Vehicle repair work order anomaly detection method, device, system and terminal equipment

Abstract

The application relates to an abnormality detection method, device, system and terminal equipment of a vehicle repair work order, comprising the following steps: acquiring first component information corresponding to a target vehicle before repair and second component information corresponding to the target vehicle after repair generated by an OBD detection device; acquiring a repair work order corresponding to the target vehicle, wherein the repair work order comprises third component information corresponding to a target component used in the repair process; comparing the first component information with the second component information, taking the part inconsistent with the first component information in the second component information as fourth component information; comparing the third component information with the fourth component information, and determining that the repair work order is abnormal in the case that the third component information and the fourth component information are inconsistent. Through the application, the problem that the safety of the repaired vehicle is reduced due to the lack of an abnormality detection method for the repair work order of the vehicle in the related art is solved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of on-board automatic diagnosis system, and particularly relates to an abnormality detection method, device, system and terminal equipment of a vehicle repair work order. BACKGROUND

[0002] With the development of social economy, the number of cars on the road is increasing, and traffic accidents are also increasing. Therefore, the demand for insurance repair of accident vehicles is gradually increasing.

[0003] However, at present, there are a large number of repair manufacturers without repair qualifications, which use unqualified parts and technology to repair accident vehicles through the way of "affiliation" and "borrowing" repair qualifications, and use expanded loss range or false repair work orders to cheat insurance companies. This will reduce the safety of the repaired accident vehicle, and cause great economic losses to the vehicle owner and the insurance company.

[0004] At present, there is no effective solution to the problem of lack of abnormality detection of vehicle repair work orders in related technologies, which leads to reduced safety of repaired vehicles. SUMMARY

[0005] The embodiments of the present application provide an abnormality detection method, device, system and terminal equipment of a vehicle repair work order, to at least solve the problem of lack of abnormality detection of vehicle repair work orders in related technologies, which leads to reduced safety of repaired vehicles.

[0006] In a first aspect, the embodiments of the present application provide an abnormality detection method of a vehicle repair work order, comprising: obtaining first detection information corresponding to a target vehicle before repair and second detection information corresponding to the target vehicle after repair generated by an OBD detection device, wherein the first detection information comprises first component information, and the second detection information comprises second component information; obtaining a repair work order corresponding to the target vehicle, wherein the repair work order comprises third component information corresponding to a target component used in the repair process of the target vehicle; comparing the first component information with the second component information, and regarding the part inconsistent with the first component information in the second component information as fourth component information; comparing the third component information with the fourth component information, and determining that the repair work order is abnormal in the case that the third component information and the fourth component information are inconsistent.

[0007] In some embodiments, the first detection information further comprises a fault code corresponding to the target vehicle; the repair work order further comprises fifth component information corresponding to a faulty component in the target vehicle before repair; after obtaining the repair work order corresponding to the target vehicle, the method further comprises: inputting the fault code into a trained fault component prediction model to obtain sixth component information matching the fault code output by the trained fault component prediction model; calculating the similarity between the fifth component information and the sixth component information; in the case where the similarity between the fifth component information and the sixth component information is less than a first preset threshold, determining that the repair work order is abnormal.

[0008] In some embodiments, the first detection information further comprises first location information of the target vehicle before repair, and the second detection information further comprises second location information of the target vehicle after repair; after obtaining the first detection information corresponding to the target vehicle before repair and the second detection information corresponding to the target vehicle after repair generated by the OBD detection device, the method further comprises: comparing the first location information and the second location information with third location information of a repair shop corresponding to the repair work order, respectively; in the case where the comparison result corresponding to the first location information or the comparison result corresponding to the second location information is inconsistent, determining that a location deviation event occurs in the repair process.

[0009] In some embodiments, the first detection information further comprises first mileage of the target vehicle before repair, and the second detection information further comprises second mileage of the target vehicle after repair; after obtaining the first detection information corresponding to the target vehicle before repair and the second detection information corresponding to the target vehicle after repair generated by the OBD detection device, the method further comprises: calculating the difference between the first mileage and the second mileage; in the case where the difference between the first mileage and the second mileage is greater than a second preset threshold, determining that a location deviation event occurs in the repair process.

[0010] In some embodiments, the third part information includes part names, part version numbers, and part serial numbers of the target parts; the fourth part information includes part names, part version numbers, and part serial numbers of the replacement parts; the comparison of the third part information and the fourth part information includes: comparing the part version numbers and the part serial numbers of the replacement parts with the part version numbers and the part serial numbers of the target parts with the same part names respectively; in the case that the comparison results corresponding to each of the replacement parts are consistent, it is determined that the comparison of the third part information and the fourth part information is consistent; in the case that the comparison result corresponding to at least one of the replacement parts is inconsistent, it is determined that the comparison of the third part information and the fourth part information is inconsistent.

[0011] In some embodiments, after obtaining the first detection information corresponding to the target vehicle before maintenance and the second detection information corresponding to the target vehicle after maintenance generated by the OBD detection device, the method further includes: storing the first detection information and the detection time stamp corresponding to the first detection information, and the second detection information and the detection time stamp corresponding to the second detection information in the blockchain.

