Vehicle-mounted fault processing method, device, equipment, medium and vehicle
By receiving and analyzing user fault description text, determining event categories and query interfaces, and generating fault analysis responses based on data query results, the problem of existing diagnostic systems relying on databases is solved, enabling flexible and diverse fault analysis.
Patent Information
- Application Number
- CN202410742996.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-06-08
- Publication Date
- 2025-12-12
AI Technical Summary
Existing diagnostic systems rely on manually maintained databases, making it difficult to answer questions using unstructured knowledge, and resulting in monotonous and rigid responses.
By receiving users' fault description text, text analysis is performed to determine the event category and query interface. Combined with the data query results, a fault analysis response is generated, including fault analysis text and solution text.
It achieves highly scalable and diverse fault analysis and response capabilities, accurately identifying the cause of the fault and providing solutions based on the fault description text.
Smart Images
Figure CN121117136A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of computer technology, and in particular to a vehicle-mounted fault handling method, apparatus, equipment, medium, and vehicle. Background Technology
[0002] Existing diagnostic systems mainly rely on retrieval and ranking based on relational or graph databases to achieve question answering. This approach transforms the question answering task into ranking question-answer pairs in the database, and replies to the user with the most similar answers that meet or exceed the similarity threshold.
[0003] However, existing diagnostic systems based on database retrieval technology rely on manual maintenance of the database, and the scope of answers is limited to the structured knowledge already existing in the question-and-answer database. It is difficult to use unstructured knowledge to answer questions outside the scope of the database, and the response language is relatively monotonous and rigid. Summary of the Invention
[0004] To address the aforementioned technical problems, this disclosure provides a vehicle-mounted fault handling method, apparatus, equipment, medium, and vehicle.
[0005] Firstly, this disclosure provides a vehicle-mounted fault handling method, including:
[0006] Receive the user's fault description text;
[0007] The fault description text is analyzed to obtain the corresponding event category and query interface;
[0008] Data can be queried using the query interface and the event category to obtain the corresponding data query results;
[0009] The fault analysis is performed by combining the fault description text, the event category, and the data query results, and a corresponding fault analysis response is generated. The fault analysis response includes fault analysis text and fault resolution text.
[0010] Secondly, this disclosure provides an on-board fault handling device, including:
[0011] The text receiving module is used to receive the user's fault description text;
[0012] The text analysis module is used to perform text analysis processing on the fault description text to obtain the corresponding event category and query interface;
[0013] The signal query module is used to query data through the query interface and the event category to obtain the corresponding data query results.
[0014] The fault analysis module is used to perform fault analysis by combining the fault description text, the event category, and the data query results, and generate a corresponding fault analysis response, which includes fault analysis text and fault resolution text.
[0015] Thirdly, this disclosure provides an on-board fault handling device, including:
[0016] processor;
[0017] Memory, used to store executable instructions;
[0018] The processor is used to read executable instructions from memory and execute the executable instructions to implement the vehicle fault handling method of the first aspect.
[0019] Fourthly, this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to implement the vehicle fault handling method of the first aspect.
[0020] Fifthly, this disclosure provides a vehicle including the on-board fault handling device described above.
[0021] The technical solution provided in this disclosure has the following advantages compared with the prior art:
[0022] The vehicle-mounted fault handling method, apparatus, device, medium, and vehicle disclosed in this embodiment can receive a user's fault description text, then perform text analysis processing on the fault description text to obtain the corresponding event category and query interface, then perform data query through the query interface and the event category to obtain the corresponding data query results, and finally combine the fault description text, the event category, and the data query results to perform fault analysis and generate a corresponding fault analysis response. The fault analysis response includes fault analysis text and fault resolution text. Thus, the event category and corresponding query interface for resolving the fault problem are first determined based on the fault description text, then the cause of the fault is further determined based on the obtained data query results, and finally a fault analysis response with high scalability and rich content diversity is generated. Attached Figure Description
[0023] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.
[0024] Figure 1 A schematic flowchart illustrating an embodiment of the vehicle fault handling method provided in this disclosure;
[0025] Figure 2 A flowchart illustrating another vehicle-mounted fault handling method provided in this embodiment of the present disclosure;
[0026] Figure 3 A flowchart illustrating yet another vehicle-mounted fault handling method provided in this embodiment of the present disclosure;
[0027] Figure 4 A schematic flowchart illustrating another vehicle-mounted fault handling method provided in this embodiment of the present disclosure;
[0028] Figure 5 This is a schematic diagram of the structure of an on-board fault handling device provided in an embodiment of the present disclosure;
[0029] Figure 6 This is a schematic diagram of the structure of an on-board fault handling device provided in an embodiment of the present disclosure. Detailed Implementation
[0030] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.
