Fault statistical data visualization method and system and electronic equipment

Abstract

The invention relates to the technical field of vehicle faults, and discloses a fault statistical data visualization method and system and electronic equipment, and the method comprises the steps: obtaining time series data generated by a target vehicle through presetting a fault statistical index and an index display type corresponding to the fault statistical index, the time sequence data comprises diagnosis fault codes arranged according to fault time, classifying the diagnosis fault codes according to the fault statistical indexes to obtain a classification result, performing data statistics on the fault time and the diagnosis fault codes according to the classification result to obtain to-be-displayed data after statistics, and displaying the to-be-displayed data according to the to-be-displayed data. Performing visual rendering on the to-be-displayed data according to the index display type to obtain visual data, and generating a fault statistical report according to the visual data; according to the method, the fault statistical data when the vehicle breaks down is visually displayed, a user can understand the data conveniently, and the user can be helped to rapidly position and solve problems.

Description

Technical Field

[0001] The present application relates to the field of vehicle failure technology, and in particular to a method, system and electronic device for visualizing failure statistics data. Background Art

[0002] A Diagnostic Trouble Code (DTC) is a unique alphanumeric code that identifies a specific type of problem with a vehicle's onboard computer system. Technicians use these codes to diagnose and repair the underlying problem that caused the malfunction. Each DTC corresponds to a specific component or system within the vehicle, such as the engine, transmission, or exhaust system. When a problem occurs, the onboard computer will store the associated DTC in its memory, which can be accessed using a scan tool or through the onboard diagnostic system. DTCs are generated by the vehicle's diagnostic system when a malfunction is detected, and each DTC represents a specific malfunction or problem. These problems can involve various vehicle systems, such as the engine, transmission, exhaust system, etc.

[0003] Currently, the main way to view DTCs is through the on-board diagnostics system (OBD-II) and professional automotive diagnostic tools (such as scan tools). The OBD-II system is usually used to monitor the performance of different components and generate corresponding DTCs when problems occur. The above methods require professional equipment, cumbersome operation steps, untimely data updates, unintuitive information display, inconvenient data management, and low security. Obviously, there is an urgent need for a new method for visualizing fault statistics data to solve at least one of the above problems.

[0004] It should be noted that the above content only provides background technical information related to the present application and does not necessarily constitute prior art. Summary of the invention

[0005] In view of the shortcomings of the prior art described above, the present application provides a method, system and electronic device for visualizing fault statistics data to intuitively display fault statistics data when a vehicle fails, which is easy for users to understand and can help users quickly locate and solve problems.

[0006] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0007] According to one aspect of an embodiment of the present application, a method for visualizing fault statistical data is provided, comprising: presetting fault statistical indicators and indicator display types corresponding to the fault statistical indicators, wherein the fault statistical indicators include the number of faults, severity, and frequency of occurrence; acquiring time series data generated by a target vehicle, wherein the time series data includes diagnostic fault codes arranged according to fault time; classifying the diagnostic fault codes according to the fault statistical indicators to obtain classification results, performing data statistics on the fault time and the diagnostic fault codes according to the classification results to obtain statistical data to be displayed; visually rendering the data to be displayed according to the indicator display type to obtain visualized data, and generating a fault statistical report based on the visualized data.

[0008] In one embodiment of the present application, based on the aforementioned scheme, after generating a fault statistics report according to the visualization data, the method also includes: pre-setting a data permission label corresponding to the fault statistics indicator; obtaining a target user and user permissions corresponding to the target user; determining target data from the fault statistics report according to a comparison result between the user permissions and the data permission label; and generating a target report according to the target data and the fault information corresponding to the diagnostic fault code.

[0009] In one embodiment of the present application, based on the aforementioned scheme, the method also includes: sending the target report to a user terminal corresponding to the target user, wherein the user terminal is provided with a visualization page, and the visualization page is used to display the target report, and / or, based on the preset operation authority of the target user, execute the page operation instructions input by the target user.

[0010] In one embodiment of the present application, based on the aforementioned scheme, the visualization page executes the page operation instructions input by the target user based on the preset operation permissions of the target user in at least one of the following ways: if the preset operation permissions include the first operation permissions, then at least one of the data viewing instructions, data editing instructions and data management instructions input by the target user is executed; if the preset operation permissions include the second operation permissions, then the data viewing instructions input by the target user are executed.

