Query method, device and equipment for fault resolution solution

Abstract

The present disclosure relates to a fault solution query method, device and equipment, the method comprising: in the case that it is monitored that there is an application program architecture call chain fault on the vehicle, generating fault corresponding fault prompt text information, screening the key words from the fault prompt text information, taking the key words as the nodes of the first label to construct the first label, wherein the first label is the label corresponding to the fault, the first label is a label constituted by at least two nodes in a tree structure, sending the first label to the cloud, displaying the first solution set corresponding to the first label received from the cloud, and the first solution set comprises N solutions, N is a natural number. According to the present disclosure, the fault can be labeled according to a standard and rapid process after the vehicle fails, and the solution to the fault is queried based on the label, thereby improving the accuracy of the solution obtained by querying.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle fault analysis technology, and in particular to methods, apparatus and equipment for querying fault solutions. Background Technology

[0002] During the operation of the vehicle, each function relies on one or more Service Oriented Architecture (SOA) systems to call each other. These one or more SOA systems call each other to form a call chain, which represents the call relationship between SOA services and the call relationship between functions within SOA services.

[0003] When the aforementioned call chain malfunctions, the vehicle's relevant functions cannot be implemented. Since different malfunctions have different solutions, in order to determine a solution, users typically rely on their experience to compile relevant information about the vehicle malfunction into text, then input this text into a relevant search engine or database to search for solutions within the search results.

[0004] Clearly, solutions obtained through this text search method are limited by factors such as user experience, the search database, and the selection of search terms, resulting in significant uncertainty in search results. Furthermore, the aforementioned process for obtaining solutions corresponding to tags through text search cannot establish a standardized procedure. Therefore, the accuracy of solutions to problems obtained through this method is poor. Summary of the Invention

[0005] To overcome the problems existing in related technologies, this disclosure provides a method, apparatus and device for querying fault solutions.

[0006] According to a first aspect of the present disclosure, a method for querying fault solutions is provided, comprising:

[0007] If a fault is detected in the application architecture call chain on the vehicle, a corresponding fault message text is generated.

[0008] Keywords are selected from the fault message text and used as nodes for a first tag to construct a first tag. The first tag is the tag corresponding to the fault and is a tree-structured tag consisting of at least two nodes.

[0009] Send the first tag to the cloud.

[0010] The display shows the first solution set corresponding to the first tag received from the cloud, the first solution set including N solutions, where N is a natural number.

[0011] As an optional embodiment, the step of filtering keywords from the fault prompt text information and using the keywords as nodes of the first tag to construct the first tag includes:

[0012] Obtain tag prompt information, which is generated based on the tag set in the cloud.

[0013] The first prompt information corresponding to the fault prompt text information is selected from the label prompt information. This first prompt information is used to guide keyword filtering from the fault prompt text information.

[0014] Keywords are selected from the fault prompt text information based on the first prompt information, and the keywords are used as nodes of the first tag to construct the first tag.

[0015] As an optional embodiment, the first tag includes a first path, the first path includes P nodes, each of the P nodes corresponds to a field, where P is a positive integer.

[0016] The step of filtering keywords from the fault prompt text information based on the first prompt information and using the keywords as nodes of the first tag to construct the first tag includes:

[0017] The first keyword is obtained by filtering from the fault message text information, and the first keyword is used as the first field corresponding to the root node in the first path.

[0018] The second keyword is obtained by filtering the fault prompt text information based on the first prompt information, and the second keyword is used as the second field corresponding to the first node, where the first node is any node other than the root node in the first path.

[0019] As an optional embodiment, the step of filtering the second keyword from the fault prompt text information based on the first prompt information and using the second keyword as the second field corresponding to the first node includes:

[0020] After the third field is determined, at least one optional field is generated based on the first prompt information and the third field. The third field is the field corresponding to the parent node of the first node.

[0021] The second field is determined from the at least one optional field based on the fault message text information.

[0022] As an optional embodiment, the keywords include a first set of keywords, a second set of keywords, and a third set of keywords. The first set of keywords consists of words characterizing the features of the vehicle where the fault occurs, the second set of keywords consists of words characterizing the equipment where the fault occurs, and the third set of keywords consists of words characterizing the type of fault. The first tag is a tree structure comprising three levels, which are, from top to bottom, the first level, the second level, and the third level.

[0023] The step of filtering keywords from the fault message text and using those keywords as nodes for the first tag to construct the first tag includes:

[0024] Set the first set of keywords as nodes in the first level, set the second set of keywords as nodes in the second level, and set the third set of keywords as nodes in the third level.

[0025] As an optional embodiment, the keywords include the type of vehicle manufacturer to which the fault belongs, the vehicle type, the vehicle-side control equipment, the execution equipment, and the fault type.

[0026] The step of filtering keywords from the fault message text and using those keywords as nodes for the first tag to construct the first tag includes:

[0027] Set the vehicle manufacturer type as the root node of the first tag.

[0028] Set the vehicle type as a child node of the car manufacturer type.

[0029] Configure the vehicle-side control device as a sub-node of the vehicle type.

[0030] Configure the execution device as a child node of the vehicle-side control device.