[0031] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.
[0032] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.
[0033] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.
[0034] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".
[0035] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
[0036] To address the aforementioned problems, this disclosure provides an in-vehicle fault handling method, apparatus, device, medium, and vehicle. The following will first combine... Figures 1 to 4 The vehicle fault handling method provided in the embodiments of this disclosure will be described in detail.
[0037] Figure 1 A schematic flowchart of an on-board fault handling method provided in an embodiment of this disclosure is shown.
[0038] In this embodiment of the disclosure, the vehicle fault handling method can be executed by an electronic device. Specifically, the electronic device may include, but is not limited to, mobile terminals such as computer equipment, mobile phones, in-vehicle equipment, vehicle controllers, tablet computers, and wearable devices.
[0039] like Figure 1 As shown, the vehicle fault handling method may include the following steps.
[0040] S110, Receive the user's fault description text.
[0041] In this embodiment of the disclosure, the electronic device can receive a user's fault description text.
[0042] Optionally, the fault description text can be text used to describe the fault content.
[0043] Specifically, users can input fault description text into the electronic device, such as through text input, voice input, etc. The electronic device can receive the fault description text from the user. For example, the fault description text can be "Why is the tire pressure abnormal?" or "Why is the reversing camera not working?", etc. There are no restrictions here.
[0044] S120. Perform text analysis processing on the fault description text to obtain the corresponding event category and query interface.
[0045] In this embodiment of the disclosure, the electronic device can perform text analysis processing on the fault description text to obtain the corresponding event category and query interface.
[0046] Optionally, text analysis processing can be the analysis and processing of keywords in the fault description text.
[0047] Optionally, the query interface can be an interface used to query corresponding data. For example, the query interface can be an Application Programming Interface (API). The query interface may include a real-time signal query interface and a reasonable signal range query interface.
[0048] Optionally, the real-time signal query interface can be an interface for querying real-time signal values in vehicles.
[0049] Optionally, the reasonable signal range query interface can be an interface for querying the reasonable range of a certain signal.
[0050] Optionally, the event category can be used to characterize the type of failure that occurred in the fault text. Specifically, when the fault description text belongs to the fault diagnosis domain, the corresponding event category can be a fault diagnosis category; when the fault description text belongs to the question-and-answer domain, the corresponding event category can be a question-and-answer category.
[0051] Specifically, after receiving the fault description text, the electronic device can perform text analysis processing on the fault description text to obtain the corresponding query interface and event category. The query interface may include a real-time signal query interface and a reasonable signal range query interface, and the event category may include fault diagnosis type, question answering type, etc.
[0052] S130. Perform data query through the query interface and the event category to obtain the corresponding data query results.
[0053] In this embodiment of the disclosure, the electronic device can perform data queries through the query interface and the event category to obtain the corresponding data query results.
[0054] Optionally, data query can be used to query the corresponding signal through a query interface.
[0055] Optionally, the data query results can include multiple signals found.
[0056] Specifically, after obtaining the query interface and event category, the electronic device can perform data queries through the query interface and the event category to obtain the corresponding data query results. For example, for the event "Why is the tire pressure abnormal?", the event category is fault diagnosis. The electronic device can query the vehicle's real-time tire pressure through the real-time signal query interface and query the reasonable tire pressure range through the reasonable signal range query interface. In this case, the data is numerical. For example, for the event "Why is the reversing camera not working?", the event category is fault diagnosis. The electronic device can query the vehicle's real-time rear camera status through the real-time signal query interface and query the reasonable rear camera status through the reasonable signal range query interface. In this case, the data is Boolean.
[0057] S140. Combine the fault description text, the event category, and the data query results to perform fault analysis and generate a corresponding fault analysis response. The fault analysis response includes fault analysis text and fault resolution text.
[0058] In this embodiment of the disclosure, the electronic device can perform fault analysis by combining the fault description text, the event category, and the data query results, and generate a corresponding fault analysis response.
[0059] Alternatively, fault analysis can be performed on signal faults in the text.