[0012] In a second aspect, the embodiments of the present application provide an abnormality detection device for a vehicle maintenance work order, which includes: a first obtaining module configured to obtain first detection information corresponding to a target vehicle before maintenance and second detection information corresponding to the target vehicle after maintenance generated by an OBD detection device, wherein the first detection information includes first part information, and the second detection information includes second part information; a second obtaining module configured to obtain a maintenance work order corresponding to the target vehicle, wherein the maintenance work order includes third part information corresponding to target parts used in the maintenance process of the target vehicle; a comparison module configured to compare the first part information with the second part information, and take parts inconsistent with the first part information in the second part information as fourth part information; and a determination module configured to compare the third part information with the fourth part information, and determine that the maintenance work order is abnormal in the case that the comparison of the third part information and the fourth part information is inconsistent.

[0013] In a third aspect, the embodiments of the present application provide an abnormality detection system for a vehicle maintenance work order, which includes: an OBD detection device and a server; wherein the OBD detection device is configured to perform OBD detection on a target vehicle before maintenance to generate first detection information, and perform the OBD detection on the target vehicle after maintenance to generate second detection information; and the server is configured to perform the abnormality detection method for a vehicle maintenance work order according to any one of the first aspect.

[0014] In a fourth aspect, an embodiment of the present application provides a terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the vehicle repair work order anomaly detection method of any one of the first aspect when executing the computer program.

[0015] In a fifth aspect, an embodiment of the present application provides a computer program product, comprising a computer program, and the computer program, when executed, causes the vehicle repair work order anomaly detection method of any one of the first aspect to be performed.

[0016] Compared with the related art, the vehicle repair work order anomaly detection method, device, system and terminal device provided by the embodiments of the present application can obtain the first component information corresponding to the target vehicle before repair and the second component information corresponding to the target vehicle after repair generated by the OBD detection device, and obtain the repair work order corresponding to the target vehicle. By comparing the first component information with the second component information, the fourth component information corresponding to the replaced component in the repair process of the target vehicle can be obtained. By comparing the third component information corresponding to the target component included in the repair work order with the fourth component information, it can be determined whether the repair work order is abnormal. In this way, it can be determined whether the third component information (for example, component version number, component serial number) of the target component used in the repair included in the repair work order is consistent with the fourth component information corresponding to the replaced component. If the comparison result is inconsistent, it can be determined that the repair work order is abnormal. By detecting whether the repair work order is abnormal, it can be determined whether the repair process of the target vehicle has the situation of using unqualified components or component missing, thereby ensuring the safety of the target vehicle after repair. Through the present application, the problem of lack of abnormal detection of the repair work order of the vehicle in the related art and the resulting reduction in the safety of the repaired vehicle are solved, and the technical effect of improving the safety of the repaired vehicle by abnormally detecting the repair work order of the vehicle is achieved.

[0017] The details of one or more embodiments of the present application are presented in the following drawings and description to make other features, objects and advantages of the present application more clear and easy to understand. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0019] Figure 1 is a structural schematic diagram of an abnormality detection system of a vehicle repair work order according to an embodiment of the present application;

[0020] Figure 2 is a flowchart of an abnormality detection method of a vehicle repair work order according to an embodiment of the present application;

[0021] Figure 3 is a structural schematic diagram of an abnormality detection device of a vehicle repair work order according to an embodiment of the present application;

[0022] Figure 4 is a structural schematic diagram of a terminal device according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular sequences of steps, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application can be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known methods, devices, circuits, and

[0024] It is to be understood that the terminology "includes", "has", "holds", "contains" and / or "comprising", when used in this specification and in the following claims, indicates the presence of the described features, integers, steps, operations, elements, and / or components but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0025] It is also to be understood that the terminology "and / or" when used in this specification and in the following claims, refers to at least one of the items, or any combination of one or more of the items, and includes any possible combination of the items.

[0026] As used in this specification and in the claims, the terms "if" and "when" can be interpreted to mean "upon" or "in response to a determination" or "in response to a detection" depending on the context. Similarly, the phrase "if it is determined" or "if a detection is made" can be interpreted to mean "upon determining" or "in response to determining" or "upon detecting" or "in response to detecting" depending on the context.

[0027] In addition, in the description of the specification and the appended claims, the terms "first", "second", "third", etc. are used only to distinguish descriptions, and cannot be understood as indicating or implying relative importance.

[0028] Reference to“one embodiment” or“some embodiments” or“an embodiment” or“some embodiments” etc. in the present application description means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the application. Thus, appearances of the phrases“in one embodiment” or“in some embodiments” or“in other embodiments” or“in additional embodiments” etc. in various places in the specification are not necessarily all referring to the same embodiment, but can refer to one or more but not all embodiments, unless otherwise specifically noted. The terms“including,”“comprising,”“having” and variations thereof herein are meant to be broad and encompass the terms“consisting of” and“consisting essentially of,” unless otherwise noted.

[0029] With the development of social economy, the number of cars on the road is increasing, and traffic accidents are also increasing, so the demand for insurance repair of accident vehicles is gradually increasing.

[0030] However, at present, there are a large number of repair manufacturers without repair qualifications repairing accident vehicles by means of“affiliation” and“borrowing” repair qualifications, using unqualified parts and technology, and using expanded loss range or false repair work orders to cheat insurance companies for insurance claims. This will reduce the safety of the repaired accident vehicle and cause great economic losses to the vehicle owner and the insurance company.

