Vehicle fault diagnosis method, device and equipment and readable storage medium

Abstract

The invention provides a vehicle fault diagnosis method, apparatus and device, and a readable storage medium. The method comprises the steps of obtaining fault description information and a vehicle identification identifier input by a user; the fault description information is used for representing a vehicle fault condition; in a preset diagnosis database, determining a target fault code corresponding to the fault description information, and determining a plurality of fault codes associated with the vehicle identification identifier; the diagnosis database stores a corresponding relation between the fault description information and the fault codes; and under the condition that the target fault code accords with the multiple fault codes corresponding to the vehicle identification identifier, generating a fault diagnosis result according to the target fault code so as to complete vehicle fault diagnosis. The vehicle fault diagnosis efficiency can be improved.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the technical field of vehicles, and in particular, to a vehicle fault diagnosis method, apparatus, electronic device, and computer-readable storage medium. Background Art

[0002] Automobiles are widely used in modern society. With the continuous increase in the number of automobiles, vehicle fault diagnosis has become increasingly important. An automobile is a combination of a complex mechanical and electronic system. During long-term driving, faults will inevitably occur and need to be diagnosed in a timely manner.

[0003] In related technologies, the vehicle is connected to a diagnostic instrument, and the diagnostic instrument communicates with the vehicle, so that the diagnostic instrument can read the fault codes of the vehicle.

[0004] However, related technologies require a series of cumbersome operations relying on professional equipment and professional personnel, and the efficiency of locating problems is relatively low. Summary of the Invention

[0005] In view of the above problems, embodiments of the present disclosure are proposed to provide a vehicle fault diagnosis method, apparatus, electronic device, and computer-readable storage medium that overcome the above problems or at least partially solve the above problems.

[0006] In a first aspect, embodiments of the present disclosure disclose a vehicle fault diagnosis method, including:

[0007] Obtain the fault description information input by the user and the vehicle identification identifier; the fault description information is used to represent the vehicle fault situation;

[0008] In a preset diagnostic database, determine the target fault code corresponding to the fault description information, and determine multiple fault codes associated with the vehicle identification identifier; the diagnostic database stores the corresponding relationship between the fault description information and the fault codes;

[0009] When the target fault code conforms to the multiple fault codes corresponding to the vehicle identification identifier, generate a fault diagnosis result according to the target fault code to complete vehicle fault diagnosis.

[0010] Optionally, the diagnostic database stores maintenance information corresponding to the fault codes; the method further includes:

[0011] In the diagnostic database, determine the target maintenance information corresponding to the target fault code;

[0012] Add the target maintenance information to the fault diagnosis result.

[0013] Optionally, the method further includes:

[0014] Send diagnostic data including the fault description information of the user input, the target fault code, and the target repair information to the server; the server is used to determine, from the stored set of diagnostic data, multiple target diagnostic data including the fault description information, and determine the fault codes and repair information that meet the preset quantity condition among the multiple target diagnostic data as the update data;

[0015] Receive the update data returned by the server, and based on the update data, update the corresponding relationship between the fault description information and the fault codes and repair information in the diagnostic database.

[0016] Optionally, the step of determining the target fault code corresponding to the fault description information in the preset diagnostic database includes:

[0017] In the preset diagnostic database, determine at least two target fault codes corresponding to the fault description information;

[0018] Send at least two target fault codes and the vehicle identification identifier to the server to obtain the trigger probability of each target fault code returned by the server; the server is used to determine the trigger probability of each target fault code according to the vehicle identification identifier in the stored fault code historical data;

[0019] Determine the final target fault code among at least two target fault codes according to the trigger probability of each target fault code.

[0020] Optionally, there are multiple pieces of the target repair information; the method further includes:

[0021] Obtain multiple pieces of feedback information input by the user for the fault diagnosis result; each piece of feedback information is used to indicate the effective repair information among the multiple target repair information;

[0022] Sort the multiple target repair information in the fault diagnosis result according to the effective repair information indicated by the multiple pieces of feedback information to obtain a repair information sequence.

[0023] Optionally, the step of determining the target fault code corresponding to the fault description information in the preset diagnostic database includes:

[0024] Extract user keywords from the fault description information input by the user, and respectively determine the similarity between the user keywords and multiple fault description information in the diagnostic database;

[0025] Determine the target fault description information from the multiple fault description information in the diagnostic database according to the similarity corresponding to the multiple fault description information;

[0026] Determine the target fault code corresponding to the target fault description information.

[0027] Optionally, the step of determining the target fault code corresponding to the fault description information in the preset diagnostic database includes:

[0028] Determine the target diagnostic database corresponding to the vehicle identification in multiple preset diagnostic databases;

[0029] In the target diagnostic database, determine the target fault code corresponding to the fault description information.

[0030] In a second aspect, an embodiment of the present disclosure discloses a vehicle fault diagnosis device, including:

[0031] A data acquisition module, configured to acquire the fault description information input by the user and the vehicle identification; the fault description information is used to represent the vehicle fault condition;

[0032] A fault matching module, configured to determine the target fault code corresponding to the fault description information in the preset diagnostic database, and determine multiple fault codes associated with the vehicle identification; the diagnostic database stores the corresponding relationship between the fault description information and the fault code;

[0033] A diagnostic result module, configured to generate a fault diagnosis result according to the target fault code to complete vehicle fault diagnosis when the target fault code meets the multiple fault codes corresponding to the vehicle identification.