[0031] The fault type is set as a child node of the execution device to construct the first label.

[0032] As an optional embodiment, after displaying the first solution set corresponding to the first tag received from the cloud, the method further includes:

[0033] If the number of solutions in the first solution set is less than a first threshold, the user's add operation based on the first fault is received, a second solution set is obtained, and the second solution set is updated to the solution set corresponding to the first tag. The add operation is to add a new solution to the first solution set.

[0034] As an optional embodiment, the method for displaying the first solution set corresponding to the first tag received from the cloud further includes:

[0035] If there is an erroneous solution in the first solution set, a deletion operation or a modification operation for the erroneous solution is received to obtain a third solution set. The third solution set is then updated to the solution set corresponding to the first tag. The deletion operation is to delete the erroneous solution from the first solution set, and the modification operation is to modify the erroneous solution from the first solution set.

[0036] According to a second aspect of the present disclosure, a fault solution query apparatus is provided, comprising:

[0037] The generation module is used to generate fault message text information corresponding to the fault when a fault in the application architecture call chain is detected on the vehicle.

[0038] The filtering module is used to filter keywords from the fault prompt text information, and use the keywords as nodes of the first tag to construct a first tag, wherein the first tag is the tag corresponding to the fault, and the first tag is a tag with a tree structure composed of at least two nodes.

[0039] The sending module is used to send the first tag to the cloud.

[0040] The display module is used to display the first solution set corresponding to the first tag received from the cloud. The first solution set includes N solutions, where N is a natural number.

[0041] According to a third aspect of the present disclosure, a computer program product is provided that stores a set of instructions, which are executed by the computer program product to implement the fault solution querying method provided by the fault solution querying aspect of the present disclosure.

[0042] According to a fourth aspect of the present disclosure, an electronic device is provided, comprising: a processor; a memory for storing executable instructions of the processor; the processor being configured to read the executable instructions from the memory and execute the instructions to implement a fault solution querying method provided by the fault solution querying aspect of the present disclosure.

[0043] According to a fifth aspect of the present disclosure, a computer-readable storage medium is provided that stores computer program instructions thereon, which, when executed by a processor, implement the steps of a fault solution querying method provided by the fault solution querying aspect of the present disclosure.

[0044] The technical solutions provided by the embodiments of this disclosure can include the following beneficial effects: by tagging each SOA call chain fault with a corresponding label, and obtaining the corresponding solution set based on the label, this tagging system is used to query the solution set corresponding to each SOA call chain fault. Compared with the prior art of constructing text based on vehicle fault-related information and performing text search to obtain fault solutions, this disclosure can automatically generate a corresponding label for each specific fault. In the cloud database, each label has multiple corresponding solution sets. Therefore, as long as a fault occurs in the vehicle, the label corresponding to the fault will be automatically generated, the corresponding solution set will be found, and then the solution set will be displayed on the vehicle. From the occurrence of a fault in the vehicle to querying and displaying the solution set, there is a standard and rapid process, and there is a strict one-to-one correspondence between the fault and the solution set. The solution to the fault can be found accurately and quickly without manual intervention, thereby improving the accuracy of the queried solutions.

[0045] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0046] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0047] Figure 1 This is a flowchart illustrating a method for querying a fault solution according to an exemplary embodiment.

[0048] Figure 2 This is a flowchart illustrating a method for querying a fault solution according to another exemplary embodiment.

[0049] Figure 3 This is a flowchart illustrating a method for querying a fault solution according to yet another exemplary embodiment.

[0050] Figure 4 This is a flowchart illustrating a method for querying a fault solution according to yet another exemplary embodiment.

[0051] Figure 5 This is a flowchart illustrating a fault solution query method according to another exemplary embodiment.

[0052] Figure 6 This is a flowchart illustrating a method for querying a fault solution according to yet another exemplary embodiment.

[0053] Figure 7This is a flowchart illustrating a fault solution query method according to another exemplary embodiment.

[0054] Figure 8 This is a block diagram illustrating a fault solution query device according to an exemplary embodiment.

[0055] Figure 9 This is a block diagram illustrating a vehicle according to an exemplary embodiment.

[0056] Figure 10 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Detailed Implementation

[0057] The exemplary embodiments will now be described in detail with reference to the accompanying drawings.

[0058] It should be noted that the relevant embodiments and accompanying drawings are only for describing and illustrating exemplary embodiments provided by this disclosure, and not all embodiments of this disclosure, nor should this disclosure be understood to be limited to the relevant exemplary embodiments.

[0059] It should be noted that the terms "first," "second," etc., used in this disclosure are only used to distinguish different steps, devices, or modules. These terms do not represent any specific technical meaning, nor do they indicate any order or interdependence between them.

[0060] It should be noted that the terms “a,” “a plurality of,” and “at least one” used in this disclosure are illustrative rather than restrictive. Unless otherwise expressly indicated in the context, they should be understood as “one or more.”

[0061] It should be noted that the term "and / or" used in this disclosure is used to describe the relationship between related objects, and generally indicates that there are at least three relationships. For example, A and / or B can at least indicate: the existence of A alone, the existence of both A and B, and the existence of B alone.

