A fault diagnosis method for an in-vehicle online service system

Abstract

The application discloses a fault diagnosis method of a vehicle-mounted online service system, and comprises the following steps: S1) detecting whether a vehicle communication port connection is normal, and if normal, acquiring vehicle log data; S2) acquiring dotting information data, wherein the dotting information data is acquired according to a signal of a dotting device; S3) performing data optimization and performance analysis on the dotting information data and the vehicle log data; and S4) outputting results of the data optimization and performance analysis, wherein the data optimization result comprises fault logs of the vehicle-mounted online service system, and the performance analysis result comprises a response success rate and a response time of the vehicle-mounted online service system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automobiles, in particular to the field of diagnosis of an online service system in a vehicle. BACKGROUND

[0002] With the rapid development of intelligentization and networking of the automobile industry, the online service system in a vehicle has become one of the key development projects in the automobile industry. The normal operation of the online service system in a vehicle requires the cooperation of multiple electronic control units (ECUs) in the vehicle, a background and a mobile phone online service APP, and therefore when the function of the online service system in a vehicle is tested, the response of each end needs to be considered, that is, the tester needs to pay attention to the performance of end-to-end during the test and capture the fault logs of each end so as to analyze the problems. Before the development of the present application, the tester needs to manually configure the connection of a computer and a hardware interface card and the like to realize the capture of the log data of the vehicle end, different hardware corresponds to the capture of different log types, which leads to a repeated and complicated configuration process and is prone to human errors. For problems that are not easy to reproduce, it will be difficult to diagnose, analyze and solve once the log is missing, and the configuration of each software and corresponding hardware requires a higher quality of the tester, which will result in a higher training cost. When evaluating the performance of the test object, the tester often uses a stopwatch or a vehicle data recorder to record the response time and the response success rate, which is extremely low in work efficiency and the statistical result is not accurate. After the test is completed, the tester needs to store and name the logs in multiple formats and deliver them through a U disk, a network disk and the like, when multiple projects are carried out at the same time, there are many bugs detected, which results in a large difficulty, low efficiency, high error rate and untimely feedback of transmission. In addition, the diagnostic personnel often need to open multiple logs at the same time when diagnosing a problem to search for key information, which results in a low diagnosis efficiency. SUMMARY

[0003] To solve the above problems, the purpose of the present application is to provide a diagnosis and analysis system which collects data from a terminal and performs intelligent dotting, synchronization, integration and diagnosis and analysis throughout the whole process.

[0004] The present application provides a fault diagnosis method of an online service system in a vehicle, which comprises the following steps:

[0005] S1) detecting whether the connection of a vehicle communication port is normal, and if so, acquiring vehicle log data;

[0006] S2) acquiring dotting information data, wherein the dotting information data is acquired according to the signal of a dotting device;

[0007] S3) performing data optimization and performance analysis on the dotting information data and the vehicle log data;

[0008] S4) outputting results of the data optimization and performance analysis, wherein the results of the data optimization include fault logs of the vehicle online service system, and the results of the performance analysis include a response success rate and a response time of the vehicle online service system.

[0009] Preferably, the fault diagnosis method of the vehicle online service system, the vehicle log data includes vehicle information, CAN bus log, domain controller log and vehicle-specific host controller log.

[0010] Preferably, the fault diagnosis method of the vehicle online service system, the data optimization further includes:

[0011] The vehicle log data and the point information data are stored in a timing rolling naming manner.

[0012] A log database is established, and the log database includes the vehicle log data and the point information data.

[0013] The log data corresponding to the point time point is extracted according to the point time point of the point information data.

[0014] Preferably, the fault diagnosis method of the vehicle online service system, the log database is established by SQL.

[0015] Preferably, the fault diagnosis method of the vehicle online service system, the performance analysis further includes:

[0016] The preset rule information is extracted according to the point information data and the embedded point keywords in the vehicle log data, and the preset rule information includes performance test related information of the vehicle online service system.

[0017] The preset rule information is labeled to obtain labeled preset rule information.

[0018] The labeled preset rule information is searched and the response success rate and the response time of the vehicle online service system are calculated.

[0019] Preferably, the fault diagnosis method of the vehicle online service system, the preset rule information is extracted according to a regular expression.

[0020] Preferably, the fault diagnosis method of the vehicle online service system, the preset rule information is labeled using data mapping abstraction.