[0034] Optionally, the device further includes:

[0035] A diagnostic sending module, configured to send diagnostic data including the fault description information, the target fault code, and the target repair information input by the user to the server; the server is configured to determine multiple target diagnostic data including the fault description information in the stored diagnostic data set, and determine the fault code and repair information that meet the preset quantity condition in the multiple target diagnostic data as the update data;

[0036] A data update module, configured to receive the update data returned by the server, and update the corresponding relationship between the fault description information and the fault code and repair information in the diagnostic database based on the update data.

[0037] Optionally, the fault matching module includes:

[0038] A multi-fault code sub-module, configured to determine at least two target fault codes corresponding to the fault description information in the preset diagnostic database;

[0039] A trigger probability sub-module, configured to send at least two target fault codes and the vehicle identification to a server to obtain the trigger probability of each target fault code returned by the server; the server is configured to determine the trigger probability of each target fault code according to the vehicle identification in the stored fault code historical data;

[0040] A probability indication sub-module, configured to determine a final target fault code among at least two target fault codes according to the trigger probability of each target fault code.

[0041] Optionally, there are multiple pieces of target maintenance information; the device further includes:

[0042] A user feedback module, configured to obtain multiple feedback messages input by a user for the fault diagnosis result; each feedback message is used to indicate valid maintenance information among multiple pieces of target maintenance information;

[0043] A maintenance sequence module, configured to sort multiple pieces of target maintenance information in the fault diagnosis result according to the valid maintenance information indicated by multiple feedback messages respectively to obtain a maintenance information sequence.

[0044] Optionally, the fault matching module includes:

[0045] A key extraction sub-module, configured to extract user keywords from the fault description information input by the user and respectively determine the similarity between the user keywords and multiple pieces of fault description information in the diagnosis database;

[0046] A similarity determination sub-module, configured to determine target fault description information among multiple pieces of fault description information in the diagnosis database according to the similarities corresponding to multiple pieces of fault description information;

[0047] A similarity indication sub-module, configured to determine a target fault code corresponding to the target fault description information.

[0048] Optionally, the fault matching module includes:

[0049] An identification corresponding sub-module, configured to determine a target diagnosis database corresponding to the vehicle identification in multiple preset diagnosis databases;

[0050] An identification data sub-module, configured to determine a target fault code corresponding to the fault description information in the target diagnosis database.

[0051] In a third aspect, embodiments of the present disclosure also disclose an electronic device, including a processor, a communication interface, a memory, and a communication bus; wherein, the processor, the communication interface, and the memory complete communication with each other through the communication bus; the memory is used for storing a computer program; the processor is used for implementing the steps of the vehicle fault diagnosis method as described in the first aspect when executing the program stored on the memory.

[0052] In a fourth aspect, embodiments of the present disclosure also disclose a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the vehicle fault diagnosis method as described in the first aspect are implemented.

[0053] In the embodiments of the present disclosure, by obtaining the fault description information input by the user and the vehicle identification identifier, the fault description information is used to represent the vehicle fault situation, in a preset diagnosis database, determining the target fault code corresponding to the fault description information, and determining a plurality of fault codes associated with the vehicle identification identifier. When the target fault code conforms to the plurality of fault codes corresponding to the vehicle identification identifier, a fault diagnosis result is generated according to the target fault code to complete the vehicle fault diagnosis. It is possible to determine the corresponding target fault code in the diagnosis database based on the fault description information input by the user, and determine that the target fault code conforms to the fault codes associated with the current vehicle identification identifier, then a fault diagnosis result can be generated according to the target fault code, avoiding the need to rely on professionals to perform cumbersome diagnosis operations based on professional equipment, and the diagnosis can be automatically completed through the fault description information input by the user, improving the efficiency of vehicle fault diagnosis. Description of the Drawings

[0054] Figure 1 is a step diagram of a vehicle fault diagnosis method provided by an embodiment of the present disclosure;

[0055] Figure 2 is a step diagram of another vehicle fault diagnosis method provided by an embodiment of the present disclosure;

[0056] Figure 3 is a schematic diagram of a vehicle fault diagnosis process provided by an embodiment of the present disclosure;

[0057] Figure 4 is a block diagram of a vehicle fault diagnosis device provided by an embodiment of the present disclosure;

[0058] Figure 5 is a block diagram of an electronic device provided by an embodiment of the present disclosure. Detailed Embodiments

[0059] Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present application can be more thoroughly understood and the scope of the present application can be completely conveyed to those skilled in the art.

[0060] Figure 1 The flowchart of a vehicle fault diagnosis method provided by an embodiment of the present disclosure is shown, and the method includes:

[0061] Step 101, obtaining the fault description information input by the user and the vehicle identification identifier; the fault description information is used to represent the vehicle fault situation.

[0062] In the embodiments of the present disclosure, the vehicle fault diagnosis method can be executed by the user's mobile terminal, in-vehicle terminal or other devices with data processing capabilities. In the case of a vehicle fault, for example, the seat cannot be adjusted in angle, the window cannot be raised or lowered, the air conditioner does not work, and other faults. The user can input the fault description information in the device for diagnosis by means of text or voice, etc. The user can clearly indicate the faulty component or fault phenomenon that the user believes in the fault description information. For example, the fault description information input by the user can be "the air conditioner is not running" or "the temperature inside the vehicle is high and cannot be lowered", etc., to represent the vehicle fault situation. The content of the fault description information input by the user is not specifically limited herein.

