handling rules include several aspects such as the faults that need to be handled, the frequency of fault handling, additional information that needs to be spliced, and the forwarding destination. After determining the preset fault handling rules corresponding to the vehicle fault, the intelligent perception and data processing engine parses the rules to determine the frequency control, forwarding type, and data splicing content. If the preset fault handling rules corresponding to the vehicle fault do not specify the processing frequency, it is only necessary to determine the forwarding type (push to users, push to after-sales platforms, push to internal message queues, etc.) according to the forwarding destination defined in the rule; and according to the data requirements that need to be completed as defined in the rules, with the help of internal basic service capabilities, perform relevant data query and splicing through HTTP (request-response protocol) requests to obtain the first feature data.

[0078] In addition, since the provisions in the preset fault handling rules are not the same, and different provisions correspond to different handling methods, this application implements another possible handling method to illustrate.

[0079] In one embodiment, the method further comprises:

[0080] If the preset fault handling rule specifies a processing frequency corresponding to a vehicle fault, the LUA script is used to control the frequency of the vehicle fault.

[0081] In actual applications, if the rules specify the frequency of handling vehicle faults, LUA scripts are used through REDIS to use SET, EX, and NX instructions to achieve frequency control of the same fault on the same vehicle.

[0082] Figure 3 This is a flowchart of a fault analysis and multi-platform forwarding process provided by the embodiment of the present application. Figure 3As shown, when a vehicle breaks down and reports a fault signal, the dynamic rule processing engine (intelligent perception and data processing engine) retrieves the KAFKA consumer object from the resource plaza (system cache) to pull data and perform data parsing. For example, data parsing and object packaging are performed based on a custom message protocol. Then, through a chained concurrent data stream processing model, rule matching is performed based on the parsing results. For example, thread a matches rule A and must complete Task 1 corresponding to rule A; thread b matches rule B and must complete Task 2 corresponding to rule B, and so on. Different rules generally include several tasks, such as fault (determining the fault to be handled), frequency (fault handling frequency), information (additional information to be spliced), and destination (forwarding destination). The specific data content corresponding to tasks in different rules generally varies. The process is considered complete after the corresponding task is completed, and the processed data is then sent to the destination corresponding to the rule parsing. Destinations include users, after-sales platforms, business message queues, and other destinations. Furthermore, if the rule specifies the frequency of vehicle fault handling, LUA scripts are used to control the frequency of vehicle faults.

[0083] S104: The target feature data is transmitted to the platform processing system for the after-sales system to conduct information feedback.

[0084] In actual applications, the intelligent perception and data processing engine forwards the processed target feature data to the rule-defined platform processing system, allowing the after-sales system to provide information feedback and provide users with troubleshooting guidance, thus fully converting digital information into valuable information. It can be understood that the platform processing system is the forwarding destination obtained by parsing the preset troubleshooting rules, and can include users, after-sales platforms, business message queues, and other processing systems.

[0085] In addition, since the methods of constructing channels are different, the embodiments of the present application can illustrate one possible construction method.

[0086] In one embodiment, before transmitting the characteristic data to the platform processing system for information feedback by the after-sales system, the method further includes:

[0087] Establish a communication mechanism with the platform processing system through network connection.

[0088] In actual applications, the intelligent perception and data processing engine needs to build a communication mechanism with the platform processing system (high-value data flow platform such as after-sales) through network connection, and then send the high-value data (target feature data) that finally meets the conditions to the platform processing system.

[0089] Figure 4 A data flow diagram provided in this application embodiment. Figure 4 As shown in the figure, during normal vehicle use, a sudden incident causes a collision, triggering a vehicle failure and uploading a fault signal. The vehicle body information collection component then transmits the collision signal to the cloud via a TCP / MQTT channel, completing fault collection. The intelligent perception and data processing engine then captures the faulty vehicle's message data from the message queue and performs fault analysis. For example, it collects the vehicle identification code, fault location, and basic user information, and makes the necessary judgments. Finally, the fault is transmitted to the after-sales platform, which handles after-sales processing and fault follow-up. This includes, but is not limited to, returning to the user based on the received fault information, confirming the fault situation, and providing necessary rescue services.

[0090] In summary, the present application first obtains message data representing vehicle fault information from the system cache and parses the message data to obtain key feature information corresponding to the vehicle. Then, based on preset fault handling rules, the key feature information is screened to determine target feature data that meets the requirements for subsequent circulation. Finally, the target feature data is transmitted to the platform processing system for information feedback by the after-sales system. In this way, the key feature information corresponding to the vehicle fault is processed by the preset fault handling rules and sent to the platform processing system, thereby improving the utilization rate of vehicle data.

[0091] Based on the vehicle fault sensing and processing method provided in the above embodiment, the present application also provides a vehicle fault sensing and processing device. The vehicle fault sensing and processing device is described below in conjunction with the embodiments and drawings.

[0092] Figure 5 A schematic diagram of the structure of a vehicle fault sensing and processing device provided in an embodiment of the present application. Figure 5 As shown, the vehicle fault sensing and processing device 500 provided in the embodiment of the present application includes:

[0093] An acquisition module, used to obtain message data representing vehicle fault information from a system cache;

[0094] A parsing module, configured to parse the message data to obtain key feature information corresponding to the vehicle;

[0095] A screening module is used to screen the key feature information based on preset fault handling rules to determine target feature data that meets the requirements for subsequent flow;

[0096] The transmission module is used to transmit the target feature data to the platform processing system for the after-sales system to conduct information feedback.

[0097] As an implementation method, with respect to how to obtain message data, the above-mentioned vehicle fault sensing and processing device 500 further includes: a cache module;

[0098] The cache module is used to pull message data representing vehicle fault information from the data transmission channel through the client monitoring mechanism based on the vehicle's internal data flow message queue;

[0099] The message data is stored in a system cache.