[0021] Preferably, the fault diagnosis method of the vehicle online service system, the labeled preset rule information is searched using a distributed search and analysis engine.

[0022] Preferably, the fault diagnosis method of the vehicle-mounted online service system, the distributed search and analysis engine is Elastic Search.

[0023] Preferably, the fault diagnosis method of the vehicle-mounted online service system, the result of the data optimization and performance analysis is output through a webpage.

[0024] The technical scheme provided by the embodiment of the application has the following advantages:

[0025] 1. The accuracy, timeliness and integrity of the log data collected in the test process can be ensured, and sufficient data support is provided for the diagnostic personnel;

[0026] 2. The performance test data can be directly processed, and the visual test result can be output, so that the analysis efficiency of the diagnostic personnel on the fault and performance test of the vehicle-mounted online service system is improved. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 The fault diagnosis method of the vehicle-mounted online service system is preferred for the embodiment of the application.

[0028] Figure 2 The architecture schematic diagram of the vehicle-mounted online service diagnosis system using the fault diagnosis method of the vehicle-mounted online service system preferred by the application is provided.

[0029] Figure 3 The timing schematic diagram of the vehicle-mounted online service diagnosis system using the fault diagnosis method of the vehicle-mounted online service system preferred by the application is provided. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical scheme and advantages of the application clearer, the technical scheme of the embodiment of the application will be described in more detail below in combination with the drawings of the embodiment of the application. In the drawings, the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions. The described embodiments are part of the embodiments of the application, not all embodiments. The embodiments described below by referring to the drawings are exemplary and are intended to explain the application, and cannot be understood as a limitation of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the application.

[0031] In addition, it needs to be explained that, unless otherwise explicitly specified and limited, the "installation", "connection", "connection" and similar words used in the description of the application should be understood broadly, for example, the connection can be fixed connection, or detachable connection, or integral connection; can be mechanical connection, or electrical connection; can be directly connected, or indirectly connected through intermediate medium, or the internal communication of two elements, and the person skilled in the art can understand the specific meaning of the application according to the specific circumstances.

[0032] The preferred technical solutions of the embodiments of the application will be described in detail below with reference to the drawings.

[0033] In order to solve the problems of complicated configuration process in fault diagnosis of the prior art vehicle online service system, low efficiency, high error rate and untimely feedback when evaluating the performance of the test object, Figure 1 The flow chart of the fault diagnosis method of the preferred vehicle online service system of the embodiments of the application is shown in Fig. Figure 1 The fault diagnosis method of the vehicle online service system comprises the following steps:

[0034] S1) detecting whether the vehicle communication port connection is normal, and if normal, acquiring vehicle log data;

[0035] S2) acquiring dot information data, the dot information data being acquired according to the signal of the dot device;

[0036] S3) performing data optimization and performance analysis on the dot information data and the vehicle log data;

[0037] S4) outputting the results of the data optimization and performance analysis, the result of the data optimization including fault log of the vehicle online service system, and the result of the performance analysis including response success rate and response time of the vehicle online service system.

[0038] In order to better understand the above technical solutions, the above technical solutions will be described in detail below with reference to the drawings and specific embodiments.

[0039] S1) detecting whether the vehicle communication port connection is normal, and if normal, acquiring vehicle log data;

[0040] Specifically, the vehicle communication port is connected with the vehicle to be tested through a hardware interface card, so as to acquire vehicle log data. The vehicle log data includes automobile special-purpose host controller log, domain controller log, vehicle information and CAN bus log.

[0041] S2) acquiring dot information data, the dot information data being acquired according to the signal of the dot device;

[0042] Specifically, the dotting information data can be realized by a dotting APP installed on a device, and the dotting device includes but is not limited to a mobile phone, a tablet, a computer, a smart device and the like.

[0043] S3) performing data optimization and performance analysis on the dotting information data and the vehicle log data;

[0044] Specifically, the data optimization further includes:

[0045] The dotting information data and the vehicle log data are stored in a timed rolling naming manner;

[0046] A log database is established, and the log database includes the vehicle log data and the dotting information data;

[0047] According to the dotting time point of the dotting information data, the log data conforming to the dotting time point is extracted.

[0048] Preferably, the log database can be established by SQL.