[0063] The vehicle identification identifier may refer to the vehicle identification number (VIN, Vehicle Identification Number). The VIN code can be composed of 17 characters, including letters and numbers, and has uniqueness, which is used to identify each vehicle. The VIN code contains information such as the vehicle manufacturer, year, model, body type and code, engine code and assembly location, etc. It can also be based on other identification methods to distinguish vehicles, so as to obtain different types of vehicle identification identifiers, which are not limited herein.

[0064] Step 102, in a preset diagnosis database, determining the target fault code corresponding to the fault description information, and determining a plurality of fault codes associated with the vehicle identification identifier; the diagnosis database stores the corresponding relationship between the fault description information and the fault code.

[0065] In an embodiment of the present disclosure, a diagnostic database may be pre-stored in a device for diagnosis. The diagnostic database stores the correspondence between fault description information and fault codes. It can be understood that the fault description information corresponding to a fault code may have a relatively large amount of content. For example, fault code A indicates an air conditioner fault, and the fault description information may be too high temperature, too low temperature, the air conditioner does not operate, the air conditioner has no wind, etc. The fault description information corresponding to a fault code may be an information set. However, the fault description information input by the user may be less. When the fault description information input by the user corresponds to any one of the fault description information in the information set corresponding to the fault code, the fault code can be determined as the target fault code.

[0066] Vehicle identification identifiers can distinguish different vehicles. Components included in different vehicles, such as controllers, may be different. Therefore, the faults that may occur in different vehicles may not be exactly the same. Further, the fault codes corresponding to different vehicles may be different. For example, the first vehicle has controller A, and the second vehicle does not have controller A, so the second vehicle will not have a fault code related to controller A.

[0067] Since there are many components in a vehicle, for example, in terms of controllers, it may include an engine control unit (ECU), a brake controller, a body control module (BCM), and others. The fault codes corresponding to different components are also different. Therefore, different vehicles can correspond to different multiple fault codes.

[0068] Step 103, when the target fault code conforms to the multiple fault codes corresponding to the vehicle identification identifier, generate a fault diagnosis result according to the target fault code to complete vehicle fault diagnosis.

[0069] In an embodiment of the present disclosure, the target fault code obtained based on the diagnostic database may be compared with the multiple fault codes corresponding to the vehicle identification identifier. The multiple fault codes corresponding to the vehicle identification identifier cover the possible fault codes of the current vehicle.

[0070] If the target fault code obtained based on the diagnostic database does not belong to any one of the multiple fault codes corresponding to the vehicle identification identifier, it indicates that there is an error in the diagnosis, and the diagnosis can be re-performed. When the target fault code conforms to the multiple fault codes corresponding to the vehicle identification identifier, a fault diagnosis result can be generated according to the target fault code.

[0071] Generating a fault diagnosis result based on a target fault code may mean that the generated fault diagnosis result carries the target fault code, or it may further mean that based on the target fault code, fault information corresponding to the fault code is searched for in a relevant database. The fault information may, for example, be information related to the component where the fault occurred, the impacts that the fault may cause, etc. The fault diagnosis result carries the fault information determined based on the target fault code. Here, there is no specific limitation on how to generate the fault diagnosis result based on the target fault code.

[0072] The fault diagnosis result can be displayed on the user's mobile terminal, in-vehicle terminal, or other devices to inform the user or maintenance personnel of the current vehicle fault situation.

[0073] In summary, in the embodiments of the present disclosure, by obtaining the fault description information input by the user and the vehicle identification identifier, where the fault description information is used to represent the vehicle fault situation, in a preset diagnostic database, a target fault code corresponding to the fault description information is determined, and a plurality of fault codes associated with the vehicle identification identifier are determined. In the case where the target fault code conforms to the plurality of fault codes corresponding to the vehicle identification identifier, a fault diagnosis result is generated based on the target fault code to complete the vehicle fault diagnosis. It is possible to determine the corresponding target fault code in the diagnostic database based on the fault description information input by the user, and determine that the target fault code conforms to the fault codes associated with the current vehicle identification identifier, then a fault diagnosis result can be generated based on the target fault code, avoiding the need to rely on professionals to perform cumbersome diagnostic operations based on professional equipment, and automatically completing the diagnosis through the fault description information input by the user, improving the efficiency of vehicle fault diagnosis.

[0074] Reference Figure 2 , which shows a flowchart of the steps of a vehicle fault diagnosis method provided by an embodiment of the present disclosure. The method includes:

[0075] Step 201, obtaining the fault description information input by the user and the vehicle identification identifier; the fault description information is used to represent the vehicle fault situation;

[0076] Step 202, in a preset diagnostic database, determining a target fault code corresponding to the fault description information, and determining a plurality of fault codes associated with the vehicle identification identifier; the diagnostic database stores the corresponding relationship between the fault description information and the fault code;

[0077] Step 203, in the case where the target fault code conforms to the plurality of fault codes corresponding to the vehicle identification identifier, generating a fault diagnosis result based on the target fault code to complete the vehicle fault diagnosis.