[0100] As an implementation method, regarding how to parse message data, the above-mentioned parsing module is specifically used to:

[0101] Deserialize the message data using a deserialization tool;

[0102] The deserialized message data is parsed based on a preset data interaction protocol to extract key feature information corresponding to the vehicle; the key feature information includes vehicle identification code, fault type, fault code, fault collection time and vehicle location.

[0103] As an implementation method, regarding how to screen key feature information, the screening module specifically includes: a query module, a processing module, and a judgment module;

[0104] A query module, configured to perform rule query based on the key feature information to determine a preset fault handling rule corresponding to the vehicle fault;

[0105] a processing module, configured to parse the preset fault processing rules and process the key feature information according to the preset fault processing rules to obtain first feature data;

[0106] The judgment module is used to judge the validity of the first feature data and use the first feature data that passes the validity judgment as target feature data.

[0107] As an implementation method, regarding how to process key feature information, the processing module is specifically used to:

[0108] If the preset fault handling rule does not specify a handling frequency corresponding to the vehicle fault, determining the forwarding destination and the data information that needs to be additionally spliced ​​with the key feature information according to the preset fault handling rule;

[0109] Based on the internal basic service capabilities, the data information is obtained through a request-response protocol and is spliced ​​with the key feature information to obtain the first feature data.

[0110] As an implementation method, how to process the key feature information, the above processing module is specifically further used to:

[0111] If the preset fault handling rule specifies a processing frequency corresponding to a vehicle fault, the LUA script is used to control the frequency of the vehicle fault.

[0112] As an implementation method, regarding how to construct a channel, the above-mentioned vehicle fault sensing and processing device 500 further includes: a construction module;

[0113] A building block used to establish a communication mechanism with the platform processing system through a network connection.

[0114] In summary, the present application first obtains message data representing vehicle fault information from the system cache and parses the message data to obtain key feature information corresponding to the vehicle. Then, based on preset fault handling rules, the key feature information is screened to determine target feature data that meets the requirements for subsequent circulation. Finally, the target feature data is transmitted to the platform processing system for information feedback by the after-sales system. In this way, the key feature information corresponding to the vehicle fault is processed by the preset fault handling rules and sent to the platform processing system, thereby improving the utilization rate of vehicle data.

[0115] In addition, the present application also provides a device for vehicle fault perception and processing, including: a memory for storing a computer program; a processor for implementing the steps of the vehicle fault perception and processing method as described in any of the above items when executing the computer program.

[0116] In addition, the present application also provides a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for vehicle fault perception and processing as described in any one of the above items are implemented.

[0117] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for sensing and handling vehicle faults, characterized in that: The method comprises: Acquire message data representing vehicle fault information from a system cache; Parsing the message data to obtain key feature information corresponding to the vehicle; Based on the preset fault handling rules, the key feature information is screened to determine the target feature data that meets the subsequent flow; The target feature data is transmitted to the platform processing system for information feedback by the after-sales system.

2. The method according to claim 1, characterized in that Before acquiring the message data representing the vehicle fault information from the system cache, the method further includes: Based on the vehicle's internal data flow message queue, the client monitors the mechanism to pull the message data representing the vehicle fault information from the data transmission channel; The message data is stored in the system cache.

3. The method according to claim 1, characterized in that The parsing of the message data to obtain key feature information corresponding to the vehicle includes: Deserialize the message data using a deserialization tool; The deserialized message data is parsed based on a preset data interaction protocol to extract key feature information corresponding to the vehicle; the key feature information includes a vehicle identification code, a fault type, a fault code, a fault collection time, and a vehicle location.

4. The method according to claim 1, characterized in that: The key feature information is screened based on the preset fault handling rules to determine the target feature data that meets the subsequent flow, including: Perform rule query based on the key feature information to determine a preset fault handling rule corresponding to the vehicle fault; parsing the preset fault processing rule, and processing the key feature information according to the preset fault processing rule to obtain first feature data; A validity judgment is performed on the first feature data, and the first feature data that passes the validity judgment is used as target feature data.

5. The method according to claim 4, characterized in that The parsing of the preset fault processing rule and processing the key feature information according to the preset fault processing rule to obtain the first feature data includes: If the preset fault handling rule does not specify the processing frequency corresponding to the vehicle fault, determining the forwarding destination and the data information that needs to be additionally spliced ​​with the key feature information according to the preset fault handling rule; Based on the internal basic service capability, the data information is obtained through a request-response protocol and is spliced ​​with the key feature information to obtain the first feature data.

6. The method according to claim 5, characterized in that The method further comprises: If the preset fault handling rule specifies the processing frequency corresponding to the vehicle fault, the LUA script is used to control the frequency of the vehicle fault.

7. The method according to claim 1, characterized in that Before transmitting the target feature data to the platform processing system for information feedback by the after-sales system, the method further includes: Through network connection, a communication mechanism is established with the platform processing system.

8. A vehicle fault sensing and processing device, characterized in that: include: An acquisition module, used for acquiring message data representing vehicle fault information from a system cache; A parsing module, used to parse the message data to obtain key feature information corresponding to the vehicle; A screening module, used to screen the key feature information based on preset fault handling rules to determine target feature data that meets the requirements for subsequent flow; The transmission module is used to transmit the target feature data to the platform processing system for the after-sales system to conduct information feedback.

9. A vehicle fault sensing and processing device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the method for vehicle fault perception and processing as claimed in any one of claims 1 to 7 when executing the computer program.

10. A readable storage medium, characterized in that: The readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for vehicle fault perception and processing as described in any one of claims 1 to 7.

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