[0049] Specifically, the performance analysis further includes:

[0050] According to the dotting keyword in the dotting information data and the vehicle log data, preset rule information is extracted, and the preset rule information includes performance test related information of the vehicle-mounted online service system;

[0051] The preset rule information is labeled to obtain labeled preset rule information;

[0052] The labeled preset rule information is searched and the response success rate and the response time of the vehicle-mounted online service system are calculated.

[0053] Preferably, the preset rule information is extracted according to a regular expression.

[0054] Preferably, the preset rule information is labeled by using data mapping abstraction.

[0055] Preferably, the labeled preset rule information is searched by using a distributed search and analysis engine such as Elastic Search.

[0056] S4) outputting the results of the data optimization and the performance analysis, wherein the result of the data optimization includes fault logs of the vehicle-mounted online service system, and the result of the performance analysis includes the response success rate and the response time of the vehicle-mounted online service system.

[0057] The data optimization and performance analysis results are preferably output through a webpage, which can maintain and manage the automatic dotting rules on the dotting device and display the fault logs and performance analysis results of the vehicle-mounted online service system.

[0058] The application will be described in detail below with reference to the accompanying drawings.

[0059] Figure 2 The application will be described in detail below with reference to the accompanying drawings. Figure 2 The vehicle-mounted online service diagnosis system includes a dotting device 10, a cloud big data center 20, a computer terminal 30, a hardware interface card 40 and a test vehicle 50. In this embodiment, the hardware interface card is selected from VN 1640 or Value CAN to access the CAN bus of the test vehicle, VN 5640 to access the OCU (online communication unit), MediaConverter to access ICAS1 / Gateway (domain controller of the whole vehicle function application service) and Inverter to access ICAS3 / CNS3 (domain controller of the vehicle-mounted entertainment system).

[0060] Figure 3 The application will be described in detail below with reference to the accompanying drawings. Figure 2 Figure 3 The dotting device 10 is installed with a dotting APP, which is a mobile phone in this embodiment. The dotting APP applies for using and controlling the related modules such as the network, storage and camera of the smart phone through the permission declaration of the Android / iOS system. The computer terminal 30 is configured with the webpage and log grabbing software for testing the vehicle. When the APP is started, the test state of the log grabbing software is polled (once per second) by using the thread technology, and the dotting button is activated when the condition is met. The dotting function is completed by accessing the RESTful (Representational State Transfer) interface provided by the cloud big data center through the HTTP (Hyper Text Transfer Protocol) protocol. The multimedia files during the dotting are uploaded to the cloud big data center 20 through the FTP (File Transfer Protocol) protocol.

[0061] ​The log capture software installed on the computer 30 accesses the relevant RESTful interface provided by the cloud big data center 20 through the HTTP protocol to obtain the business data (including vehicle information acquisition, dotting information acquisition, etc.) in the background of the cloud big data center 20 and update the cloud data. When the test personnel starts log collection, the specified type of log data (OCU, CAN, ICAS1 / Gateway or ICAS3 / CNS3) is captured using multi-threading technology. In order to avoid the generated log file being too large, the log file is stored in a timed rolling naming manner. At the same time, in order to ensure the integrity of the log data, the software uses a SQLite lightweight database. Each test will generate a SQLite database, which saves the complete log data (including log content and log generation time) in rows. After the test personnel performs dotting on the dotting APP, the software will use the SQL (Structured Query Language) statement of the relational database to extract the log data that meets the dotting time point in the SQLite database, form a temporary text file, and upload the temporary file to the cloud big data center 20 using the FTP protocol.

[0062] The cloud big data center 20 receives the fault log information uploaded by the dotting APP, and the log capture software installed on the computer 30 will classify and upload the fault-related logs or the entire performance test-related logs to the cloud. The cloud big data center 20 uses multi-threading technology to read the uploaded log files, and uses regular expressions to analyze the dotting keywords in the logs. The vehicle basic information, dotting information, and corresponding dotting log-related information are stored in the MySql (relational database management system) data, and the RESTful interface communicates with the Mysql database through connection pool technology, and uses JPA (Java Persistence API) and MyBatis (Java-based persistence layer framework) framework to realize data mapping abstraction. The performance test-related log information is stored in the NoSql (non-relational database) database after being labeled, and then the Elastic Search (distributed search and analysis engine) framework is used to search the label, and the response success rate and response time of the performance test of the vehicle online service system are calculated.