[0011] In one embodiment of the present application, based on the aforementioned scheme, the method also includes at least one of the following: generating a periodic task, wherein the periodic task is used to update a target report in each preset update cycle, and send the updated target report to a user terminal corresponding to the target user; monitoring the diagnostic fault code of the target vehicle by utilizing a preset service monitoring system, and if a new diagnostic fault code is detected, updating the target report, and sending the updated target report to the user terminal corresponding to the target user.

[0012] In one embodiment of the present application, based on the aforementioned scheme, the method also includes: obtaining historical fault codes, performing statistics on the historical fault codes, and determining the minimum support and minimum confidence based on the statistical results; extracting the initial item set corresponding to the diagnostic fault code from the historical fault codes through a preset association rule mining algorithm, extracting the frequent item set corresponding to the diagnostic fault code from the initial item set based on the minimum support, and extracting association rules from the frequent item set; screening from the association rules based on the minimum confidence to obtain association results; determining the associated fault code of the diagnostic fault code based on the association result, and displaying the associated fault code through a visualization page.

[0013] According to one aspect of an embodiment of the present application, a fault statistics data visualization system is provided, including: a target vehicle, used to generate time series data, wherein the time series data includes diagnostic fault codes arranged according to fault time; a server side, used to set fault statistical indicators and indicator display types corresponding to the fault statistical indicators, wherein the fault statistical indicators include the number of faults, severity, and frequency of occurrence, obtain the time series data generated by the target vehicle, classify the diagnostic fault codes according to the fault statistical indicators to obtain a classification result, perform data statistics on the fault time and the diagnostic fault code according to the classification result to obtain statistical data to be displayed, visualize the data to be displayed according to the indicator display type to obtain visualized data, and generate a fault statistics report based on the visualized data.

[0014] In one embodiment of the present application, based on the aforementioned scheme, the target vehicle includes a vehicle gateway and at least one electronic controller; the electronic controller is used to generate the diagnostic fault code; the vehicle gateway is connected to each of the electronic controllers, and the vehicle gateway is used to collect the diagnostic fault code of each of the electronic controllers, obtain the fault time, generate the time series data according to the fault time and the diagnostic fault code, and send the time series data to the server.

[0015] In one embodiment of the present application, based on the aforementioned scheme, the server side includes at least one of the following: a time series database, used to store the time series data sent by the vehicle gateway; a visualization module, used to visualize the data to be displayed according to the indicator display type to obtain visualization data, generate a fault statistics report based on the visualization data, and display the fault statistics report; a service monitoring system, used to monitor the diagnostic fault code, and if it is monitored that the target vehicle generates a new diagnostic fault code, send the fault statistics report to the user terminal corresponding to the target user.

[0016] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device implements a fault statistics data visualization method as described in any one of the above embodiments.

[0017] Beneficial effects of the present application: The present application obtains time series data generated by a target vehicle by pre-setting fault statistical indicators and indicator display types corresponding to the fault statistical indicators, wherein the time series data includes diagnostic fault codes arranged according to fault time, classifies the diagnostic fault codes according to the fault statistical indicators, obtains classification results, performs data statistics on the fault time and the diagnostic fault codes according to the classification results, obtains statistically analyzed data to be displayed, visualizes the data to be displayed according to the indicator display type, obtains visualized data, and generates a fault statistical report based on the visualized data; statistics of fault information are realized through diagnostic fault codes, and fault information is displayed intuitively and concisely, which facilitates users to quickly view and analyze fault data, reduces the time for manual interpretation of diagnostic fault codes, and improves fault handling efficiency.

[0018] In addition, this application also accesses the visualization page through a preset network address link to view fault statistics reports without the need for professional diagnostic equipment, wiring harnesses, and professional diagnostic engineers, and is not restricted by location restrictions; by setting different permissions for different personnel, data security is improved.