[0031] At present, there is no effective solution to the problem of lack of abnormal detection of vehicle repair work orders in the related art, which leads to reduced safety of the repaired vehicle.

[0032] In view of this, the embodiment of the present application provides an abnormality detection method of a vehicle maintenance work order. The first component information corresponding to a target vehicle before maintenance and the second component information corresponding to the target vehicle after maintenance are generated by an OBD (On-Board Diagnostics, vehicle-mounted automatic diagnosis system) detection device, and the maintenance work order corresponding to the target vehicle is obtained. By comparing the first component information with the second component information, the fourth component information corresponding to the replaced component in the maintenance process of the target vehicle can be obtained. By comparing the third component information corresponding to the target component included in the maintenance work order with the fourth component information, whether the maintenance work order is abnormal can be determined. In this way, whether the third component information (for example, component version number, component serial number) of the target component used in the maintenance included in the maintenance work order is consistent with the fourth component information corresponding to the replaced component can be determined. If the comparison result is inconsistent, it can be determined that the maintenance work order is abnormal. By detecting whether the maintenance work order is abnormal, whether the maintenance process of the target vehicle has the use of unqualified components or the absence of components and the like can be determined, so as to ensure the safety of the target vehicle after maintenance. Through the present application, the problem that the related art lacks a way to detect the abnormality of the vehicle maintenance work order and thus the safety of the vehicle after maintenance is reduced is solved, and the technical effect of improving the safety of the vehicle after maintenance by detecting the abnormality of the vehicle maintenance work order is achieved.

[0033] The exemplary application architecture of the abnormality detection system of the vehicle maintenance work order provided by the embodiment of the present application is described below, referring to Figure 1 , Figure 1 is a structural schematic diagram of the abnormality detection system 10 of the vehicle maintenance work order according to an embodiment of the present application, comprising: an OBD detection device 110 and a server 120; wherein the OBD detection device 110 is configured to perform OBD detection on a target vehicle 130 before maintenance to generate first detection information, and perform OBD detection on the target vehicle 130 after maintenance to generate second detection information. Each OBD detection device 110 can establish a connection with the server 120 through a wired network or a wireless network.

[0034] The server 120 can be a single server, or can also be a server cluster composed of multiple servers (or micro servers). The server cluster can also be a distributed cluster. The embodiment of the present application does not limit the specific implementation mode of the server 120.

[0035] In the embodiment, the OBD detection device 110 has a plug-in port matched with the on-board OBD interface in the target vehicle 130. When the plug-in port of the OBD detection device 110 is clamped with the on-board OBD interface, the OBD detection device 110 can obtain the data information of the OBD of the target vehicle 130. The OBD of the target vehicle 130 can monitor the data information of multiple subsystems and components in the target vehicle 130. The OBD can be connected to the electrical control unit (ECU) of the target vehicle 130, and the ECU has the function of detecting and analyzing various faults. When a fault occurs in a system or component in the target vehicle 130, the ECU can record the fault information and related codes, and issue a warning through a fault light to inform the driver. The OBD detection device 110 can access and process the fault information recorded by the ECU through the on-board OBD interface, and generate the first detection information and the second detection information in the form of a report based on the fault information recorded by the ECU.

[0036] Among them, since the first detection information is obtained before the target vehicle 130 is repaired, the first detection information can include: vehicle information (such as license plate number, vehicle model, first mileage, etc.), number of reported abnormalities (including the number of abnormalities corresponding to each subsystem of the target vehicle 130), summary information of each abnormality, first component information of each component contained in each subsystem, and fault codes corresponding to each abnormality, etc.

[0037] The second detection information is obtained after the target vehicle 130 is repaired, so the second detection information can include: vehicle information (such as license plate number, vehicle model, second mileage, etc.), and second component information of each component contained in each subsystem, etc.

[0038] After generating the first detection information and the second detection information, the OBD detection device 110 can send the first detection information and the second detection information corresponding to the target vehicle 130 to the server 120. Alternatively, the OBD detection device 110 can send the first detection information and the second detection information corresponding to the target vehicle 130 to the cloud, and the server 120 obtains the first detection information and the second detection information corresponding to the target vehicle 130 from the cloud.

[0039] The server 120 can obtain a repair work order corresponding to the target vehicle 130, wherein the repair work order includes third component information corresponding to the target component used in the repair process of the target vehicle 130; compare the first component information with the second component information, and take the part inconsistent with the first component information in the second component information as the fourth component information; compare the third component information with the fourth component information, and determine that the repair work order is abnormal in the case that the third component information and the fourth component information are inconsistent.

[0040] In the embodiment, the server 120 can be equipped with an insurance company's claim settlement system. The OBD detection device 110 for vehicle maintenance detection at a vehicle repair factory can be added with a function of selecting a corresponding insurance company, and issuing an instruction by the insurance company to the repair factory that undertakes a repair order, requiring the repair factory to perform pre-repair detection and post-repair detection on the target vehicle 130 using the OBD detection device 110, and selecting a corresponding insurance company to upload the first detection information and the second detection information in the form of a report.

[0041] In the embodiment, the repair order can be directly uploaded to the server 120 by the repair factory. Alternatively, the repair factory can upload the repair order to the cloud, and the server 120 obtains the repair order corresponding to the target vehicle 130 from the cloud. The repair order includes third component information of a target component used by the repair factory in the repair process of the target vehicle 130.