[0063] The web page end can maintain and manage user information, vehicle information, website permissions, and automatic dotting rules. All related log files will finally be summarized on the web page end. In addition, the web page end can display the MOS fault log processed by the cloud big data center and the performance analysis result.

[0064] The following is based on Figure 3Further illustrate the specific use steps of the vehicle online service diagnosis system using the preferred fault diagnosis method of the vehicle online service system of the present application. As shown in Figure 3 The vehicle online service diagnosis system using the preferred fault diagnosis method of the vehicle online service system of the present application further comprises the following steps:

[0065] Step 01, the tester starts the software vehicle connection;

[0066] Vehicle connection step:

[0067] Step 02, vehicle connection step, the log capture software checks the communication port connection;

[0068] Step 03, the tester sends a capture command to the log capture software, and the test vehicle waits for the log capture operation;

[0069] OCU (online communication unit) log capture step:

[0070] Step 04, OCU log capture step, the log capture software starts the OCU log capture thread for the test vehicle;

[0071] Step 05, the test vehicle cyclically and in real time sends OCU log data;

[0072] Step 06, the log capture software cyclically and in real time saves the OCU log data cyclically and in real time sent by the test vehicle;

[0073] HU (host) log capture step:

[0074] Step 07, the log capture software starts the HU log capture thread for the test vehicle;

[0075] Step 08, the test vehicle cyclically and in real time sends HU log data;

[0076] Step 09, the log capture software cyclically and in real time saves the HU log data cyclically and in real time sent by the test vehicle;

[0077] ICAS (domain controller) log capture step:

[0078] Step 10, ICAS log capture step, the log capture software starts the ICAS log capture thread for the test vehicle;

[0079] Step 11, the test vehicle cyclically and in real time sends ICAS log data to the log capture software;

[0080] Step 12, the test software cyclically and in real time saves the ICAS log data cyclically and in real time sent by the test vehicle;

[0081] CAN (CAN bus) log capture step:

[0082] Step 13, the log capture software starts a CAN log capture thread for the test vehicle;

[0083] Step 14, the test vehicle cyclically sends CAN log data in real time to the log capture software;

[0084] Step 15, the log capture software cyclically saves the CAN log data cyclically sent by the test vehicle in real time;

[0085] Reading the dotting information step:

[0086] Step 16, the log capture software starts a reading dotting thread in the cloud background, and the test vehicle waits for dotting information;

[0087] Step 17, the tester clicks the dotting button through the dotting APP;

[0088] Step 18, the dotting APP saves the dotting time information and uploads it to the cloud background;

[0089] Step 19, the cloud background returns the dotting information to the log capture software;

[0090] Step 20, the log capture software saves the dotting log;

[0091] Uploading the dotting log step:

[0092] Step 21, the tester sends a stop log collection command to the log capture software;

[0093] Step 22, the log capture software closes the OCU log capture thread, the HU log capture thread, the ICAS log capture thread, the CAN log capture thread, and the dotting thread, and ends the cycle, and then the log capture software reads the dotting log;

[0094] Step 23, the log capture software extracts log data that meets the dotting time point according to the read dotting log and generates a log temporary file;

[0095] Step 24, the log capture software uploads the log file to the cloud background;

[0096] Log analysis and display step:

[0097] Step 25, the cloud background saves the log file;

[0098] Step 26, the cloud background analyzes the log file;

[0099] Step 27, the cloud background saves the analysis result;

[0100] Step 28, the tester checks the log analysis result through the web page;

[0101] Step 29, the webpage end queries the cloud end background for analysis data;

[0102] Step 30, the cloud end background returns the analysis data to the webpage end;

[0103] Step 31, the webpage end shows the log data and graphical analysis results to the test personnel.