[0019] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0021] Figure 1 is a schematic diagram of an exemplary system architecture shown in an exemplary embodiment of the present application;

[0022] Figure 2 is a flowchart of a method for visualizing fault statistical data according to an exemplary embodiment of the present application;

[0023] Figure 3 is a schematic diagram of the system architecture of a method for visualizing fault statistical data shown in an exemplary embodiment of the present application;

[0024] Figure 4 is a schematic diagram of a system architecture of a method for visualizing fault statistical data shown in another exemplary embodiment of the present application;

[0025] Figure 5 is a data transmission schematic diagram of a fault statistics data visualization method shown in an exemplary embodiment of the present application;

[0026] Figure 6 is a block diagram of a fault statistics data visualization system shown in an exemplary embodiment of the present application;

[0027] Figure 7 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0028] The following will describe the implementation methods of the present application with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific implementation methods, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for illustrating the present application, not for limiting the scope of protection of the present application.

[0029] It should be noted that the illustrations provided in the following embodiments are only used to illustrate the basic concept of the present application in a schematic manner, and therefore the illustrations only show components related to the present application rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0030] In the following description, a large number of details are discussed to provide a more thorough explanation of the embodiments of the present application. However, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present application difficult to understand.

[0031] First of all, it should be explained that the electronic control unit (ECU) is an important electronic product component, which is widely used in electronic production and plays a very important role in people's daily life. The electronic control unit (ECU) is a miniature computer management center. It takes signal (data) acquisition, calculation processing, analysis and judgment, and decision-making as input, and then issues control instructions and directs the actuator to work as output. It also provides stable power supply or reference voltage to the sensor. All its functions are completed through the sum of various hardware and software, and its core is a microcomputer system with a single-chip microcomputer as the main body.

[0032] Grafana is an open source monitoring dashboard and graphics editor that is widely used to visualize time series data. Grafana is a powerful data visualization tool that supports the integration of multiple data sources (such as Elasticsearch, InfluxDB, Prometheus, etc.) and can transform complex data into easy-to-understand charts and dashboards. With Grafana, users can monitor system status, performance and other indicators in real time, and conduct in-depth analysis and insights into the data.

[0033] InfluxDB is an open source database designed for time series data. Time series data is a collection of data points that are continuously generated over time, such as monitoring data (CPU usage, memory usage), IoT device sensor data, stock market data, etc. InfluxDB provides the ability to efficiently store, query, and analyze this data.

[0034] Prometheus is an open source monitoring and alarm system based on a time series database. It periodically captures the status of monitored components through the HTTP protocol, supports clients in multiple languages ​​and rich visualization modes, such as Grafana integration, and can efficiently process large amounts of monitoring data and provide accurate alarm functions. Prometheus has independent and active community support and is suitable for monitoring virtualized environments, Docker containers, and Kubernetes clusters. With its multidimensional data model, PromQL query language, efficient storage, and accurate alarms, it excels in the field of performance monitoring and alarming. Simply put, Prometheus is an open source system monitoring and alarm tool that helps users monitor the health of applications and infrastructure in real time, and promptly discover and respond to potential problems by collecting time series data and providing query and visualization interfaces.

[0035] A Diagnostic Trouble Code (DTC) is a unique alphanumeric code that identifies a specific type of problem with a vehicle's onboard computer system and is used to diagnose and repair the underlying problem that caused the malfunction. DTCs are generated by the vehicle's diagnostic system when a malfunction is detected, and each DTC represents a specific malfunction or problem. These problems can involve various vehicle systems, such as the engine, transmission, exhaust system, etc.