[0042] The server 120 can compare the first component information with the second component information, and determine the part inconsistent with the first component information in the second component information as fourth component information, that is, the fourth component information of the component replaced by the target vehicle 130 before and after the repair can be obtained.

[0043] The server 120 can compare the third component information with the fourth component information, and determine whether the repair order is abnormal.

[0044] In specific implementation, if the third component information is consistent with the fourth component information, it can be determined that the repair order is normal, and there is no abnormal behavior such as expanding the loss range or fraud. If the third component information is inconsistent with the fourth component information, for example, there are more components in the third component information than the components contained in the fourth component information, or there are components with the same name in the third component information and the fourth component information, but the component information (such as component version number or component serial number) is inconsistent, it can be determined that the repair order is abnormal, and there is an abnormal behavior such as expanding the loss range or fraud.

[0045] In specific implementation, the server 120 and the OBD detection device 110 can adopt the composition shown in Figure 4 or include the components shown in Figure 4 . Figure 4is a structural schematic diagram of a terminal device according to an embodiment of the present application. When the terminal device 4 has the function of the server 120 described in the embodiments of the present application, the terminal device 4 can be the server 120 or a chip or system on chip in the server 120. When the terminal device 4 has the function of the OBD detection device 110 described in the embodiments of the present application, the terminal device 4 can be the OBD detection device 110 or a chip or system on chip in the OBD detection device 110.

[0046] In some embodiments, the server 120 provided by the embodiments of the present application can be implemented in a software manner. For example, it can be loaded on Figure 4 The server 120 in the memory 41 of the terminal device 4 shown can be software in the form of programs and plug-ins, etc., including a first acquisition module 30, a second acquisition module 31, a comparison module 32, and a determination module 33. These modules are logical, and thus can be combined or further split according to the implemented functions.

[0047] The functions of the various modules will be described below.

[0048] The vehicle maintenance work order anomaly detection method provided by the embodiments of the present application will be described in combination with an exemplary application architecture of the vehicle maintenance work order anomaly detection system 10 provided by the embodiments of the present application.

[0049] The vehicle maintenance work order anomaly detection method provided by an embodiment of the present application will be described below. Please refer to Figure 2 The vehicle maintenance work order anomaly detection method provided by an embodiment of the present application will be described below. Please refer to Figure 2 , Figure 2 is a flowchart of a vehicle maintenance work order anomaly detection method according to an embodiment of the present application. As shown in the figure, the method includes: Figure 2

[0050] In step S201, first detection information corresponding to the target vehicle before maintenance and second detection information corresponding to the target vehicle after maintenance generated by the OBD detection device are acquired, wherein the first detection information includes first component information, and the second detection information includes second component information.

[0051] In the present embodiment, the OBD detection device can access and process the information recorded by the ECU in the target vehicle through the vehicle-mounted OBD interface (for example, a standard data interface), and generate the first detection information and the second detection information in the form of reports based on the information recorded by the ECU.

[0052] ​In a specific implementation, the staff of the repair factory can use the OBD detection device to perform pre-repair detection on the target vehicle before repairing the target vehicle, generate first detection information, and send the first detection information to the cloud; the staff of the repair factory can also use the OBD detection device to perform post-repair detection on the target vehicle after the target vehicle has completed repair, generate second detection information, and send the second detection information to the cloud.

[0053] The first detection information and the second detection information can each include vehicle information (for example, a license plate number, a vehicle model, a vehicle frame number, etc.) of the target vehicle, and the first detection information and the second detection information corresponding to the target vehicle can be obtained from the cloud based on the vehicle information.

[0054] In one embodiment, the first detection information further includes first location information of the target vehicle before repair, and the second detection information further includes second location information of the target vehicle after repair; after obtaining the first detection information corresponding to the target vehicle before repair and the second detection information corresponding to the target vehicle after repair generated by the OBD detection device, the method further includes: comparing the first location information and the second location information with third location information of the repair factory corresponding to the repair work order, and determining that a location deviation event occurs in the repair process in a case where a comparison result corresponding to the first location information or a comparison result corresponding to the second location information is inconsistent.

[0055] In this embodiment, the OBD detection device can also obtain first location information of the target vehicle before repair and second location information of the target vehicle after repair determined by a Global Positioning System (GPS) or a Beidou Navigation Satellite System (BDS). By comparing the first location information and the second location information with third location information of the repair factory corresponding to the repair work order, it can be determined whether the target vehicle is detected and repaired in the area (i.e., the third location information) of the designated repair factory, thereby avoiding the case where other repair factories fraudulently use repair qualifications of the designated repair factory to detect and repair the target vehicle.

[0056] In a specific implementation, it can be directly determined whether the first location information (for example, coordinates, latitude and longitude, etc.) or the second location information is consistent with the third location information; if the first location information is inconsistent with the third location information or the second location information is inconsistent with the third location information, it is determined that a location deviation event occurs in the repair process, which indicates that the repair process of the target vehicle can have the case where a repair factory without repair qualifications repairs the target vehicle by means of "affiliation", "borrowing" of repair qualifications, etc.