[0062] It should be noted that the various steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Unless otherwise specified, the scope of this disclosure is not limited to the order in which the steps are described in the relevant embodiments.

[0063] It should be noted that all actions involving the acquisition of signals, information, or data in this disclosure are carried out in compliance with the relevant data protection laws and policies of the country where the location is situated, and with authorization from the owner of the relevant device.

[0064] Exemplary methods

[0065] Figure 1This is a flowchart illustrating a method for querying a fault solution according to an exemplary embodiment, such as... Figure 1 As shown, the method for querying fault solutions includes the following steps.

[0066] In step S110, if a fault is detected in the application architecture call chain on the vehicle, a fault prompt text message corresponding to the fault is generated.

[0067] In this embodiment, the Service-Oriented Architecture (SOA) call chain represents a function (e.g., opening a car door) implemented through mutual calls between one or more SOA services, forming an SOA call chain of mutual service calls. In the event of a failure in the SOA call chain, a corresponding fault message is generated.

[0068] The fault indication text information is generated by the vehicle based on detected faults and is used to describe the fault characteristics of the SOA call chain. For example, the fault indication text information can be used to identify the faulty device that caused the fault, the fault point that caused the fault, or the cause of the fault.

[0069] In step S120, keywords are selected from the fault prompt text information and used as nodes of the first tag to construct the first tag. The first tag is the tag corresponding to the fault and is a tag consisting of at least two nodes forming a tree structure.

[0070] In this embodiment, by introducing a tagging mechanism on the vehicle-side SOA call chain, each SOA call chain fault corresponds to a tag. The tag summarizes the information in the fault identifier corresponding to the same fault, and provides a complete description of the characteristics and causes of the SOA call chain fault.

[0071] Since the fault message text is text information describing the features of SOA call chain faults, it can be segmented into multiple words. Based on the part of speech and semantics of these words, keywords that can be used as nodes in the tags are selected and filled into the corresponding nodes of the tags to construct a tree-like tag structure.

[0072] For example, the tags can be a tag tree in the form of a tree diagram, with the car manufacturer to which the vehicle belongs as the root node of the tag tree, the vehicle model as the child node of the car manufacturer, and specific fault-related tags such as faulty equipment, fault point, and fault cause as child nodes of the vehicle model.

[0073] In step S130, the first tag is sent to the cloud.

[0074] This embodiment can be set up under a vehicle-cloud integrated tag system. Under this tag system, the vehicle and the cloud are connected via communication. The tag experience library can be deployed in the cloud, storing tag sets and the solution sets corresponding to each tag in the tag set. When a failure occurs in the SOA call chain on the vehicle, a first tag corresponding to the failure is generated on the vehicle and sent to the cloud, so that the cloud can retrieve the first solution set corresponding to the first tag by searching in the tag experience library.

[0075] For example, tags can be sent to the cloud using a tracking link (TracerSpan). That is, TracerSpan serves as the basic information structure for uploading vehicle-side information to the cloud, with tags as components within TracerSpan.

[0076] In step S140, the first solution set corresponding to the first tag received from the cloud is displayed. The first solution set includes N solutions, where N is a natural number.

[0077] In this embodiment, for each tag, there exists a corresponding solution set, which includes N optimal solutions for dealing with the fault identified by that tag. In the tag experience database in the cloud, each tag is associated with its corresponding solution set. Therefore, whenever the cloud receives a tag sent from the vehicle, it can find the corresponding solution set and feed it back to the vehicle.

[0078] Taking the first tag as an example, the vehicle sends the first tag to the cloud. After the cloud determines the first solution set corresponding to the first tag, it feeds back the first solution set to the vehicle. The vehicle can then display the first solution set on its display interface so that the user can view it.

[0079] In this disclosure, each SOA call chain failure is tagged, and a corresponding solution set is obtained based on the tag. This tagging system is used to query the solution set corresponding to each SOA call chain failure. Compared with existing technologies that construct text based on vehicle failure-related information and perform text search to obtain solutions, this disclosure can automatically generate a corresponding tag for each specific failure. In the cloud database, each tag has multiple corresponding solution sets. Therefore, as long as a failure occurs in the vehicle, the tag corresponding to the failure will be automatically generated, the corresponding solution set will be found, and then the solution set will be displayed on the vehicle. From the occurrence of a failure in the vehicle to querying and displaying the solution set, there is a standardized and rapid process, and there is a strict one-to-one correspondence between failures and solution sets. The solution to the failure can be found accurately and quickly without manual intervention, thereby improving the accuracy of the obtained solutions.

[0080] As an optional embodiment, such as Figure 2 As shown, the above-mentioned S120 may further include:

[0081] In step S210, tag prompt information is obtained, which is generated based on the tag set in the cloud.

[0082] In this embodiment, the label prompt information is generated based on the label set stored in the label experience library, and is used to standardize the prompt information of the labels generated on the vehicle side.

[0083] In one embodiment, the label prompt information includes label format prompts and optional content prompts: the label format prompts are determined based on the format of the labels in the label set and are used to standardize the format of the labels generated by the vehicle; the optional content prompts are determined based on the content of the labels in the label set and are used to standardize the content of the labels generated by the vehicle.