[0060] Optionally, the fault analysis response can be a fault analysis result used to reply to the user. The fault analysis response includes fault analysis text and fault resolution text.
[0061] Specifically, after receiving the data query results, the electronic device can perform fault analysis by combining the fault description text, the event category, and the data query results, and generate a corresponding fault analysis response. The fault analysis response includes fault analysis text and fault resolution text. The fault analysis text can be a response to the user explaining the cause of the fault, while the fault resolution text can be a response to the user providing suggestions for resolving the fault.
[0062] Therefore, in this embodiment of the disclosure, the system can receive a user's fault description text, then perform text analysis processing on the fault description text to obtain the corresponding event category and query interface, then perform data query through the query interface and the event category to obtain the corresponding data query results, and finally combine the fault description text, the event category, and the data query results to perform fault analysis and generate a corresponding fault analysis response. The fault analysis response includes fault analysis text and fault resolution text. Thus, the system first determines the event category and corresponding query interface for resolving the fault based on the fault description text, then further determines the cause of the fault by combining the obtained data query results, and finally generates a fault analysis response with high scalability and rich content diversity.
[0063] Optionally, S120 may specifically include: inputting the fault description text into a pre-trained text analysis model; extracting keywords from the fault description text using the text analysis model, and determining the event category as a fault diagnosis category based on the keywords; and generating the query interface corresponding to the fault based on the fault diagnosis category and the fault description text.
[0064] In this embodiment of the disclosure, the electronic device can input the fault description text into a pre-trained text analysis model.
[0065] Alternatively, the pre-trained text analysis model can be a pre-trained large language model used to extract keywords from the text.
[0066] Specifically, after obtaining the fault description text, the electronic device can input the fault description text into a pre-trained text analysis model.
[0067] Furthermore, the electronic device can extract keywords from the fault description text using the text analysis model and determine the event category as a fault diagnosis category based on the keywords.
[0068] Optionally, the keywords can be keywords used to characterize the fault problem.
[0069] Specifically, the electronic device can extract keywords from the fault description text using the text analysis model and determine the event category as a fault diagnosis category based on the keywords. For example, for the fault description text "Why is the tire pressure abnormal?", determining the corresponding event category yields a fault diagnosis type; for the fault description text "Why isn't the reversing camera working?", determining the corresponding event category yields a fault diagnosis type; and for the fault description text "How do I adjust the seat?", determining the corresponding event category yields a question-and-answer type.
[0070] Furthermore, the electronic device can generate the corresponding query interface based on the fault diagnosis category and the fault description text.
[0071] For example, for the fault description text "Why is the tire pressure abnormal?", the text analysis model extracts the keywords from the text, specifically the keyword "tire pressure", and generates the corresponding signal query interfaces, such as the real-time signal query interface (tire pressure) and the reasonable signal range query interface (tire pressure); for the fault description text "Why is the reversing camera not working?", the text analysis model extracts the keywords from the text, specifically the keyword "reversing camera", and generates the corresponding signal query interfaces, such as the real-time signal query interface (rear camera) and the reasonable signal range query interface (rear camera).
[0072] Figure 2 A flowchart illustrating another vehicle fault handling method provided in an embodiment of this disclosure is shown.
[0073] like Figure 2As shown, taking the fault description text "Why is the tire pressure abnormal?" as an example, the user can input the fault description text "Why is the tire pressure abnormal?" The electronic device can input the fault description text into a pre-trained Large Language Model (LLM) (Text Analysis Model) for text analysis processing, thereby obtaining the event category as a numerical event category in vehicle fault diagnosis, and generating the corresponding query interface API, such as the real-time signal query interface (tire pressure) and the reasonable signal range query interface (tire pressure).
[0074] Optionally, after obtaining the query interface and event category, the electronic device can perform data queries through the query interface and the event category to obtain the corresponding data query results.
[0075] For example, given the fault description text "The tire pressure is abnormal," and the event category is fault diagnosis, the electronic device can query the vehicle's real-time tire pressure signal through the real-time signal query interface (tire pressure) to obtain the data query results: "Left front tire: 2.5 bar, Right front tire: 2.6 bar, Left rear tire: 2.6 bar, Right rear tire: 2.3 bar." Then, it can query the reasonable range of the tire pressure signal through the reasonable signal range query interface (tire pressure) to obtain the data query results: "Left front tire: 2.3-2.5 bar, Right front tire: 2.3-2.5 bar, Left rear tire: 2.5-2.7 bar, Right rear tire: 2.5-2.7 bar."