[0057] In this way, the transparency of the target vehicle repair process can be effectively ensured, the insurance company can be timely reported when the position deviation event occurs in the repair process of the target vehicle, the repair process of the target vehicle is investigated by the insurance company, the target vehicle repaired by the repair shop without repair qualification is prevented from directly returning to the vehicle owner, and the interests of the vehicle owner and the insurance company are protected.

[0058] In an embodiment, the first detection information further includes a first mileage of the target vehicle before repair, and the second detection information further includes a second mileage of the target vehicle after repair; after obtaining the first detection information corresponding to the target vehicle before repair and the second detection information corresponding to the target vehicle after repair generated by the OBD detection device, the method further includes: calculating the difference between the first mileage and the second mileage; in the case that the difference between the first mileage and the second mileage is greater than a second preset threshold, it is determined that the repair process has a position deviation event.

[0059] In this embodiment, the vehicle mileage difference in the first detection information and the second detection information can also be used to determine whether the target vehicle is detected and repaired within the area of the designated repair shop, so as to avoid other repair shops from using the repair qualification of the above-mentioned designated repair shop to detect and repair the target vehicle.

[0060] In specific implementation, when the difference between the first mileage and the second mileage is greater than the second preset threshold (for example, the second preset threshold can be 5 kilometers, 2.5 kilometers, etc.), it can be determined that the repair process has a position deviation event.

[0061] Step S202, obtaining a repair work order corresponding to the target vehicle, wherein the repair work order includes third component information corresponding to a target component used in the repair process of the target vehicle.

[0062] In this embodiment, the repair shop can upload the repair work order to the cloud, and can obtain the repair work order corresponding to the target vehicle from the cloud. The repair work order can include third component information corresponding to a target component used in the repair process of the target vehicle, and in addition, the repair work order can also include fifth component information corresponding to a fault component in the target vehicle before repair.

[0063] Specifically, the repair order can include fifth component information of the faulty components in the target vehicle before repair determined by the repair manufacturer after determining the loss of the target vehicle. The fifth component information can include the faulty subsystems in the target vehicle before repair, and the information (e.g., part name, part version number, and part serial number) corresponding to the faulty components contained in each faulty subsystem. In addition, the repair order can also include third component information corresponding to the target components used by the repair manufacturer after repairing the target vehicle. The third component information can also include price information of each target component, etc.

[0064] In one embodiment, the first detection information further includes a fault code corresponding to the target vehicle; after obtaining the repair order corresponding to the target vehicle, the method further includes the following steps:

[0065] Step 1, input the fault code into the trained faulty component prediction model to obtain sixth component information matched with the fault code output by the trained faulty component prediction model.

[0066] Step 2, calculate the similarity of the fifth component information and the sixth component information.

[0067] Step 3, in the case where the similarity of the fifth component information and the sixth component information is less than a first preset threshold, determine that the repair order is abnormal.

[0068] In this embodiment, fault code data of various automobile manufacturers and vehicle models can be collected, including fault subsystems corresponding to different fault codes, and faulty components contained in each fault subsystem. These data can be obtained from repair manuals of automobile manufacturers, OBD-II databases, fault diagnosis records, and repair cases. In addition, a large amount of historical repair order data can also be obtained from the insurance company's claim system, which covers repair records of different automobile manufacturers and different vehicle models, including fault codes, repair items, component replacement conditions, repair costs, repaired subsystems, etc.

[0069] A machine learning model (e.g., decision tree, random forest, support vector machine, etc.) can be used to establish a mapping from fault codes to fault subsystems / components based on the above-mentioned fault code data and historical repair order data through fault codes, fault subsystems corresponding to fault codes, and faulty components. Moreover, by training the above-mentioned machine learning model, the trained faulty component prediction model can output sixth component information matched with the fault code based on the input fault code, which includes predicted fault subsystems matched with the fault code, and information corresponding to predicted fault components contained in each predicted fault subsystem.

[0070] Then, the similarity between the fifth component information (including the faulty subsystems in the target vehicle before repair and the information corresponding to the faulty components included in each faulty subsystem) of the faulty components in the target vehicle before repair included in the repair order and the sixth component information described above can be calculated.

[0071] Specifically, the cosine similarity or Jaccard similarity algorithm can be used to calculate the similarity between the fifth component information and the sixth component information. If the similarity is less than a first preset threshold (for example, which can be set to 0.8, 0.6, etc.), it can be determined that the repair order is abnormal, which means that the components and subsystems (i.e., the fifth component information) that the target vehicle needs to replace reported by the repair manufacturer are inconsistent with the historical record standard (i.e., the sixth component information) predicted by the faulty component prediction model (for example, the fifth component information requires to repair a subsystem or component that does not exist in the sixth component information).

[0072] In this way, when it is detected that the repair order is abnormal, the insurance company can be timely reported, and the insurance company can analyze and judge the repair order corresponding to the target vehicle, prevent the repair order reported by the repair manufacturer from expanding the loss range and other abnormal behaviors, which not only can improve the transparency of the repair process of the target vehicle, but also can help the insurance company to prevent dishonest repair behavior, thereby protecting the rights and interests of the vehicle owner and the insurance company.

[0073] In step S203, the first component information is compared with the second component information, and the part of the second component information that is inconsistent with the first component information is taken as the fourth component information.