[0104] In the system use, the test personnel starts the dotting APP on the dotting device 10, sets the log capture software on the computer end 30 to check the communication port connection with the test vehicle 50 and waits for the log capture operation. The operator sends the capture instruction through the log capture software, the log capture software starts the OCU log capture thread, the HU log capture thread, the CAS log capture thread and the CAN log capture thread respectively, the capture thread can receive and save the log data of the test vehicle 50 in real time. Then, the log capture software starts the reading dotting thread to the cloud end background of the cloud big data center 20. The test personnel starts the dotting button of the dotting APP, the dotting APP saves the dotting time information to the cloud end background of the cloud big data center 20, the cloud end background of the cloud big data center 20 returns the dotting information to the log capture software and saves it. The test personnel sends the stop log collection instruction to the log capture software, the test software reads the dotting information returned by the cloud end background of the cloud big data center 20 and generates the log temporary file, uploads the log file to the cloud end background of the cloud big data center 20, and the cloud end background of the cloud big data center 20 saves and analyzes the log file uploaded by the log capture software and exports the analysis results. The test personnel can query the analysis data results through the webpage end.

[0105] Those skilled in the art will appreciate that information, signals, and data can be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that can be referenced throughout the above description can be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0106] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans can implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

[0107] The various illustrative logical blocks, circuits, and circuits described in connection with the embodiments disclosed herein can be implemented or performed with a general purpose processor, 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 any combination thereof designed to perform the functions described herein. The general purpose processor can be a microprocessor, but in the alternative, the processor can be any conventional processor, controller, microcontroller, or state machine. A processor can also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

[0108] The steps of a method or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor. The processor and the storage medium can reside in an ASIC. The ASIC can reside in a user terminal. In the alternative, the processor and the storage medium can reside as discrete components in a user terminal.

[0109] In one or more exemplary embodiments, the functions described can be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions can be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media can be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0110] The above embodiments are provided to persons skilled in the art to implement or use the present application, and the persons skilled in the art can make various modifications or changes to the above embodiments without departing from the inventive idea of the present application, and thus the scope of protection of the present application should not be limited by the above embodiments, but should be the maximum scope of protection meeting the innovative features mentioned in the claims.

Claims

1. A fault diagnosis method for an in-vehicle online service system, comprising the following steps: S1) Check if the vehicle communication port connection is normal. If it is normal, obtain the vehicle log data. S2) Obtain dot information data, wherein the dot information data is obtained based on the signal from the dot device; S3) Perform data optimization and performance analysis on the point information data and the vehicle log data; S4) Output the results of the data optimization and performance analysis, wherein the data optimization results include the fault logs of the in-vehicle online service system, and the performance analysis results include the response success rate and response time of the in-vehicle online service system; in, The vehicle log data includes automotive host controller logs, domain controller logs, vehicle information, and CAN bus logs. The data optimization further includes: The vehicle log data and point information data are stored using a timed, rolling naming method; Establish a log database, which includes the vehicle log data and the point tracking information data; Extract the log data that matches the timing point of the timing information data; The performance analysis further includes: Based on the tracking information data and the tracking keywords in the vehicle log data, preset rule information is extracted, including performance test related information of the vehicle online service system. The preset rule information is tagged to obtain tagged preset rule information; Retrieve the tagged preset rule information and calculate the response success rate and response time of the vehicle online service system; The results of data optimization and performance analysis are output through a web interface. The web interface allows for the maintenance and management of automatic marking rules on the marking devices and can also display the fault logs and performance analysis results of the vehicle online service system. The process of acquiring vehicle log data involves using multi-threading technology to capture specified types of log data. The tracking device is a mobile phone. The tracking APP requests to use and control the network, storage, and camera modules of the smartphone through the permission declaration of the Android / iOS system. It accesses the RESTful interface provided by the cloud big data center through the HTTP protocol to complete the tracking function. It uploads multimedia files during tracking to the cloud big data center through the FTP protocol. The cloud big data center uses multi-threading technology to read the uploaded logs. The log database is an SQLite database, and a new SQLite database is generated for each test.

2. The fault diagnosis method for the vehicle-mounted online service system according to claim 1, characterized in that, Create a log database using SQL.

3. The fault diagnosis method for the vehicle-mounted online service system according to claim 1, characterized in that, The preset rule information is extracted based on regular expressions.

4. The fault diagnosis method for the vehicle-mounted online service system according to claim 1, characterized in that, The preset rule information is labeled using data mapping abstraction.

5. The fault diagnosis method for the vehicle-mounted online service system according to claim 1, characterized in that, The tagged preset rule information is retrieved using a distributed search and analysis engine.

6. The fault diagnosis method for the vehicle-mounted online service system according to claim 5, characterized in that, The distributed search and analytics engine is Elastic Search.

Images