[0076] For example, regarding the fault description text "Why is the reversing camera not working?", the event category is fault diagnosis. The electronic device can query the real-time status of the vehicle's rear camera through the real-time signal query interface (rear camera) and obtain the data query results: "Online: True, Obstructed: True". Then, it can query the reasonable status of the rear camera through the reasonable signal range query interface (rear camera) and obtain the data query results: "Online: True, Obstructed: False".
[0077] Optionally, before inputting the fault description text into the pre-trained text analysis model, the vehicle fault handling method may further include: extracting data from historical fault data to obtain fault triple data, wherein the fault triple data includes historical fault description text, historical fault signals, and historical fault analysis responses; and training the text analysis model to be trained using the historical fault description text and the historical fault signals to obtain the text analysis model.
[0078] In this embodiment of the disclosure, the electronic device can extract data from historical fault data to obtain fault triplet data.
[0079] Optionally, historical fault data can be data from historical fault diagnosis.
[0080] Optionally, the fault triplet data can include historical fault description text, historical fault signals, and historical fault analysis responses.
[0081] Furthermore, the electronic device can use the historical fault description text and the historical fault signals to train the text analysis model to obtain the text analysis model.
[0082] Optionally, S140 may specifically include: concatenating the fault description text, the event category, and the data query result to obtain a corresponding concatenated text; inputting the concatenated text into a pre-trained fault analysis model; and performing fault analysis on the concatenated text through the fault analysis model to generate a corresponding fault analysis response.
[0083] In this embodiment of the disclosure, the electronic device can concatenate the fault description text, the event category, and the data query result to obtain the corresponding concatenated text, and input the concatenated text into a pre-trained fault analysis model.
[0084] Alternatively, the fault analysis model can be a pre-trained large language model for analyzing fault signals.
[0085] Specifically, after obtaining the query interface and the data query results, the electronic device can concatenate the fault description text, the event category, and the data query results to obtain the corresponding concatenated text, and input the concatenated text into a pre-trained fault analysis model.
[0086] Furthermore, the electronic device can perform fault analysis on the spliced text using the fault analysis model and generate a corresponding fault analysis response.
[0087] Specifically, the electronic device inputs the spliced text into the fault analysis model, enabling the model to perform fault analysis and generate corresponding fault analysis responses. For example, for the fault description text "Why is the tire pressure abnormal?", the fault analysis model analyzes the spliced text and obtains the following fault cause response: The reasonable tire pressure range for the front tires is 2.3-2.5 bar, and the current right front tire pressure is 2.6 bar; it is recommended to release some air. The reasonable tire pressure range for the rear tires is 2.5-2.7 bar, and the current right rear tire pressure is 2.3 bar; it is recommended to inflate some air. The pressures of the other tires are normal. The fault resolution suggestion response is: If the tire pressure still cannot be maintained within the normal range after the operation, it is recommended to call customer service for further inspection. As another example, for the fault description text "Why isn't the reversing camera working?", the fault analysis model analyzes the spliced text and obtains the following fault cause response: The reversing camera is temporarily unusable because the rear camera is obstructed. The fault resolution suggestion response is: It is recommended to clear any obstructions to the rear camera's view, provided it is safe to do so. If the reversing camera still does not work properly after the operation, it is recommended to call customer service for further inspection.
[0088] Optionally, before inputting the concatenated text into the pre-trained fault analysis model, the vehicle fault handling method may further include: training the fault analysis model to be trained by using historical fault description text, historical fault signals and historical fault analysis responses from the fault triplet data, thereby obtaining the fault analysis model, which includes multiple structured data.
[0089] In this embodiment of the disclosure, the electronic device can train the fault analysis model to be trained by using historical fault description text, historical fault signals and historical fault analysis responses in the fault triplet data.
[0090] Optionally, the structured data can be a pre-defined data structure that includes data from multiple dimensions. Different event categories can correspond to different data structures. For example, the fault diagnosis category corresponds to a fault diagnosis data structure, which may specifically include: fault description text data, event category data, data query result data, and fault analysis response data; other data structures are also possible, and this is not limited here.
[0091] Optionally, the fault analysis model is used to perform fault analysis on the concatenated text and generate a corresponding fault analysis response, including: determining target structural data from multiple structural data based on the concatenated text, wherein the target structural data includes the fault description text data, the event category data, the data query result data, and the fault analysis response data; filling the concatenated text into the target structural data, and analyzing the concatenated text to generate a corresponding fault analysis response.