[0084] In step S220, a first prompt message corresponding to the fault prompt text information is filtered out from the label prompt information, wherein the first prompt message is used to prompt the filtering of keywords from the fault prompt text information;

[0085] In this embodiment, different faults have different tag prompts. When an SOA call chain fault is detected on the vehicle side, a fault prompt text message corresponding to the fault is generated. Based on the fault prompt text message, a first prompt message is selected from the tag prompt messages. Then, a first tag is generated based on the fault prompt text message and the first prompt message.

[0086] For example, the cloud-based tag experience library generates tag prompts based on a tag set at regular intervals and sends these prompts to the vehicle. This ensures the vehicle is aware of the latest information in the tag set, thereby guaranteeing the accuracy of the generated tags.

[0087] In step S230, keywords are selected from the fault prompt text information based on the first prompt information, and the keywords are used as nodes of the first tag to construct the first tag.

[0088] In this embodiment, the first tag consists of multiple fields, each containing partial information about the fault. After determining the fault prompt text information, partial fields of the first tag can be obtained from the fault prompt text information and the first prompt information. Therefore, the first tag corresponding to the fault can be generated based on the fault prompt text information and the first prompt information.

[0089] As an optional embodiment, such as Figure 3 As shown, the first tag includes a first path, the first path includes P nodes, and each of the P nodes corresponds to a field, where P is a positive integer.

[0090] The step of filtering keywords from the fault prompt text information based on the first prompt information and using the keywords as nodes of the first tag to construct the first tag includes:

[0091] In step S310, a first keyword is obtained by filtering from the fault prompt text information, and the first keyword is used as the first field corresponding to the root node in the first path;

[0092] In this embodiment, the labels can be a tree-like label tree, with each label representing a path. During the labeling of faults, for each label, the corresponding fields on each node are generated sequentially from the root node to the leaf node.

[0093] The first keyword can be obtained directly from the fault prompt text information, and the first keyword can be used as the first field corresponding to the root node in the first path.

[0094] In step S320, a second keyword is obtained by filtering from the fault prompt text information according to the first prompt information, and the second keyword is used as the second field corresponding to the first node, where the first node is any node other than the root node in the first path.

[0095] In this embodiment, whenever a field corresponding to a node on the generated path is generated, and that node has child nodes as a parent node, the first prompt information will generate at least two optional fields for its child nodes based on the field corresponding to the parent node, and determine the optional field that matches the fault prompt text information among these two optional fields as the field corresponding to the child node.

[0096] As an optional embodiment, the fault message text identifies the location of the fault as the Body Control Module (BCM), which can be a parent node. The first message contains several selectable specific fault causes, and the fault cause code "Error Code 001" can be selected from the first message based on the information identified in the fault message text. In this case, "Error Code 001" becomes a child node of the parent node.

[0097] As an optional embodiment, such as Figure 4 As shown, generating the second field corresponding to the first node based on the first prompt information and the fault prompt text information includes:

[0098] In step S410, after the third field is determined, at least one optional field is generated based on the first prompt information and the third field, wherein the third field is the field corresponding to the parent node of the first node;

[0099] In step S420, the second field is determined from the at least one optional field based on the fault prompt text information.

[0100] In this embodiment, the first node is a node on the path that has a parent node. Once the fields corresponding to the parent node of the first node are determined, the possible content of the first node, i.e., at least one optional field, can be determined based on the first prompt information. Then, the optional field that matches the fault prompt text information can be determined as the second field corresponding to the first node. Therefore, except for the root node in the path, the fields corresponding to all nodes can be determined by the above process.

[0101] For example, the car manufacturer can be used as the root node of the tag tree, the vehicle model can be used as the child node of the car manufacturer, the specific faulty device can be used as the child node of the vehicle model, the more specific fault point can be used as the child node of the faulty device, and the cause of the fault point can be used as the child node of the fault point. A path formed by these five nodes can be regarded as a tag.

[0102] Therefore, we can determine the field corresponding to the root node as "Car Manufacturer 1" based on the fault prompt text information. Since Car Manufacturer 1 can include "Model 1, Model 2, Model 3 and Model 4", we can determine Car Manufacturer 1 as the third field at this time. The first prompt information is "Model 1, Model 2, Model 3 and Model 4". Then, based on the fault prompt text information, we can select "Model 1" from the first prompt information.

[0103] At this point, "Model 1" can be updated to the third field, and the first prompt information can be updated simultaneously to include "Model 1" such as "Body Control Module, Electronic Control Unit, Range Extender," etc. Then, based on the fault prompt text information, the fields of the child nodes of Model 1 can be determined from the above content. This process can be repeated to obtain a complete tag.

[0104] By using the above method, we can ensure that each node in the tag corresponds to an accurate field, thereby guaranteeing the accuracy of the tag. This allows the cloud database to quickly understand the content of the tag and efficiently retrieve the solution set corresponding to the fault.