[0078] The above steps 201 to 203 can refer to the content of the above Figure 1 embodiment, and will not be elaborated here.

[0079] When a vehicle breaks down, it often needs to be repaired. Given a trouble code, it is necessary to further determine the corresponding repair method based on the trouble code. However, in the related art, the repair manual is queried based on the trouble code, and the efficiency is very low.

[0080] Optionally, the diagnostic database stores repair information corresponding to the trouble code; the method further includes:

[0081] Step 204, in the diagnostic database, determine the target repair information corresponding to the target trouble code;

[0082] Step 205, add the target repair information to the fault diagnosis result.

[0083] In the embodiments of the present disclosure, the diagnostic database may also store repair information corresponding to the trouble code. For example, for the trouble description information that the seat cannot be adjusted, the corresponding trouble code is A, and the repair information corresponding to the trouble code A may be "replace the seat controller". In the diagnostic database, according to the trouble code, the corresponding target repair information can be queried, and the target repair information can be added to the fault diagnosis result, so as to provide repair guidance for users or maintenance personnel.

[0084] It can be understood that the diagnostic database may store repair information corresponding to the trouble code type, that is, in the diagnostic database, different trouble code types correspond to different repair information. If two different trouble codes belong to the same trouble code type, the same repair information can be determined.

[0085] For example, the trouble code types may include communication faults, ECU internal faults, sensor faults, voltage faults, etc. The repair information corresponding to the communication fault may be "check the Controller Area Network (CAN) bus or a single controller"; the repair information corresponding to the ECU internal fault may be "replace the hardware"; the repair information corresponding to the sensor fault may be "check the wiring harness, and if the wiring harness is okay, then replace the hardware"; the repair information corresponding to the voltage fault may be "first check the battery voltage of the battery, then check the output voltage of the DC-to-DC converter, and finally check the fuse of the main relay".

[0086] By implementing the embodiments of the present disclosure, by determining the target repair information corresponding to the target trouble code in the diagnostic database and adding the target repair information to the fault diagnosis result. It is possible to conveniently determine the target repair information corresponding to the target trouble code in the diagnostic database and add the target repair information to the fault diagnosis result, thereby improving the fault repair efficiency.

[0087] The diagnostic database stores the correspondence between fault description information and fault codes. Usually, a relatively large number of fault description information is required to handle different fault description information input by users. Therefore, among the multiple fault description information in the diagnostic database, whether the content corresponding to the fault description information input by the user can be determined has a great impact on the accuracy of fault diagnosis.

[0088] Optionally, the step of determining the target fault code corresponding to the fault description information in the preset diagnostic database includes:

[0089] Extract user keywords from the fault description information input by the user, and respectively determine the similarity between the user keywords and multiple fault description information in the diagnostic database;

[0090] Determine the target fault description information from the multiple fault description information in the diagnostic database according to the similarities corresponding to the multiple fault description information;

[0091] Determine the target fault code corresponding to the target fault description information.

[0092] In the embodiments of the present disclosure, keywords can be extracted from the fault description information input by the user. It can be based on the term frequency-inverse document frequency (TF-IDF) algorithm. TF represents the frequency of a word appearing in a document, IDF is the inverse document frequency, which reflects the rarity of a word. The TF-IDF value is the product of TF and IDF. The higher the TF-IDF value, the more important the word is in the current document. It can also be based on the Naive Bayes classifier for keyword extraction. By learning a large number of labeled texts, a probability model between words and keyword categories is established. The method of extracting keywords is not specifically limited herein.

[0093] The user keywords can be applied to the fault description information input by the user, and the similarity between the user keywords and multiple fault description information in the diagnostic database can be calculated. For example, it can be based on cosine similarity. The text is represented as a vector, and the cosine value of the angle between vectors is calculated to measure the similarity. It can also be based on the Euclidean distance, calculating the distance between two vectors in space. The smaller the distance, the more similar the texts. It can also be based on the edit distance, calculating the number of the least edit operations (inserting, deleting, replacing characters) required to convert one string to another string. The fewer the edit operations, the more similar the texts. The method of calculating the similarity is not specifically limited herein.

[0094] After determining the similarity between each fault description information in the diagnosis database and the user keywords, the target fault description information can be determined from the fault description information according to the similarity of different fault description information. For example, the fault description information with the largest similarity in the diagnosis database can be used as the target fault description information, and then the target fault code corresponding to the target fault description information can be determined.

[0095] By implementing the embodiments of the present disclosure, user keywords are extracted from the input fault description information of the user, the similarities between the user keywords and multiple fault description information in the diagnosis database are determined respectively, and the target fault description information is determined from the multiple fault description information according to the similarities corresponding to the multiple fault description information, and then the corresponding target fault code is determined. It is possible to accurately match the fault code corresponding to the input fault description information of the user in the diagnosis database based on the similarity calculation, thereby improving the accuracy of fault diagnosis.

[0096] Based on the preset diagnosis database, the fault code and repair information can be conveniently determined. However, with the improvement of the vehicle structure and the change of other factors, if the diagnosis is carried out based on the diagnosis database with fixed content, it may lead to insufficient accuracy in subsequent vehicle fault diagnosis.