[0092] In this embodiment of the disclosure, the electronic device can determine the target structural data from among the multiple structural data based on the spliced text.
[0093] Optionally, the target structure data may include fault description text data, event category data, data query result data, and fault analysis response data.
[0094] Specifically, the electronic device can determine the corresponding target structural data from multiple structural data based on the concatenated text. The target structural data may include fault description text data, event category data, data query result data, and fault analysis response data.
[0095] Furthermore, the electronic device can fill the spliced text into the target structure data, analyze the spliced text, and generate a corresponding fault analysis response.
[0096] The concatenated text is filled into the target structure data to clarify the specific content of each data type. Then, based on the specific content of each data type, the content of the unfilled parts in the target structure data is analyzed to obtain the fault analysis response.
[0097] Figure 3 A flowchart illustrating another vehicle fault handling method provided in an embodiment of this disclosure is shown.
[0098] like Figure 3 As shown, taking the fault description text "The tire pressure is abnormal" as an example, the system can input the concatenated text into a Large Language Model (LLM) for fault analysis. The resulting fault cause is: The reasonable tire pressure range for the front tires is 2.3-2.5 bar; the current right front tire pressure is 2.6 bar, so it is recommended to release some air. The reasonable tire pressure range for the rear tires is 2.5-2.7 bar; the current right rear tire pressure is 2.3 bar, so it is recommended to inflate some air. The pressures of the remaining tires are normal. The system also provides troubleshooting suggestions: If the tire pressure still cannot be maintained within the normal range after these steps, it is recommended to call customer service for further inspection.
[0099] Figure 4 A flowchart illustrating another vehicle fault handling method provided in an embodiment of this disclosure is shown.
[0100] like Figure 4As shown, taking the fault description text "The tire pressure is abnormal" as an example, the user can input the fault description text "The tire pressure is abnormal". The electronic device can input the fault description text into a pre-trained Large Language Model (LLM) for text analysis processing, thereby obtaining the event category as the fault diagnosis category and generating the corresponding query interface API, such as the real-time signal query interface (tire pressure) and the reasonable signal range query interface (tire pressure). Then, the electronic device can query the vehicle's real-time tire pressure signal through the real-time signal query interface (tire pressure) and obtain the data query result: "Left front tire: 2.5 bar, right front tire: 2.6 bar, left rear tire: 2.6 bar, right rear tire: 2.3 bar". Then, it can query the reasonable range of the tire pressure signal through the reasonable signal range query interface (tire pressure) and obtain the data query result: "Left front tire: 2.3-2.5 bar, right front tire: 2.3-2.5 bar, left rear tire: 2.5-2.7 bar, right rear tire: 2.5-2.7 bar". Finally, the system inputs the concatenated text into a Large Language Model (LLM) for fault analysis, obtaining the following fault cause and response: The optimal tire pressure range for the front tires is 2.3-2.5 bar; the current pressure of the right front tire is 2.6 bar, so it is recommended to release some air. The optimal tire pressure range for the rear tires is 2.5-2.7 bar; the current pressure of the right rear tire is 2.3 bar, so it is recommended to inflate some air. The pressures of the remaining tires are normal. The system also provides troubleshooting suggestions: If the tire pressure still cannot be maintained within the normal range after these steps, it is recommended to call customer service for further inspection.
[0101] Figure 5 A schematic diagram of the structure of an on-board fault handling device provided in an embodiment of this disclosure is shown.
[0102] In some embodiments of this disclosure, Figure 5 The vehicle fault handling device shown can be installed in an electronic device. Specifically, the electronic device may include, but is not limited to, mobile terminals such as computer equipment, mobile phones, in-vehicle equipment, vehicle controllers, tablet computers, and wearable devices.
[0103] like Figure 5 As shown, the vehicle-mounted fault handling device 500 may include a text receiving module 510, a text analysis module 520, a signal query module 530, and a fault analysis module 540.
[0104] The text receiving module 510 can be used to receive the user's fault description text.
[0105] The text analysis module 520 can be used to perform text analysis processing on the fault description text to obtain the corresponding event category and query interface.
[0106] The signal query module 530 can be used to query data through the query interface and the event category to obtain the corresponding data query results.