[0105] As an optional embodiment, the keywords include a first set of keywords, a second set of keywords, and a third set of keywords. The first set of keywords consists of words characterizing the features of the vehicle where the fault occurs, the second set of keywords consists of words characterizing the equipment where the fault occurs, and the third set of keywords consists of words characterizing the type of fault. The first tag is a tree structure with three levels, which are, from top to bottom, the first level, the second level, and the third level.

[0106] The step of filtering keywords from the fault message text and using those keywords as nodes for the first tag to construct the first tag includes:

[0107] Set the first set of keywords as nodes in the first level, set the second set of keywords as nodes in the second level, and set the third set of keywords as nodes in the third level.

[0108] In this embodiment, different levels can be set for the first label, and different types of keywords can be set on different levels to construct a label tree corresponding to the first label. Specifically, the label tree can be set to three levels: the first keyword representing the characteristics of the vehicle where the fault is located is set as a node in the top first level; the second keyword representing the device where the fault is located is set as a node in the middle second level; and the third keyword representing the type of fault is set as a node in the bottom third level.

[0109] For example, the car manufacturer and model to which the fault belongs are independent of the fault in the vehicle-side equipment and can therefore be considered as the first-level node. The equipment related to the fault is directly related to the fault and can be considered as the second-level node. The cause and type of the fault can be considered as the third-level node.

[0110] As an optional embodiment, the keywords include the type of vehicle manufacturer to which the fault belongs, the vehicle type, the vehicle-side control equipment, the execution equipment, and the fault type.

[0111] The step of filtering keywords from the fault message text and using those keywords as nodes for the first tag to construct the first tag includes:

[0112] Set the vehicle manufacturer type as the root node of the first tag.

[0113] Set the vehicle type as a child node of the car manufacturer type.

[0114] Configure the vehicle-side control device as a sub-node of the vehicle type.

[0115] Configure the execution device as a child node of the vehicle-side control device.

[0116] The fault type is set as a child node of the execution device to construct the first label.

[0117] In this embodiment, the tag tree includes a path with five nodes. From top to bottom, these five nodes represent: vehicle manufacturer type, vehicle type, vehicle-side control device, execution device, and fault type.

[0118] For example, the first label representing the fault uses 8 bytes, i.e., an unsigned 64-bit integer. The vehicle manufacturer occupies the high 2 bytes, the middle 3 bytes, and the specific fault-related content occupies the low 3 bytes. The first label can be: Vehicle Manufacturer 1 -- Vehicle Model 1 -- BCM -- Door Motor 1 -- Error Code 001.

[0119] As an optional embodiment, after displaying the first solution set corresponding to the first tag received from the cloud, the method further includes:

[0120] If the number of solutions in the first solution set is less than a first threshold, the user's add operation based on the first fault is received, a second solution set is obtained, and the second solution set is updated to the solution set corresponding to the first tag. The add operation is to add a new solution to the first solution set.

[0121] In this embodiment, in order to improve the richness of solutions corresponding to the fault, the user can add new solutions to the solution set.

[0122] Specifically, taking the first solution set as an example, after the vehicle receives the first solution set from the cloud, if the user wants a solution that meets a first threshold, and the number of solutions in the first solution set is less than the first threshold, the user can add a new solution to the first solution set on the vehicle side, resulting in a second solution set. Simultaneously, the cloud-based tag experience database is updated, updating the solution set in the database corresponding to the first tag to the second solution set. In this way, users can then query using the first tag to obtain the updated second solution set, thus improving the richness of solutions corresponding to faults.

[0123] As an optional embodiment, the method for displaying the first solution set corresponding to the first tag received from the cloud further includes:

[0124] If there is an erroneous solution in the first solution set, a deletion operation or a modification operation for the erroneous solution is received to obtain a third solution set. The third solution set is then updated to the solution set corresponding to the first tag. The deletion operation is to delete the erroneous solution from the first solution set, and the modification operation is to modify the erroneous solution from the first solution set.

[0125] In this embodiment, in order to improve the accuracy of the solutions corresponding to the faults, users can delete existing solutions from the solution set or modify existing solutions.

[0126] Specifically, taking the first solution set as an example, after the vehicle receives the first solution set from the cloud, if the user feels that there are incorrect or inaccurate solutions in the first solution set, the user can delete the incorrect or inaccurate solutions on the vehicle, or modify the incorrect or unprofitable solutions to obtain the third solution set. Simultaneously, the cloud-based tag experience database is updated, updating the solution set corresponding to the first tag in the database to the third solution set. In this way, users can then query using the first tag to obtain the updated third solution set, thus improving the accuracy of solutions corresponding to faults.

[0127] As an optional embodiment, such as Figure 5 As shown, the tagging system may exist in the following four application scenarios: web client, cloud service, development environment, and SOA service.

[0128] The cloud service includes a tag experience library, which can be a relational database management system (MySQL) database. The cloud service receives tags sent by the vehicle and queries the database to retrieve the corresponding solution set for each tag, which is then fed back to the vehicle.

[0129] The web client is installed on the vehicle's device. Users can add, modify, and delete tags in the tag experience library through the web client to change the solution set corresponding to the tag. The modified solution set will be synchronized to the cloud database.