[0097] Optionally, the method further includes:

[0098] Sending the diagnosis data including the input fault description information of the user, the target fault code, and the target repair information to the server; the server is used to determine multiple target diagnosis data including the fault description information in the stored diagnosis data set, and determine the fault code and repair information that meet the preset quantity condition in the multiple target diagnosis data as the update data;

[0099] Receiving the update data returned by the server, and based on the update data, updating the corresponding relationship between the fault description information and the fault code and repair information in the diagnosis database.

[0100] In the embodiments of the present disclosure, after the target fault code and the target repair information have been determined according to the input fault description information of the current user, the input fault description information of the user, the target fault code, and the target repair information can be used as a group of diagnosis data and sent to the server.

[0101] It can be understood that when a single user conducts multiple fault diagnoses on a single device, a set of diagnostic data obtained each time can be sent to the server. Diagnostic data obtained by different users on different devices during fault diagnosis can also be sent to the server. As a result, the server can store a relatively large amount of diagnostic data, namely a diagnostic data set. Each set of diagnostic data can include fault description information historically input by the user, as well as the corresponding target fault code and target repair information.

[0102] The server can compare the fault description information input by the current user with the fault description information of each diagnostic data in the stored diagnostic data set, which can be to calculate the similarity between the fault description information. When calculating the similarity, it can be based on methods such as cosine similarity, Euclidean distance, and edit distance.

[0103] In the case where the similarity between the fault description information of each diagnostic data in the diagnostic data set and the fault description information input by the current user is greater than a specific threshold, it can be determined that the specific diagnostic data in the diagnostic data set includes the fault description information input by the current user. Thus, the target diagnostic data can be determined in the diagnostic data set.

[0104] Each target diagnostic data contains the fault description information historically input by the user, as well as the corresponding target fault code and target repair information. Among them, between different target diagnostic data, the fault codes can be different, and the repair information may also be different.

[0105] It is possible to perform statistics on all the target diagnostic data to determine the occurrence times of each fault code and the occurrence times of each repair information. For example, when performing statistics on 10 sets of diagnostic data, the 10 sets of diagnostic data include fault codes A, B, C, and D, with the quantities being 6 fault codes A, 3 fault codes B, 1 fault code C, and 1 fault code D respectively. For the fault codes, the preset quantity condition can be to use the fault code with the largest quantity as the fault code in the updated data, or to select the preset quantity with the largest quantity, such as 2 or 3 fault codes, as the fault codes in the updated data. The statistical and selection processes for the repair information are similar and will not be elaborated here.

[0106] It can be understood that the fault codes and repair information in the updated data are for the fault description information input by the current user. Therefore, after receiving the updated data returned by the server, it is possible to first determine the stored fault diagnosis information corresponding to the fault diagnosis information input by the current user in the diagnostic database, and then update the fault codes and repair information corresponding to this fault diagnosis information.

[0107] In an embodiment of the present disclosure, by sending diagnostic data including the fault description information input by the user, the target fault code, and the target repair information to the server, the server determines multiple target diagnostic data including the fault description information in the stored diagnostic data set, and determines the fault codes and repair information that meet the preset quantity condition in the multiple target diagnostic data as the update data, receives the update data returned by the server, and based on the update data, updates the corresponding relationship between the fault description information and the fault codes and repair information in the diagnostic database. Thus, the diagnostic database in the device can be continuously updated based on a large amount of data in the server, and further, the accuracy of fault diagnosis can be improved.

[0108] When diagnosing according to the diagnostic database to determine the fault code, multiple fault codes may be matched. For example, it is because the fault description information input by the user has a high degree of match with multiple stored fault description information in the diagnostic database, but the existence of multiple fault codes will cause the fault to be unable to be accurately located.

[0109] Optionally, the step of determining the target fault code corresponding to the fault description information in the preset diagnostic database includes:

[0110] In the preset diagnostic database, determine at least two target fault codes corresponding to the fault description information;

[0111] Send at least two target fault codes and the vehicle identification identifier to the server to obtain the trigger probability of each target fault code returned by the server; the server is used to determine the trigger probability of each target fault code in the stored fault code historical data according to the vehicle identification identifier;

[0112] According to the trigger probability of each target fault code, determine the final target fault code among at least two target fault codes.

[0113] In an embodiment of the present disclosure, in the preset diagnostic database, determining at least two target fault codes corresponding to the fault description information may be because the fault description information input by the user has a high similarity with multiple stored fault description information in the diagnostic database, so there are at least two target fault codes.

[0114] Since different vehicle structures, internal components, etc. can be different, the faults that may occur in different vehicles and the probabilities of various faults occurring are different, and the vehicle identification identifier can be used to distinguish different vehicles and also different vehicle types. Therefore, at least two target fault codes and the vehicle identification identifier can be sent to the server.

[0115] The server may store historical data of fault codes corresponding to different vehicle types, that is, the fault codes that have occurred for each vehicle type. The server can then determine the trigger probability of each target fault code among at least two target fault codes based on the vehicle identification identifier. A high trigger probability indicates that the specific fault code appears more frequently in the historical fault code data.

[0116] Furthermore, based on the trigger probability of each target fault code, the final target fault code can be determined among at least two target fault codes. For example, the target fault code with the highest trigger probability is used as the final target fault code.