[0074] In this embodiment, the first component information is the information obtained by detecting the target vehicle before repair using the OBD detection device, and the second component information is the information obtained by detecting the target vehicle after repair using the OBD detection device. Therefore, the part of the second component information that is inconsistent with the first component information can be taken as the information of the actual replaced components in the repair process of the target vehicle, and the fourth component information is obtained.

[0075] In one embodiment, after obtaining the first detection information corresponding to the target vehicle before repair and the second detection information corresponding to the target vehicle after repair generated by the OBD detection device, the method further comprises: storing the first detection information and the detection timestamp corresponding to the first detection information, and the second detection information and the detection timestamp corresponding to the second detection information in the blockchain.

[0076] In the embodiment, the first detection information, the detection timestamp corresponding to the first detection information, the second detection information, and the detection timestamp corresponding to the second detection information can be stored by a smart contract or other blockchain technology, and they or their hash values can be stored in the blockchain as powerful and credible evidence in the vehicle insurance inspection and claim process. After the target vehicle is repaired, the first component information in the first detection information stored in the blockchain can be compared with the second component information in the second detection information stored in the blockchain, and the non-tamperability and transparency of the blockchain are used to ensure that the first component information and the second component information cannot be maliciously modified, thereby ensuring the authenticity and transparency of the repair process.

[0077] In step S204, the third component information is compared with the fourth component information, and in the case that the third component information is inconsistent with the fourth component information, it is determined that the repair work order is abnormal.

[0078] In the embodiment, if the third component information is consistent with the fourth component information, it can be determined that the repair work order is normal, and there is no abnormal behavior such as expanding the loss range or fraud. If the third component information is inconsistent with the fourth component information, for example, there are more components in the third component information than in the fourth component information, or there are components with the same name in the third component information and the fourth component information, but the component information (such as component version number or component serial number) is inconsistent, it can be determined that the repair work order is abnormal, and there is an abnormal behavior such as expanding the loss range or fraud.

[0079] In one embodiment, the third component information includes the component name, component version number, and component serial number of each target component; the fourth component information includes the component name, component version number, and component serial number of the plurality of replacement components; and the comparison of the third component information and the fourth component information includes the following steps:

[0080] Step 1, compare the component version number and the component serial number of the replacement component with the component version number and the component serial number of the target component with the same component name.

[0081] Step 2, in the case that the comparison results of each replacement component are consistent, it is determined that the comparison of the third component information and the fourth component information is consistent.

[0082] Step 3, in the case that the comparison result of at least one replacement component is inconsistent, it is determined that the comparison of the third component information and the fourth component information is inconsistent.

[0083] In the present embodiment, since the OBD detection device usually detects information of electrical devices inside the target vehicle; and the repair work order includes, in addition to the information of electrical devices, information of damage to the body of the target vehicle (e.g. denting of sheet metal, scratching of vehicle paint, etc.). Therefore, the target parts and the replacement parts with the same part name can be compared one by one based on the part name of the target parts and the replacement parts.

[0084] For example, the third part information includes a target part with a part name of "brake electronic device", and the fourth part information includes a replacement part with a part name of "brake electronic device". At this time, the part version number and the part serial number of the replacement part and the part version number and the part serial number of the target part can be compared respectively.

[0085] Specifically, the part version number of the replacement part with the part name of "brake electronic device" can include a software version number and a hardware version number, and the software version number, the hardware version number and the part serial number of the replacement part can be compared with the software version number, the hardware version number and the part serial number of the target part with the part name of "brake electronic device" one by one. In this way, the replacement parts and the target parts with the same part name are compared one by one, and in the case that the comparison results of each replacement part are consistent, it is determined that the third part information and the fourth part information are consistent; or in the case that the comparison results of at least one replacement part are inconsistent, it is determined that the third part information and the fourth part information are inconsistent.

[0086] By the above steps S201 to S204, by acquiring the first component information corresponding to the target vehicle before maintenance generated by the OBD detection device, and the second component information corresponding to the target vehicle after maintenance, and acquiring the maintenance work order corresponding to the target vehicle; by comparing the first component information with the second component information, the fourth component information corresponding to the replaced component in the maintenance process of the target vehicle can be obtained; by comparing the third component information corresponding to the target component contained in the maintenance work order with the fourth component information, it can be determined whether the maintenance work order is abnormal. In this way, it can be determined whether the third component information (for example, component version number, component serial number) of the target component used in the maintenance contained in the maintenance work order is consistent with the fourth component information corresponding to the replaced component, and if the comparison result is inconsistent, it can be determined that the maintenance work order is abnormal; by detecting whether the maintenance work order is abnormal, it can be determined whether the maintenance process of the target vehicle exists the use of unqualified components or the absence of components and the like, thereby ensuring the safety of the target vehicle after maintenance. Through the present application, the problem of lack of abnormal detection of vehicle maintenance work order in related technologies and thus the safety of the vehicle after maintenance is reduced is solved, and the technical effect of improving the safety of the vehicle after maintenance by detecting the abnormality of the vehicle maintenance work order is achieved.

[0087] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0088] The vehicle maintenance work order abnormality detection method described in the above embodiment, Figure 3 The structure of the vehicle maintenance work order abnormality detection device according to an embodiment of the present application is shown, and only the parts related to the embodiment of the present application are shown for convenience of explanation.