[0107] The fault analysis module 540 can be used to perform fault analysis by combining the fault description text, the event category and the data query results, and generate a corresponding fault analysis response, which includes fault analysis text and fault resolution text.
[0108] Therefore, in this embodiment of the disclosure, the system can receive a user's fault description text, then perform text analysis processing on the fault description text to obtain the corresponding event category and query interface, then perform data query through the query interface and the event category to obtain the corresponding data query results, and finally combine the fault description text, the event category, and the data query results to perform fault analysis and generate a corresponding fault analysis response. The fault analysis response includes fault analysis text and fault resolution text. Thus, the system first determines the event category and corresponding query interface for resolving the fault based on the fault description text, then further determines the cause of the fault by combining the obtained data query results, and finally generates a fault analysis response with high scalability and rich content diversity.
[0109] In some embodiments of this disclosure, the text analysis module 520 may specifically include a first input unit, a first processing unit, and a second processing unit.
[0110] The first input unit can be used to input the fault description text into a pre-trained text analysis model.
[0111] The first processing unit can be used to extract keywords from the fault description text using the text analysis model, and determine the event category as a fault diagnosis category based on the keywords.
[0112] The second processing unit can be used to generate the query interface corresponding to the fault based on the fault diagnosis category and the fault description text.
[0113] In some embodiments of this disclosure, the text analysis module 520 may specifically include a data extraction unit and a first training unit.
[0114] The data extraction unit can be used to extract data from historical fault data before the fault description text is input into the pre-trained text analysis model, and obtain fault triple data, which includes historical fault description text, historical fault signals and historical fault analysis responses.
[0115] The first training unit can be used to train the text analysis model to be trained using the historical fault description text and the historical fault signals, so as to obtain the text analysis model.
[0116] In some embodiments of this disclosure, the fault analysis module 540 may specifically include a second input unit, a third input unit, and a second processing unit.
[0117] The second input unit can be used to concatenate the fault description text, the event category, and the data query results to obtain the corresponding concatenated text.
[0118] The third input unit can be used to input the concatenated text into a pre-trained fault analysis model.
[0119] The third processing unit can be used to perform fault analysis on the spliced text through the fault analysis model and generate a corresponding fault analysis response.
[0120] In some embodiments of this disclosure, the fault analysis module 540 may further include a second training unit.
[0121] The second training unit can be used to train the fault analysis model to be trained by using historical fault description text, historical fault signals and historical fault analysis responses in the fault triplet data before inputting the concatenated text into the pre-trained fault analysis model, thereby obtaining the fault analysis model, which includes multiple structured data.
[0122] In some embodiments of this disclosure, the fault analysis module 540 may further include a structure determination unit and a text filling unit.
[0123] The structure determination unit can be used to determine target structure data from multiple structure data based on the spliced text, the target structure data including the fault description text data, the event category data, the data query result data, and the fault analysis response data.
[0124] The text filling unit can be used to fill the spliced text into the target structure data, analyze the spliced text, and generate a corresponding fault analysis response.
[0125] It should be noted that, Figure 5 The on-board fault handling device 500 shown can perform... Figures 1 to 4 The various steps in the method embodiment shown are implemented. Figures 1 to 4 The processes and effects in the method embodiments shown are not described in detail here.
[0126] Figure 6A schematic diagram of the structure of an on-board fault handling device provided in an embodiment of this disclosure is shown.
[0127] In some embodiments of this disclosure, Figure 6 The vehicle fault handling device shown can be an electronic device that the user wants to handle vehicle faults. Specifically, the electronic device can include, but is not limited to, mobile terminals such as mobile phones, in-vehicle devices, vehicle controllers, tablets, wearable devices, and smart home devices.
[0128] like Figure 6 As shown, the vehicle-mounted fault handling device may include a processor 601 and a memory 602 storing computer program instructions.
[0129] Specifically, the processor 601 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.
[0130] Memory 602 may include a large-capacity storage for information or instructions. For example, and not limitingly, memory 602 may include a hard disk drive (HDD), a floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 602 may include removable or non-removable (or fixed) media. Where appropriate, memory 602 may be internal or external to the integrated gateway device. In a particular embodiment, memory 602 is a non-volatile solid-state memory. In a particular embodiment, memory 602 includes read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (Electrically Programmable ROM, EPROM), an electrically erasable programmable PROM (EEPROM), an electrically alterable ROM (EAROM), or flash memory, or a combination of two or more of these.