[0117] Implementing the embodiments of the present disclosure, by determining at least two target fault codes corresponding to the fault description information in the preset diagnostic database, sending the at least two target fault codes and the vehicle identification identifier to the server, the server determines the trigger probability of each target fault code based on the vehicle identification identifier in the stored historical fault code data and returns it. Furthermore, based on the trigger probability of each target fault code, the final target fault code can be determined among at least two target fault codes. It is possible to determine the probabilities of different fault codes for the large amount of fault code data stored in the server in the case of multiple target fault codes, and then select the final target fault code, which can improve the accuracy of fault diagnosis.

[0118] There may be multiple pieces of maintenance information determined according to the diagnostic database. For example, maintenance information 1 "replace the seat wiring harness", maintenance information 2 "replace the seat controller", and maintenance information 3 "replace the seat". In this case, although a relatively large amount of maintenance information is given, which can provide sufficient maintenance guidance to users or maintenance personnel, it also indicates that the accuracy of the maintenance information is insufficient, resulting in a problem of low maintenance efficiency.

[0119] Optionally, there are multiple pieces of target maintenance information; the method further includes:

[0120] Obtaining multiple feedback messages input by the user for the fault diagnosis result; each feedback message is used to indicate valid maintenance information among the multiple pieces of target maintenance information;

[0121] Sorting the multiple pieces of target maintenance information in the fault diagnosis result according to the valid maintenance information indicated by the multiple feedback messages respectively to obtain a maintenance information sequence.

[0122] In the disclosed embodiment, for the fault description information input by the user, when there are multiple target maintenance information in the fault diagnosis result, the user can interact on the device interface and input feedback information for the fault diagnosis result. It is understandable that when the same fault description information appears multiple times, for the same multiple fault diagnosis results, the user can input feedback information for each fault diagnosis result, thereby obtaining multiple feedback information.

[0123] There may be a plurality of controls corresponding to the target maintenance information displayed in the device interface, and the user triggers the control for a specific target maintenance information, thereby generating feedback information indicating the effective maintenance information. The user may also directly input text or voice to generate feedback information, which is not specifically limited here.

[0124] According to the effective maintenance information respectively indicated by the multiple feedback information, the multiple target maintenance information in the fault diagnosis result is sorted. For example, for the same fault description information input multiple times, there may be multiple fault diagnosis results, each fault diagnosis result has multiple maintenance information, and the maintenance information between the fault diagnosis results may be different. For example, the first fault diagnosis result includes maintenance information A, B and C, the second fault diagnosis result includes maintenance information A, B and D, and the third fault diagnosis result includes maintenance information A, E and F. Then, the maintenance information may be sorted according to the number of occurrences of each maintenance information, and the maintenance information sequence may be ABCDEF.

[0125] Then, the multiple target maintenance information can be sorted according to the feedback information corresponding to the historical maintenance information, so that the ones with more occurrences and higher probabilities are sorted at the front, and the ones with fewer occurrences and lower probabilities are sorted at the back.

[0126] In the implementation of the embodiment of the present disclosure, when there are multiple target maintenance information, multiple feedback information input by the user for the fault diagnosis result is obtained; each feedback information is used to indicate the effective maintenance information in the multiple target maintenance information, and the multiple target maintenance information in the fault diagnosis result is sorted according to the effective maintenance information respectively indicated by the multiple feedback information to obtain a maintenance information sequence. Based on the effectiveness of the maintenance information, multiple maintenance information can be displayed in an orderly manner, so that the effective maintenance information can be displayed more intuitively, and when sufficient maintenance guidance is provided through multiple maintenance information, the utilization efficiency of the maintenance information is improved, thereby improving the efficiency of vehicle fault maintenance.

[0127] Since the internal structures and controllers of different vehicles may vary, different faults may occur. If all vehicles are diagnosed based on the same diagnostic database, the data in the diagnostic database needs to cover different vehicles, which will result in an overly large database size. Moreover, due to the large database size, a large amount of data needs to be processed during diagnosis, leading to low diagnostic efficiency.

[0128] Optionally, the step of determining the target fault code corresponding to the fault description information in the preset diagnostic database includes:

[0129] Determine the target diagnostic database corresponding to the vehicle identification identifier among multiple preset diagnostic databases;

[0130] In the target diagnostic database, determine the target fault code corresponding to the fault description information.

[0131] In the embodiments of the present disclosure, different preset diagnostic databases may be preset for different vehicles, that is, there may be multiple preset diagnostic databases. The corresponding target diagnostic database can be determined based on the vehicle identification identifier, and then the target fault code corresponding to the fault description information can be determined in the target diagnostic database. The specific process of determining the fault code in the diagnostic database will not be elaborated here.

[0132] It can be understood that since the internal structures and controllers of vehicles of the same model can be the same, a diagnostic database may be preset for vehicles of the same model, and different vehicle identification identifiers can correspond to the diagnostic database corresponding to the same model of vehicle.

[0133] Implementing the embodiments of the present disclosure, determining the target diagnostic database corresponding to the vehicle identification identifier among multiple preset diagnostic databases, and determining the target fault code corresponding to the fault description information in the target diagnostic database. It is possible to determine a specific diagnostic database based on the vehicle identification identifier, thereby separating the diagnostic databases corresponding to different vehicles, avoiding an overly large single diagnostic database, and at the same time avoiding the need to process a large amount of data. Only the specific diagnostic database needs to be diagnosed, improving the efficiency and accuracy of fault diagnosis.