[0130] The development environment is deployed on the vehicle side. The development environment can be based on the cloud-based Integrated Drive Electronics (IDE). It uses plug-in technology to parse the tag data provided by the cloud and form a tag memory structure. When the developer enters a tag, it provides tag prompt information and facilitates the retrieval of existing information in the current tag experience library for the corresponding tag.

[0131] SOA services run on the vehicle side, which can package vehicle-side fault identifiers into TracerSpan information, assemble them, and then send them to the cloud in a unified manner.

[0132] Specifically, such as Figure 6 As shown, the cloud service includes a tag experience library, a tag cloud microservice, a cloud IDE server-side tag system component, and a monitoring cloud microservice. The tag cloud microservice synchronizes user add, modify, and delete operations on the solution set from the web client to the tag experience library. The cloud IDE server-side tag system component periodically transmits tag prompts to the vehicle-side client plugin, which is deployed on the vehicle to provide tag prompts. The monitoring cloud microservice sends tags generated on the vehicle to the cloud. Furthermore, information in the database can be synchronized to the intelligent customer service system and intelligent Q&A system, serving as a data source to provide users with corresponding solution sets for faults through intelligent customer service and intelligent Q&A.

[0133] In addition, such as Figure 7 As shown, SOA services can also obtain fault identifiers through SOA call chain instrumentation. That is, after the user has developed the vehicle-side SOA service and processed the SOA call chain instrumentation information, the service can be published to the vehicle for operation. The vehicle-side SOA service automatically uses the functions implemented by the SOA call chain instrumentation information to upload TracerSpan information. A Collecor service on the vehicle side receives all TracerSpan information, assembles it, and then uploads it to the cloud. This forms a monitoring system for the SOA call chain in the cloud.

[0134] Exemplary device

[0135] Figure 8 This is a block diagram of a fault solution query device 800 according to an exemplary embodiment. (Refer to...) Figure 8 The device 800 includes a generation module 810, a filtering module 820, a sending module 830, and a display module 840.

[0136] The generation module 810 is used to generate fault prompt text information corresponding to the fault when a fault in the application architecture call chain is detected on the vehicle.

[0137] The filtering module 820 is used to filter keywords from the fault prompt text information, and use the keywords as nodes of the first tag to construct a first tag, wherein the first tag is the tag corresponding to the fault, and the first tag is a tag consisting of at least two nodes forming a tree structure.

[0138] The fault indication text information is generated by the vehicle based on detected faults and is used to describe the fault characteristics of the SOA call chain. For example, the fault indication text information can be used to identify the faulty device that caused the fault, the fault point that caused the fault, or the cause of the fault.

[0139] The sending module 830 is used to send the first tag to the cloud.

[0140] The display module 840 is used to display the first solution set corresponding to the first tag received from the cloud, the first solution set including N solutions, where N is a natural number.

[0141] As an optional embodiment, the screening module 820 is further configured to:

[0142] Obtain tag prompt information, which is generated based on the tag set in the cloud.

[0143] The first prompt information corresponding to the fault prompt text information is filtered out from the label prompt information, wherein the first prompt information is used to prompt keyword filtering from the fault prompt text information.

[0144] Keywords are selected from the fault prompt text information based on the first prompt information, and the keywords are used as nodes of the first tag to construct the first tag.

[0145] As an optional embodiment, the filtering module 820 is also used for:

[0146] The step of filtering keywords from the fault prompt text information based on the first prompt information and using the keywords as nodes of the first tag to construct the first tag includes:

[0147] The first keyword is obtained by filtering from the fault message text information, and the first keyword is used as the first field corresponding to the root node in the first path.

[0148] The second keyword is obtained by filtering the fault prompt text information based on the first prompt information, and the second keyword is used as the second field corresponding to the first node, where the first node is any node other than the root node in the first path.

[0149] As an optional embodiment, the keywords include a first group of keywords, a second group of keywords, and a third group of keywords. The first group of keywords consists of words characterizing the features of the vehicle where the fault occurs, the second group of keywords consists of words characterizing the equipment where the fault occurs, and the third group of keywords consists of words characterizing the type of fault. The first tag is a tree structure with three levels, which are, from top to bottom, the first level, the second level, and the third level.

[0150] The aforementioned filtering module 820 is also used for:

[0151] Set the first set of keywords as nodes in the first level, set the second set of keywords as nodes in the second level, and set the third set of keywords as nodes in the third level.

[0152] As an optional embodiment, the screening module 820 is further configured to:

[0153] Set the vehicle manufacturer type as the root node of the first tag.

[0154] Set the vehicle type as a child node of the car manufacturer type.

[0155] Configure the vehicle-side control device as a sub-node of the vehicle type.

[0156] Configure the execution device as a child node of the vehicle-side control device.

[0157] The fault type is set as a child node of the execution device to construct the first label.

[0158] As an optional embodiment, the screening module 820 is further configured to:

[0159] After the third field is determined, at least one optional field is generated based on the first prompt information and the third field. The third field is the field corresponding to the parent node of the first node.