[0036] Currently, the main way to view DTC is through the on-board diagnostic system (OBD-II) and professional automotive diagnostic tools (such as scan tools). The disadvantages include: 1. Faults cannot be discovered in time during testing. Traditional diagnostic tools often do not have real-time data update functions, which means that the information seen by technicians may not be the latest vehicle status. 2. When a test failure occurs, relevant key data is not captured, such as CPU utilization, network load, CAN bus load, CAN frame loss rate, CAN forwarding delay, interface success rate, probability of occurrence of different abnormal return values ​​of the interface, abnormal input parameters, etc. 3. Professional equipment is required and the operation steps are cumbersome. Using OBD-II and scan tools to view DTC must rely on professional automotive diagnostic equipment. These devices are usually expensive and inconvenient to carry, which may not be practical for ordinary car owners or small repair shops. Compared with the visual interface, the steps to obtain DTC through OBD-II and scan tools are more complicated. Technicians need to connect the equipment, select the correct operation mode and interpret the output results, which requires technicians to have certain professional knowledge and experience. In addition, if they want to be proficient in using OBD-II and scan tools, technicians need to receive professional training to learn how to operate the equipment and interpret DTC codes, which increases the learning cost and time. 4. The information display is not intuitive and lacks a graphical interface. Unlike intuitive graphics and charts, DTCs read by professional tools are usually displayed in the form of digital codes and text. This display method is not intuitive enough, especially for non-professionals, and it is difficult to understand. 5. It is difficult to identify problems quickly. In an emergency, it is crucial to quickly locate and solve the problem. Because OBD-II and scan tools provide raw data, technicians need to spend more time analyzing and determining the cause of the fault. In contrast, visual displays can quickly highlight key issues and help users take immediate action. 6. Inconvenient data management due to difficulties in data archiving management. DTC data obtained through professional tools usually need to be recorded and managed manually, which not only increases the workload but is also prone to errors. If the DTC data needs to be organized into a report, the use of traditional tools requires manual writing and formatting, which is inefficient and error-prone. 7. Low security. Traditional diagnostic tools lack effective encryption and protection measures during data transmission and storage, which may lead to data security risks such as DTC data leakage or malicious tampering. For large maintenance organizations or fleet management, technicians at different levels have different access rights to DTC data. It is difficult for traditional tools to achieve fine permission control, resulting in insufficient permission control. 8. Poor mobility and inconvenient for use outside. Traditional diagnostic tools are usually bulky and inconvenient to use when going out or on-site maintenance. 9. No timely feedback. Far away from the maintenance station or in an environment without a network, traditional tools find it difficult to transmit data in real time to the background or expert team for emergency diagnosis and support.

[0037] Figure 1It is a schematic diagram of an exemplary system architecture shown in an exemplary embodiment of the present application.

[0038] Reference Figure 1 As shown, the system architecture may include a data acquisition device 101 and a computer device 102. The computer device 102 may be at least one of a desktop graphics processing unit (GPU) computer, a GPU computing cluster, a neural network computer, etc. The data acquisition device 101 is used to collect time series data generated by the target vehicle, wherein the time series data includes diagnostic fault codes arranged according to the fault time. In this embodiment, the data acquisition device 101 obtains the above data and provides it to the computer device 102 for processing. Relevant technicians can use the computer device 102 to pre-set fault statistical indicators and indicator display types corresponding to the fault statistical indicators, wherein the fault statistical indicators include the number of faults, severity, and frequency of occurrence, classify the diagnostic fault codes according to the fault statistical indicators, obtain the classification results, perform data statistics on the fault time and the diagnostic fault code according to the classification results, obtain the statistical data to be displayed, perform visual rendering on the data to be displayed according to the indicator display type, obtain visual data, and generate a fault statistical report based on the visual data. It should be noted that the data acquisition device 101 and the computer device 102 provided in this embodiment are only an example and should not bring any restrictions to the functions and scope of use of the embodiments of the present application.

[0039] It should be noted that the fault statistics data visualization method provided in the embodiment of the present application is generally executed by the computer device 102 , and accordingly, the fault statistics data visualization system is generally set in the computer device 102 .

[0040] Figure 2 is a flow chart of a method for visualizing fault statistics data according to an exemplary embodiment of the present application. The method for visualizing fault statistics data may be executed by a computing and processing device. The computing and processing device may be Figure 1 The computer device 102 shown in FIG. Figure 2 As shown, the fault statistics data visualization method at least includes steps S210 to S240, which are described in detail as follows:

[0041] In step S210, fault statistical indicators and indicator display types corresponding to the fault statistical indicators are preset.

[0042] In one embodiment of the present application, the fault statistical indicators and the indicator display types corresponding to the fault statistical indicators are set according to the needs. For example, the fault statistical duration is the length of time for statistical faults (such as one day, one week, one month, etc.), the statistical indicators (number of faults, severity, frequency of occurrence, etc.), the statistical content, etc. The indicator display type corresponding to the fault statistical indicator can be set according to the relevant information of the fault statistical indicator (such as the data type), and the corresponding fault statistical indicator can also be determined according to the characteristics of the indicator display type and the data applicable for display. Among them, the fault statistical indicators include the number of faults, severity, and frequency of occurrence.