[0089] Please refer to Figure 3The vehicle repair order abnormality detection device 3 comprises: a first acquisition module 30 configured to acquire first detection information corresponding to the target vehicle before repair and second detection information corresponding to the target vehicle after repair generated by the OBD detection device, wherein the first detection information comprises first component information, and the second detection information comprises second component information; a second acquisition module 31 configured to acquire a repair order corresponding to the target vehicle, wherein the repair order comprises third component information corresponding to a target component used in the repair process of the target vehicle; a comparison module 32 configured to compare the first component information with the second component information, and take the part of the second component information inconsistent with the first component information as fourth component information; and a determination module 33 configured to compare the third component information with the fourth component information, and determine that the repair order is abnormal in the case that the third component information and the fourth component information are inconsistent.

[0090] In one embodiment, the first detection information further comprises a fault code corresponding to the target vehicle; the repair order further comprises fifth component information corresponding to a faulty component in the target vehicle before repair; and the determination module 33 is further configured to input the fault code into a trained fault component prediction model to obtain sixth component information matched with the fault code output by the trained fault component prediction model, calculate the similarity of the fifth component information and the sixth component information, and determine that the repair order is abnormal in the case that the similarity of the fifth component information and the sixth component information is less than a first preset threshold.

[0091] In one embodiment, the first detection information further comprises first location information of the target vehicle before repair, and the second detection information further comprises second location information of the target vehicle after repair; and the determination module 33 is further configured to compare the first location information and the second location information with third location information of a repair factory corresponding to the repair order respectively, and determine that a location deviation event occurs in the repair process in the case that the comparison result corresponding to the first location information or the comparison result corresponding to the second location information is inconsistent.

[0092] In one embodiment, the first detection information further comprises a first mileage of the target vehicle before repair, and the second detection information further comprises a second mileage of the target vehicle after repair; and the determination module 33 is further configured to calculate the difference between the first mileage and the second mileage, and determine that a location deviation event occurs in the repair process in the case that the difference between the first mileage and the second mileage is greater than a second preset threshold.

[0093] In one embodiment, the third component information includes part names, part version numbers and part serial numbers of the target components, and the fourth component information includes part names, part version numbers and part serial numbers of the replacement components. The determining module 33 is further configured to compare the part version numbers and the part serial numbers of the replacement components with the part version numbers and the part serial numbers of the target components having the same part names, respectively. In a case where the comparison results corresponding to all the replacement components are consistent, it is determined that the third component information and the fourth component information are consistent. In a case where the comparison results corresponding to at least one replacement component are inconsistent, it is determined that the third component information and the fourth component information are inconsistent.

[0094] In one embodiment, the first obtaining module 30 is further configured to store the first detection information, the detection time stamp corresponding to the first detection information, the second detection information and the detection time stamp corresponding to the second detection information in the blockchain.

[0095] It should be noted that the information interaction and execution process between the above apparatuses / units are based on the same concept as the method embodiments of the present application, and the specific functions and technical effects thereof can be referred to the method embodiments part, which will not be repeated here.

[0096] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional units and modules is exemplified, and in actual application, the above functions can be completed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to complete all or part of the above described functions. The functional units and modules in the embodiments can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of software functional unit. In addition, the specific names of the functional units and modules are only for easy distinction, and do not limit the protection scope of the present application. The specific working process of the units and modules in the system can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0097] Figure 4 is a structural schematic diagram of a terminal device according to an embodiment of the present application. As shown in Figure 4 the terminal device 4 includes at least one processor 40 Figure 4 only one processor is shown), a memory 41, and a computer program 42 stored in the memory 41 and executable on the at least one processor 40, and the processor 40 implements the steps in any of the vehicle repair work order anomaly detection method embodiments described above when executing the computer program 42.

[0098] The terminal device 4 can be a desktop computer, a notebook computer, a palm computer, a cloud server, and the like. The terminal device 4 can include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art can understand that the terminal device 4 can include more or fewer components than shown, or can combine some components, or include different components, for example, can also include an input / output device, a network access device, and the like. Figure 4 The terminal device 4 is only an example and does not constitute a limitation on the terminal device 4, and can include more or fewer components than shown, or can combine some components, or include different components.

[0099] The processor 40 can be a central processing unit (CPU), and can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or the like. The general-purpose processor can be a microprocessor or can also be any conventional processor.

[0100] The memory 41 can be an internal storage unit of the terminal device 4 in some embodiments, for example, a hard disk or a memory of the terminal device 4. The memory 41 can also be an external storage device of the terminal device 4 in other embodiments, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, or the like. In other embodiments, the memory 41 can include both an internal storage unit and an external storage device of the terminal device 4. The memory 41 is used to store an operating system, an application program, a boot loader, data, and other programs, for example, program codes of the computer program 42, and the like. The memory 41 can also be used to temporarily store data that has been output or will be output.

[0101] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the steps in the vehicle maintenance work order exception detection method embodiments.

[0102] The embodiment of the present application provides a computer program product. When the computer program product is run on a mobile terminal, the mobile terminal is caused to implement the steps in the vehicle maintenance work order exception detection method embodiments.

[0103] The computer program can be stored in a computer readable storage medium. The computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk, or an optical data storage device, among others. The computer program can be downloaded from a network, such as the Internet, or can be copied from another computer readable storage medium.