[0160] The second field is determined from the at least one optional field based on the fault prompt text information. As an optional embodiment, the fault solution query device 800 described above is further configured to:

[0161] If the number of solutions in the first solution set is less than a first threshold, the user's add operation based on the first fault is received, a second solution set is obtained, and the second solution set is updated to the solution set corresponding to the first tag. The add operation is to add a new solution to the first solution set.

[0162] As an optional embodiment, the fault solution query device 800 described above is further used for:

[0163] If there is an erroneous solution in the first solution set, a deletion operation or a modification operation for the erroneous solution is received to obtain a third solution set. The third solution set is then updated to the solution set corresponding to the first tag. The deletion operation is to delete the erroneous solution from the first solution set, and the modification operation is to modify the erroneous solution from the first solution set.

[0164] The fault solution query device provided in this embodiment of the invention can implement the steps in the above method embodiments, and will not be repeated here to avoid repetition.

[0165] Exemplary vehicle

[0166] Figure 9 This is a block diagram illustrating a vehicle 900 according to an exemplary embodiment. The vehicle 900 may be a gasoline vehicle, a hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicles.

[0167] Reference Figure 9 The vehicle 900 may include multiple subsystems, such as a drive system 910, a control system 920, a sensing system 930, a communication system 940, an information display system 950, and a computing processing system 960. The vehicle 900 may also include more or fewer subsystems, and each subsystem may include multiple components, which will not be described in detail here.

[0168] The drive system 910 includes components that provide power to the vehicle 900. These include, for example, an engine, an energy source, and a transmission.

[0169] The control system 920 includes components that provide control for the vehicle 900. These include, for example, vehicle control, cockpit equipment control, and driver assistance control.

[0170] The perception system 930 includes components that provide the vehicle 900 with perception of its surroundings. These include, for example, a vehicle positioning system, laser sensors, voice sensors, ultrasonic sensors, and camera equipment.

[0171] The communication system 940 includes components that provide communication connectivity for the vehicle 900. These may include, for example, mobile communication networks (e.g., 3G, 4G, 5G networks), WiFi, Bluetooth, and vehicle-to-everything (V2X) connectivity.

[0172] The information display system 950 includes components that provide various information displays for the vehicle 900. These include, for example, vehicle information displays, navigation information displays, and entertainment information displays.

[0173] The computing processing system 960 includes components that provide data computing and processing capabilities for the vehicle 900. The computing processing system 960 may include at least one processor 961 and a memory 962. The processor 961 can execute instructions stored in the memory 962.

[0174] The processor 961 can be any conventional processor, such as a commercially available CPU. The processor may also include, for example, a Graphics Processing Unit (GPU), a Field Programmable Gate Array (FPGA), a System-on-Chip (SOC), an Application-Specific Integrated Circuit (ASIC), or a combination thereof.

[0175] The memory 962 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. In embodiments of this disclosure, the memory 962 stores a set of instructions that the processor 961 can execute to implement all or part of the steps of the fault solution query method described in any of the exemplary embodiments above.

[0176] Exemplary electronic devices

[0177] Figure 10 This is a block diagram illustrating an electronic device 1000 according to an exemplary embodiment. The electronic device 1000 may be a vehicle controller, an in-vehicle terminal, an in-vehicle computer, or other types of electronic devices.

[0178] Reference Figure 10The electronic device 1000 may include at least one processor 1010 and a memory 1020. The processor 1010 can execute instructions stored in the memory 1020. The processor 1010 is communicatively connected to the memory 1020 via a data bus. In addition to the memory 1020, the processor 1010 may also be communicatively connected to an input device 1030, an output device 1040, and a communication device 350 via the data bus.

[0179] The processor 1010 can be any conventional processor, such as a commercially available CPU. The processor may also include, for example, a Graphics Processing Unit (GPU), a Field Programmable Gate Array (FPGA), a System-on-Chip (SOC), an Application-Specific Integrated Circuit (ASIC), or a combination thereof.

[0180] The memory 1020 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0181] In this embodiment of the present disclosure, the memory 1020 stores executable instructions, and the processor 1010 can read the executable instructions from the memory 1020 and execute the instructions to implement all or part of the steps of the fault solution query method described in any of the exemplary embodiments above.

[0182] Exemplary computer-readable storage media

[0183] In addition to the methods and apparatus described above, exemplary embodiments of this disclosure may also be a computer program product or a computer-readable storage medium storing the computer program product. The computer product includes computer program instructions that can be executed by a processor to perform all or part of the steps described in any of the methods in the exemplary embodiments described above.

[0184] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this disclosure. These programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages, and scripting languages ​​(e.g., Python). The program code can be executed entirely on a user's computing device, partially on a user's computing device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0185] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media include: static random access memory (SRAM) having one or more electrically connected wires, electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk, or any suitable combination thereof.