[0043] In this embodiment, various types of charts can be displayed through Grafana's data visualization interface. The indicator display types include but are not limited to one or more of indicator cards, dashboards, pie charts, doughnut charts, stacked bar charts, percentage stacked bar charts, bar charts, line charts, area charts, histograms, scatter plots, etc., to meet the needs of different data displays. The specific introduction is as follows: indicator card, used to highlight a single important data point, such as system status or key performance indicators; dashboard, which displays data in the form of an arc pointer, suitable for showing the proportion of a metric relative to the maximum value; pie chart, which uses the size of different sectors to show the proportion of each part of the total, suitable for showing the distribution of classified data; doughnut chart, similar to pie chart, but empty in the middle, saves space and has aesthetic appeal, also used to show percentage data; stacked bar chart, multiple bar charts overlap, each bar represents a category, the length represents the size of the value, used to compare data in multiple dimensions; percentage stacked bar A bar chart is similar to a stacked bar chart, but the length of each part represents the percentage of the total bar length; a bar chart uses the length of the bar to represent the size of the data, which is suitable for comparing data of different categories; a line chart uses lines to connect each data point to show the trend of data changes over time, which is suitable for time series data; an area chart uses the area below the line chart to be filled with color, which can more intuitively show the cumulative effect of the data; a histogram uses height to represent frequency, which is suitable for showing the distribution of data; a scatter plot uses points to represent data, and the horizontal and vertical coordinates are two numerical variables, which is suitable for viewing the relationship between two variables. In general, through these chart types and rich configuration options, Grafana can flexibly display data from various data sources, thereby helping engineers better monitor and analyze the status and performance of environments such as ECU systems, networks, and databases.

[0044] In step S220, time series data generated by the target vehicle is obtained.

[0045] The time series data includes diagnostic fault codes arranged according to fault time.

[0046] In one embodiment of the present application, time series data sent by the target vehicle is received, wherein the diagnostic trouble code is generated by the trouble time and the diagnostic trouble code. Time series data refers to a set of data arranged at a certain time interval, which is used to describe the measurement value of a measured subject at each time point within a time range. These data can reflect the state or degree of change of a thing or phenomenon over time, such as the number of occurrences, frequency, vehicle speed when a certain DTC occurs, and other snapshot information.

[0047] In step S230, the diagnostic fault codes are classified according to the fault statistical indicators to obtain classification results, and the fault time and the diagnostic fault code are statistically analyzed according to the classification results to obtain statistical data to be displayed.

[0048] In one embodiment of the present application, the diagnostic fault codes are classified according to the preset classification standard corresponding to the fault statistical index to obtain the classification result. The diagnostic fault codes are screened according to the preset time length to obtain the screened diagnostic fault codes, and the screened diagnostic fault codes are statistically analyzed according to the classification result to obtain the statistically displayed data. For example, the preset time length is 1 month, and within this 1 month, six faults with diagnostic fault codes AABACB occurred, and the fault times were January 1, January 6, January 10, January 18, January 23, and January 27, respectively. The diagnostic fault code A corresponds to a general fault, the diagnostic fault code B corresponds to a minor fault, and the diagnostic fault code C corresponds to a serious fault. Taking the fault statistical indicator as the number of faults as an example, the diagnostic fault codes are classified according to the first preset classification standard of the number of faults to obtain the classification results (such as each diagnostic fault code), and the fault time and the diagnostic fault code are statistically analyzed according to the classification results to obtain the number of faults after each classification result is statistically analyzed (A: 3, B: 2, C: 1, unit: pieces). If the total number of faults needs to be counted, the number of faults after each classification result is summed to obtain the total number of faults (the number of faults is 6). Taking the fault statistical indicator as severity as an example, the diagnostic fault codes are classified according to the second preset classification standard of severity to obtain the classification results (such as general faults, minor faults, and serious faults), and the fault time and the diagnostic fault code are statistically analyzed according to the classification results to obtain the number of faults after each classification result is statistically analyzed (serious faults: 1, general faults: 2, minor faults: 3, unit: pieces). Taking the fault statistical indicator as the occurrence frequency as an example, the diagnostic fault code is classified according to the third preset classification standard of the occurrence frequency to obtain a classification result (such as time granularity, such as month, week, day, etc.), and the fault time and the diagnostic fault code are statistically analyzed according to the classification result to obtain the number of faults after the classification result statistics (taking the classification result of 1 week as an example, the occurrence frequency is 1.5 times a week). It should be noted that this embodiment is only for illustration and should not bring any limitation to the function and scope of use of the embodiment of the present application.