[0134] Figure 3 It is a schematic diagram of the vehicle fault diagnosis process provided by the embodiments of the present disclosure;

[0135] The user 301 inputs the fault description information into the device 302. The device 302 analyzes based on the diagnostic database. The device 302 uploads the diagnostic data to the cloud server 303, and the server 303 updates the diagnostic database of the device 302.

[0136] Figure 4 It is a vehicle fault diagnosis device provided by the embodiments of the present disclosure. The device 40 includes:

[0137] A data acquisition module 401, configured to acquire fault description information input by a user and a vehicle identification identifier; the fault description information is used to represent the vehicle fault condition;

[0138] A fault matching module 402, configured to determine a target fault code corresponding to the fault description information in a preset diagnostic database, and determine a plurality of fault codes associated with the vehicle identification identifier; the diagnostic database stores the correspondence between the fault description information and the fault code;

[0139] A diagnostic result module 403, configured to generate a fault diagnosis result according to the target fault code to complete vehicle fault diagnosis when the target fault code conforms to the plurality of fault codes corresponding to the vehicle identification identifier.

[0140] Optionally, the diagnostic database stores repair information corresponding to the fault code; the device further includes:

[0141] A repair information module, configured to determine target repair information corresponding to the target fault code in the diagnostic database;

[0142] A repair diagnosis module, configured to add the target repair information to the fault diagnosis result.

[0143] Optionally, the device further includes:

[0144] A diagnostic sending module, configured to send diagnostic data including the fault description information input by the user, the target fault code, and the target repair information to a server; the server is configured to determine, in a stored diagnostic data set, a plurality of target diagnostic data including the fault description information, and determine fault codes and repair information that meet a preset quantity condition in the plurality of target diagnostic data as updated data;

[0145] A data update module, configured to receive the updated data returned by the server, and update the correspondence between the fault description information and the fault code and the repair information in the diagnostic database based on the updated data.

[0146] Optionally, the fault matching module includes:

[0147] A multi-fault code sub-module, configured to determine at least two target fault codes corresponding to the fault description information in a preset diagnostic database;

[0148] A trigger probability sub-module, configured to send at least two target fault codes and the vehicle identification to a server to obtain the trigger probability of each target fault code returned by the server; the server is configured to determine the trigger probability of each target fault code according to the vehicle identification in the stored fault code historical data;

[0149] A probability indication sub-module, configured to determine a final target fault code among at least two target fault codes according to the trigger probability of each target fault code.

[0150] Optionally, there are multiple pieces of the target repair information; the device further includes:

[0151] A user feedback module, configured to obtain multiple feedback messages input by a user for the fault diagnosis result; each feedback message is used to indicate valid repair information among multiple pieces of target repair information;

[0152] A repair sequence module, configured to sort multiple pieces of target repair information in the fault diagnosis result according to the valid repair information indicated by multiple feedback messages respectively to obtain a repair information sequence.

[0153] Optionally, the fault matching module includes:

[0154] A key extraction sub-module, configured to extract user keywords from the fault description information input by the user and determine the similarity between each user keyword and multiple pieces of fault description information in the diagnosis database respectively;

[0155] A similarity determination sub-module, configured to determine target fault description information among multiple pieces of fault description information in the diagnosis database according to the similarities corresponding to multiple pieces of fault description information;

[0156] A similarity indication sub-module, configured to determine a target fault code corresponding to the target fault description information.

[0157] Optionally, the fault matching module includes:

[0158] An identification corresponding sub-module, configured to determine a target diagnosis database corresponding to the vehicle identification in multiple preset diagnosis databases;

[0159] An identification data sub-module, configured to determine a target fault code corresponding to the fault description information in the target diagnosis database.

[0160] In summary, in the embodiments of the present disclosure, by obtaining the fault description information input by the user and the vehicle identification identifier, where the fault description information is used to represent the vehicle fault situation, in the preset diagnostic database, the target fault code corresponding to the fault description information is determined, and multiple fault codes associated with the vehicle identification identifier are determined. When the target fault code conforms to the multiple fault codes corresponding to the vehicle identification identifier, a fault diagnosis result is generated according to the target fault code to complete the vehicle fault diagnosis. It is possible to determine the corresponding target fault code in the diagnostic database based on the fault description information input by the user, and determine that the target fault code conforms to the fault codes associated with the current vehicle identification identifier. Then, a fault diagnosis result can be generated according to the target fault code, avoiding the need to rely on professionals to perform cumbersome diagnostic operations based on professional equipment. The diagnosis can be automatically completed through the fault description information input by the user, improving the efficiency of vehicle fault diagnosis.

[0161] An embodiment of the present application also provides an electronic device, as Figure 5 shown, including a processor 1001, a communication interface 1002, a memory 1003, and a communication bus 1004. Among them, the processor 1001, the communication interface 1002, and the memory 1003 communicate with each other through the communication bus 1004.

[0162] The memory 1003 is used to store a computer program.

[0163] When the processor 1001 is used to execute the program stored on the memory 1003, it implements the steps in the above vehicle fault diagnosis method, which will not be elaborated here.

[0164] The communication bus mentioned in the above electronic device may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of simplicity, only a thick line is used in the figure to represent it, but it does not mean that there is only one bus or one type of bus.

[0165] The communication interface is used for communication between the above electronic device and other devices.