[0186] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of this disclosure. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0187] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for querying fault solutions, characterized in that, The method includes: If a fault is detected in the application architecture call chain on the vehicle, a corresponding fault message text is generated. Keywords are selected from the fault message text and used as nodes for a first tag to construct a first tag. The first tag is the tag corresponding to the fault and is a tree-structured tag consisting of at least two nodes. Send the first tag to the cloud. The display shows the first solution set corresponding to the first tag received from the cloud, the first solution set including N solutions, where N is a natural number; The step of filtering keywords from the fault message text and using those keywords as nodes for the first tag to construct the first tag includes: Obtain tag prompt information, which is generated based on the tag set in the cloud and is used to standardize the prompt information of tags generated on the vehicle side; The first prompt information corresponding to the fault prompt text information is filtered out from the label prompt information, wherein the first prompt information is used to prompt keyword filtering from the fault prompt text information. Keywords are selected from the fault prompt text information based on the first prompt information, and the keywords are used as nodes of the first tag to construct the first tag; The first tag includes a first path, which includes P nodes, each of the P nodes corresponding to a field, where P is a positive integer. The step of filtering keywords from the fault prompt text information based on the first prompt information and using the keywords as nodes of the first tag to construct the first tag includes: The first keyword is obtained by filtering from the fault message text information, and the first keyword is used as the first field corresponding to the root node in the first path. The second keyword is obtained by filtering the fault prompt text information based on the first prompt information, and the second keyword is used as the second field corresponding to the first node, where the first node is any node other than the root node in the first path.

2. The method for querying fault solutions according to claim 1, characterized in that, The step of filtering the second keyword from the fault prompt text information based on the first prompt information and using the second keyword as the second field corresponding to the first node includes: After the third field is determined, at least one optional field is generated based on the first prompt information and the third field. The third field is the field corresponding to the parent node of the first node. The second field is determined from the at least one optional field based on the fault message text information.

3. The method for querying fault solutions according to any one of claims 1-2, characterized in that, The keywords include a first group of keywords, a second group of keywords, and a third group of keywords. The first group of keywords consists of words that characterize the features of the vehicle where the fault occurs. The second group of keywords consists of words that characterize the equipment where the fault occurs. The third group of keywords consists of words that characterize the type of fault. The first tag is a tree structure with three levels, which are, from top to bottom, the first level, the second level, and the third level. The step of filtering keywords from the fault message text and using those keywords as nodes for the first tag to construct the first tag includes: Set the first set of keywords as nodes in the first level, set the second set of keywords as nodes in the second level, and set the third set of keywords as nodes in the third level.

4. The method for querying fault solutions according to any one of claims 1-2, characterized in that, The keywords include the type of vehicle manufacturer, vehicle type, vehicle-side control equipment, execution equipment, and fault type to which the fault belongs. The step of filtering keywords from the fault message text and using those keywords as nodes for the first tag to construct the first tag includes: Set the vehicle manufacturer type as the root node of the first tag. Set the vehicle type as a child node of the car manufacturer type. Configure the vehicle-side control device as a sub-node of the vehicle type. Configure the execution device as a child node of the vehicle-side control device. The fault type is set as a child node of the execution device to construct the first label.

5. The method for querying fault solutions according to claim 1, characterized in that, After displaying the first solution set corresponding to the first tag received from the cloud, the method further includes: If the number of solutions in the first solution set is less than a first threshold, the user's add operation based on the first fault is received to obtain a second solution set. The second solution set is then updated to the solution set corresponding to the first tag. The add operation is to add a new solution to the first solution set.

6. The method for querying fault solutions according to claim 1, characterized in that, The method for displaying the first solution set corresponding to the first tag received from the cloud further includes: If there is an erroneous solution in the first solution set, a deletion operation or a modification operation is received for the erroneous solution to obtain a third solution set. The third solution set is then updated to the solution set corresponding to the first tag. The deletion operation is to delete the erroneous solution from the first solution set, and the modification operation is to modify the erroneous solution from the first solution set.

7. A fault solution query device, characterized in that, include: The generation module is used to generate fault message text information corresponding to the fault when a fault in the application architecture call chain is detected on the vehicle. The filtering module is used to filter keywords from the fault prompt text information, and use the keywords as nodes of the first tag to construct a first tag, wherein the first tag is the tag corresponding to the fault, and the first tag is a tag with a tree structure composed of at least two nodes. The filtering module is also used for: Obtain tag prompt information, which is generated based on a tag set in the cloud and is used to standardize the prompt information of tags generated on the vehicle side; The first prompt information corresponding to the fault prompt text information is filtered out from the label prompt information, wherein the first prompt information is used to prompt keyword filtering from the fault prompt text information. Keywords are selected from the fault prompt text information based on the first prompt information, and the keywords are used as nodes of the first tag to construct the first tag; The sending module is used to send the first tag to the cloud. The display module is used to display the first solution set corresponding to the first tag received from the cloud, the first solution set including N solutions, where N is a natural number; The first tag includes a first path, the first path includes P nodes, each of the P nodes corresponds to a field, where P is a positive integer, and the filtering module is further configured to: filter keywords from the fault prompt text information according to the first prompt information, and use the keywords as nodes of the first tag to construct the first tag, including: The first keyword is obtained by filtering from the fault message text information, and the first keyword is used as the first field corresponding to the root node in the first path. The second keyword is obtained by filtering the fault prompt text information based on the first prompt information, and the second keyword is used as the second field corresponding to the first node, where the first node is any node other than the root node in the first path.

8. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the fault solution query method according to any one of claims 1-6.

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