[0131] The processor 601 reads and executes computer program instructions stored in the memory 602 to perform the steps of the vehicle fault handling method provided in the embodiments of this disclosure.
[0132] In one example, the on-board fault handling device may further include a transceiver 603 and a bus 604. Wherein, as Figure 6 As shown, the processor 601, memory 602 and transceiver 603 are connected via bus 604 and communicate with each other.
[0133] Bus 604 includes hardware, software, or both. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industrial Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 604 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application considers any suitable bus or interconnection.
[0134] This disclosure also provides a computer-readable storage medium that can store a computer program. When the computer program is executed by a processor, the processor enables the processor to implement the vehicle fault handling method provided in this disclosure.
[0135] The aforementioned storage medium may, for example, include a memory 602 containing computer program instructions, which can be executed by the processor 601 of the vehicle fault handling device to complete the vehicle fault handling method provided in this embodiment. Optionally, the storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), compact disc-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device.
[0136] This disclosure also provides a vehicle including the on-board fault handling device as described above. It is understood that the vehicle may also include a processor, a memory, and a computer program. The computer program is stored in the memory and configured to be executed by the processor to implement the on-board fault handling method provided in this disclosure. The processor and memory are already... Figure 6 The parts of the illustrated embodiments will not be repeated here.
[0137] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.
[0138] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A vehicle-mounted fault handling method, characterized in that, include: Receive the user's fault description text; The fault description text is analyzed to obtain the corresponding event category and query interface; Data can be queried using the query interface and the event category to obtain the corresponding data query results; The fault analysis is performed by combining the fault description text, the event category, and the data query results, and a corresponding fault analysis response is generated. The fault analysis response includes fault analysis text and fault resolution text.
2. The method according to claim 1, characterized in that, The step of performing text analysis on the fault description text to obtain the corresponding event category and query interface includes: Input the fault description text into a pre-trained text analysis model; The text analysis model is used to extract keywords from the fault description text, and the event category is determined as a fault diagnosis category based on the keywords. Based on the fault diagnosis category and the fault description text, a query interface for the corresponding fault is generated.
3. The method according to claim 2, characterized in that, Before inputting the fault description text into the pre-trained text analysis model, the method includes: Data is extracted from historical fault data to obtain fault triplet data, which includes historical fault description text, historical fault signals, and historical fault analysis responses. The text analysis model is obtained by training the text analysis model to be trained using the historical fault description text and the historical fault signals.
4. The method according to claim 1, characterized in that, The step involves combining the fault description text, the event category, and the data query results to perform fault analysis and generate a corresponding fault analysis response, including: The fault description text, the event category, and the data query results are concatenated to obtain the corresponding concatenated text; Input the concatenated text into the pre-trained fault analysis model; The fault analysis model is used to perform fault analysis on the concatenated text, and a corresponding fault analysis response is generated.
5. The method according to claim 4, characterized in that, Before inputting the concatenated text into the pre-trained fault analysis model, the method further includes: The fault analysis model is trained by using historical fault description text, historical fault signals, and historical fault analysis responses from the fault triplet data to obtain the fault analysis model, which includes multiple structured data.
6. The method according to claim 5, characterized in that, The step of performing fault analysis on the concatenated text using the fault analysis model and generating a corresponding fault analysis response includes: Based on the concatenated text, target structural data is determined from multiple structural data, including fault description text data, event category data, data query result data, and fault analysis response data; The concatenated text is filled into the target structure data, and the concatenated text is analyzed to generate a corresponding fault analysis response.
7. A vehicle-mounted fault handling device, characterized in that, include: The text receiving module is used to receive the user's fault description text; The text analysis module is used to perform text analysis processing on the fault description text to obtain the corresponding event category and query interface; The signal query module is used to query data through the query interface and the event category to obtain the corresponding data query results. The fault analysis module is used to perform fault analysis by combining the fault description text, the event category, and the data query results, and generate a corresponding fault analysis response, which includes fault analysis text and fault resolution text.
8. An on-board fault handling device, characterized in that, include: processor; Memory, used to store executable instructions; The processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the vehicle fault handling method according to any one of claims 1-6.
9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, causes the processor to implement the vehicle fault handling method according to any one of claims 1-6.
10. A vehicle, characterized in that, Includes the vehicle fault handling device as described in claim 7, the vehicle fault handling equipment as described in claim 8, or the computer-readable storage medium as described in claim 9.