[0104] In the above embodiments, the description of each embodiment has its own focus, and the parts not described or recorded in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0105] Those skilled in the art can appreciate that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0106] In the embodiments provided in the present application, it should be understood that the disclosed apparatus / network device and method can be implemented in other ways. For example, the apparatus / network device embodiments described above are only schematic. The division of the modules or units is only a logical function division, and there can be another division in actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection can be indirect coupling or communication connection through some interface, device or unit, and can be electrical, mechanical or other forms.

[0107] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the present embodiment.

[0108] The above examples are only used to illustrate the technical solutions of the present application, but not to limit the present application; although the present application has been described in detail with reference to the foregoing examples, those ordinarily skilled in the art should understand: the technical solutions recorded in the foregoing examples can still be modified, or some technical features can be replaced equivalently; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for detecting anomalies in vehicle repair work orders, characterized in that, include: Obtain first detection information corresponding to the target vehicle before repair and second detection information corresponding to the target vehicle after repair, generated by the OBD detection equipment, wherein the first detection information includes first component information and the second detection information includes second component information; Obtain the repair work order corresponding to the target vehicle, wherein the repair work order includes information on the third component corresponding to the target component used in the repair process of the target vehicle; The first component information is compared with the second component information, and the part of the second component information that is inconsistent with the first component information is taken as the fourth component information. The information of the third component is compared with the information of the fourth component. If the information of the third component is inconsistent with the information of the fourth component, it is determined that the maintenance work order is abnormal.

2. The method according to claim 1, characterized in that, The first detection information also includes a fault code corresponding to the target vehicle; the repair work order also includes information on a fifth component corresponding to the faulty component in the target vehicle before repair; after obtaining the repair work order corresponding to the target vehicle, the method further includes: The fault code is input into the trained fault component prediction model to obtain the sixth component information that matches the fault code, output by the trained fault component prediction model. Calculate the similarity between the information of the fifth component and the information of the sixth component; If the similarity between the information of the fifth component and the information of the sixth component is less than a first preset threshold, it is determined that the repair work order is abnormal.

3. The method according to claim 1 or 2, characterized in that, The first detection information further includes the first location information of the target vehicle before repair, and the second detection information further includes the second location information of the target vehicle after repair; after acquiring the first detection information corresponding to the target vehicle before repair and the second detection information corresponding to the target vehicle after repair generated by the OBD detection device, the method further includes: The first location information and the second location information are compared with the third location information of the repair manufacturer corresponding to the repair work order. If the comparison result corresponding to the first location information or the comparison result corresponding to the second location information is inconsistent, it is determined that a location offset event has occurred in the repair process.

4. The method according to claim 1 or 2, characterized in that, The first detection information also includes a first mileage of the target vehicle before repair, and the second detection information also includes a second mileage of the target vehicle after repair; after acquiring the first detection information corresponding to the target vehicle before repair and the second detection information corresponding to the target vehicle after repair generated by the OBD detection device, the method further includes: Calculate the difference between the first mileage and the second mileage; If the difference between the first mileage and the second mileage is greater than a second preset threshold, it is determined that a position offset event has occurred during the maintenance process.

5. The method according to claim 1 or 2, characterized in that, The third component information includes the part name, part version number, and part serial number of each target component; the fourth component information includes the part name, part version number, and part serial number of multiple replacement components. Comparing the information of the third component with the information of the fourth component includes: The part version number and part serial number of the replacement part are compared with the part version number and part serial number of the target part with the same part name; If the comparison results for each of the replaced parts are consistent, it is determined that the information of the third part is consistent with the information of the fourth part. If the comparison results corresponding to at least one of the replaced parts are inconsistent, it is determined that the information of the third part is inconsistent with the information of the fourth part.

6. The method according to claim 1 or 2, characterized in that, After acquiring the first detection information corresponding to the target vehicle before repair and the second detection information corresponding to the target vehicle after repair generated by the OBD detection equipment, the method further includes: The first detection information and the detection timestamp corresponding to the first detection information, as well as the second detection information and the detection timestamp corresponding to the second detection information, are stored in the blockchain.

7. An anomaly detection device for vehicle repair work orders, characterized in that, include: The first acquisition module is used to acquire first detection information corresponding to the target vehicle before repair and second detection information corresponding to the target vehicle after repair, generated by the OBD detection equipment. The first detection information includes first component information and the second detection information includes second component information. The second acquisition module is used to acquire a repair work order corresponding to the target vehicle, wherein the repair work order includes information on a third component corresponding to the target component used in the repair process of the target vehicle. The comparison module is used to compare the first component information with the second component information, and to take the part of the second component information that is inconsistent with the first component information as the fourth component information. The determination module is used to compare the information of the third component with the information of the fourth component, and if the information of the third component is inconsistent with the information of the fourth component, it determines that the maintenance work order is abnormal.

8. An anomaly detection system for vehicle repair work orders, characterized in that, include: OBD detection equipment and server; wherein, the OBD detection equipment is used to perform OBD detection on the target vehicle before repair to generate first detection information, and to perform the OBD detection on the target vehicle after repair to generate second detection information; the server is used to execute the abnormal detection method of the vehicle repair work order as described in any one of claims 1 to 6.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the anomaly detection method for vehicle repair work orders as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes a computer program, which, when run, causes the anomaly detection method for vehicle repair work orders as described in any one of claims 1 to 6 to be executed.

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