[0049] In this embodiment, the data to be displayed includes but is not limited to data corresponding to the number of faults, data corresponding to the severity, data corresponding to the frequency of occurrence, and the like. For example, the fault time and the diagnostic fault code can be statistically analyzed according to the fault statistical duration corresponding to the fault statistical index to obtain the data to be displayed. For example, by counting the fault information within one month, the data to be displayed is that the number of faults is 6, the severity is 1 serious fault, 2 general faults, 3 minor faults, and the frequency of occurrence is 1.5 times a week. It should be noted that this embodiment is for illustrative purposes only and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0050] In step S240, the data to be displayed is visualized and rendered according to the indicator display type to obtain visualized data, and a fault statistics report is generated according to the visualized data.

[0051] In one embodiment of the present application, taking the severity of a fault as an example, assuming that the indicator display type corresponding to the severity is a histogram, the severity in the data to be displayed is visualized according to the histogram to obtain visualization data of the severity. A fault statistical report is generated based on the visualization data, still taking the severity as an example, the severity in the fault statistical report is: severe fault: 1, general fault: 2, minor fault: 3, unit: individual.

[0052] In one embodiment of the present application, after generating a fault statistics report based on visualization data, data permission labels corresponding to fault statistics indicators are pre-set; a target user and user permissions corresponding to the target user are obtained; target data is determined from the fault statistics report based on a comparison result between user permissions and data permission labels; and a target report is generated based on the target data and the fault information corresponding to the diagnostic fault code.

[0053] In this embodiment, taking the severity of the fault as an example, assuming that the user authority of the target user includes viewing the severity, the target data determined from the fault statistics report includes serious faults: 1, general faults: 2, minor faults: 3, assuming that the corresponding diagnostic fault codes are P0300, P0107, P0115, P0111, P0112, P3009, then the fault information corresponding to the diagnostic fault codes are: P0300: throttle position sensor / switch circuit low, P0107: intake pressure sensor input voltage is too low, P0115: engine water temperature sensor circuit is poor, P0111: intake temperature sensor wiring is poor, P0112: intake temperature sensor circuit voltage is too low, P3009: brake pedal position sensor A circuit range / performance. The schematic target report is: serious fault: 1, P0300: throttle position sensor / switch circuit low; general fault: 2, P0107: intake pressure sensor input voltage is too low, P0115: engine water temperature sensor circuit is bad; minor fault: 3, P0111: intake temperature sensor wiring is bad, P0112: intake temperature sensor circuit voltage is too low, P3009: brake pedal position sensor A circuit range / performance. It should be noted that the fault information corresponding to the target data and diagnostic fault code in this embodiment is only for example, and should not bring any limitation to the function and scope of use of the embodiment of this application.

[0054] In one embodiment of the present application, a target report is sent to a user terminal corresponding to a target user, wherein the user terminal is provided with a visualization page, which is used to display the target report and / or to execute page operation instructions input by the target user based on the preset operation authority of the target user.

[0055] In this embodiment, the role of the visualization page is determined according to the user authority. If the user authority includes the first role authority, the visualization page of the user terminal corresponding to the target user is used to display the target report, and the page operation instruction input by the target user is executed based on the preset operation authority of the target user; if the user authority includes the second role authority, the visualization page of the user terminal corresponding to the target user is used to display the target report. It should be noted that the user authority is specifically set according to actual needs, and this application does not limit this.

[0056] In one embodiment of the present application, a periodic task is generated, wherein the periodic task is used to update a target report in each preset update cycle and send the updated target report to a user terminal corresponding to a target user; the diagnostic trouble code of the target vehicle is monitored by utilizing a preset service monitoring system, and if a new diagnostic trouble code is detected, the target report is updated and the updated target report is sent to a user terminal corresponding to the target user.