[0166] The memory may include a Random Access Memory (RAM), or may also include a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor.

[0167] The above-mentioned processor may be a general-purpose processor, including a Central Processing Unit (CPU for short), a Network Processor (NP for short), etc.; it may also be a Digital Signal Processor (DSP for short), an Application Specific Integrated Circuit (ASIC for short), a Field-Programmable Gate Array (FPGA for short), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0168] In another embodiment provided by the present application, there is also provided a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the vehicle fault diagnosis method described in the above embodiment.

[0169] In another embodiment provided by the present application, there is also provided a computer program product containing instructions, and when it runs on a computer, it causes the computer to execute the vehicle fault diagnosis method described in the above embodiment.

[0170] In the above embodiment, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer may be a general-purpose computer, a dedicated computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired manner (such as coaxial cable, optical fiber, Digital Subscriber Line (DSL)) or a wireless manner (such as infrared, wireless, microwave, etc.). The computer-readable storage medium may be any available medium that can be accessed by a computer, or a data storage device such as a server, data center, etc. that includes one or more integrated available media. The available medium may be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a Solid State Disk (SSD)).

[0171] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the said element.

[0172] Each embodiment in this specification is described in a related manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. For the embodiments of the apparatus, electronic device, computer-readable storage medium and computer program product containing instructions, since they are basically similar to the method embodiments, the description is relatively simple, and reference can be made to the corresponding parts of the method embodiments for the relevant content.

[0173] The above description is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application is included in the protection scope of the present application.

Claims

1. A vehicle fault diagnosis method, characterized in that: The method comprises: Obtaining fault description information and vehicle identification input by a user; the fault description information is used to indicate the vehicle fault condition; In a preset diagnostic database, a target fault code corresponding to the fault description information is determined, and a plurality of fault codes associated with the vehicle identification mark are determined; the diagnostic database stores a correspondence between the fault description information and the fault codes; In the case where the target fault code matches a plurality of fault codes corresponding to the vehicle identification mark, a fault diagnosis result is generated according to the target fault code to complete vehicle fault diagnosis.

2. The method according to claim 1, characterized in that The diagnostic database stores maintenance information corresponding to the fault code; the method further includes: In the diagnostic database, determining target maintenance information corresponding to the target fault code; The target maintenance information is added to the fault diagnosis result.

3. The method according to claim 2, characterized in that The method further comprises: Sending diagnostic data including the fault description information input by the user, the target fault code and the target maintenance information to a server; the server is used to determine a plurality of target diagnostic data including the fault description information in a stored diagnostic data set, and determine the fault codes and maintenance information that meet a preset quantity condition in the plurality of target diagnostic data as update data; The update data returned by the server is received, and based on the update data, the correspondence between the fault description information and the fault code and maintenance information in the diagnosis database is updated.

4. The method according to claim 1, characterized in that: The step of determining a target fault code corresponding to the fault description information in a preset diagnostic database includes: Determining at least two target fault codes corresponding to the fault description information in a preset diagnostic database; Sending at least two target fault codes and the vehicle identification to a server to obtain a trigger probability of each target fault code returned by the server; the server is used to determine the trigger probability of each target fault code in the stored fault code history data according to the vehicle identification; According to the triggering probability of each target fault code, a final target fault code is determined from at least two target fault codes.

5. The method according to claim 2, characterized in that: There are multiple target maintenance information; the method also includes: Acquire multiple feedback information input by the user for the fault diagnosis result; each feedback information is used to indicate valid maintenance information among multiple target maintenance information; According to the effective maintenance information respectively indicated by the multiple feedback information, the multiple target maintenance information in the fault diagnosis result is sorted to obtain a maintenance information sequence.

6. The method according to claim 1, characterized in that The step of determining a target fault code corresponding to the fault description information in a preset diagnostic database includes: Extracting user keywords from the fault description information input by the user, and respectively determining similarities between the user keywords and a plurality of fault description information in the diagnosis database; Determining target fault description information from the multiple fault description information in the diagnosis database according to the similarities corresponding to the multiple fault description information; A target fault code corresponding to the target fault description information is determined.

7. The method according to claim 1, characterized in that The step of determining a target fault code corresponding to the fault description information in a preset diagnostic database includes: Determining a target diagnostic database corresponding to the vehicle identification among a plurality of preset diagnostic databases; In a target diagnostic database, a target fault code corresponding to the fault description information is determined.

8. A vehicle fault diagnosis device, characterized in that: The device comprises: A data acquisition module, used to acquire fault description information and vehicle identification number input by a user; the fault description information is used to indicate the fault condition of the vehicle; A fault matching module is used to determine a target fault code corresponding to the fault description information and a plurality of fault codes associated with the vehicle identification mark in a preset diagnostic database; the diagnostic database stores a correspondence between the fault description information and the fault codes; The diagnosis result module is used to generate a fault diagnosis result according to the target fault code to complete vehicle fault diagnosis when the target fault code matches multiple fault codes corresponding to the vehicle identification mark.

9. An electronic device, characterized in that: include: A processor, a communication interface, a memory and a communication bus; wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory, used to store computer programs; The processor is used to implement the steps in the vehicle fault diagnosis method as described in any one of claims 1 to 7 when executing the program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the vehicle fault diagnosis method as described in any one of claims 1 to 7 are implemented.

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