[0057] In this embodiment, preferably, taking the service monitoring system as Prometheus as an example, if Prometheus detects a new diagnostic fault code, the target report is updated, and the updated target report is sent to the user terminal corresponding to the target user; if Prometheus does not detect a new diagnostic fault code, the target report is updated in each preset update cycle, and the updated target report is sent to the user terminal corresponding to the target user.

[0058] In one embodiment of the present application, the visualization page executes the page operation instructions input by the target user based on the preset operation permissions of the target user in at least one of the following ways: if the preset operation permissions include the first operation permissions, then at least one of the data viewing instructions, data editing instructions and data management instructions input by the target user is executed; if the preset operation permissions include the second operation permissions, then the data viewing instructions input by the target user are executed.

[0059] In one embodiment of the present application, a visualization page is accessed through a preset network address link, so that the target user can view the target report through the visualization page.

[0060] In this embodiment, before a user accesses the visualization page through a preset network address link, he needs to log in to verify the user's identity and confirm that the user is the target user to avoid insecurity caused by data leakage. By managing the account authority of the URL (network address link) of the visualization page, different authorities are distributed to different people, thereby improving the security of DTC data.

[0061] In one embodiment of the present application, historical fault codes are obtained, statistics are taken on the historical fault codes, and the minimum support and minimum confidence are determined based on the statistical results; an initial item set corresponding to the diagnostic fault code is extracted from the historical fault codes through a preset association rule mining algorithm, a frequent item set corresponding to the diagnostic fault code is extracted from the initial item set based on the minimum support, and association rules are extracted from the frequent item set; the association rules are screened based on the minimum confidence to obtain association results; the associated fault code of the diagnostic fault code is determined based on the association result, and the associated fault code is displayed through a visualization page.

[0062] In this embodiment, historical fault diagnosis codes, i.e., historical fault codes, from multiple vehicles, different time periods, and different fault types are collected to ensure that the collected data covers a comprehensive coverage and contains sufficient sample size to support subsequent association rule mining. After obtaining the historical fault codes, the historical fault codes are preprocessed, and the preprocessing includes but is not limited to deduplication (removing duplicate data records), processing missing values ​​(which can be processed by deleting missing values, replacing missing values, or using interpolation methods), processing outliers (checking whether there are outliers in the data set, if there are outliers, deleting, replacing, or using interpolation methods to process), data standardization (standardizing the fault diagnosis codes to ensure that fault diagnosis codes from different sources and formats can be mined for association rules on the same platform), and data conversion (converting the fault diagnosis codes into transaction data set format, each transaction contains a series of fault diagnosis codes that appear at the same time). By preprocessing the historical fault codes, the data quality of the historical fault codes can be improved, thereby facilitating the efficiency of subsequent data analysis and improving the speed of rule analysis. Statistics are performed on the historical fault codes to determine the minimum support and minimum confidence based on the statistical results, so as to subsequently screen frequent item sets and association rules. Through the preset association rule mining algorithm (such as Apriori algorithm or FP-Growth algorithm), the set of all possible items (i.e., fault codes) is extracted from the historical fault codes to form an initial item set. Based on the minimum support, the frequent item sets are filtered out from the initial item set. These frequent item sets represent the combinations of fault codes that often appear together in the historical data. Association rules are further extracted from the frequent item sets. These rules describe the correlation between the fault codes. The extracted association rules are filtered based on the minimum confidence to retain those rules with high confidence and strong reliability. According to the filtered association results, the associated fault codes associated with each diagnostic fault code are determined. These associated fault codes have a high co-occurrence rate in statistics and may be of great significance for fault diagnosis and prediction. Finally, the associated fault codes are displayed through a visual page, which helps users intuitively understand the complex relationship between the fault codes, and then formulate targeted maintenance strategies based on the associated fault codes to improve maintenance efficiency and accuracy, and use the associated fault codes for fault warning to discover and solve potential problems in advance.

[0063] In one embodiment of the present application, corresponding processing suggestions are provided to the user through the fault information corresponding to the diagnostic fault code. For example, P0115: Engine coolant temperature sensor circuit, its corresponding processing suggestions are: 1. Replace the sensor: If the sensor itself fails, it is recommended to replace a new engine coolant temperature sensor. 2. Check the circuit: Check whether the sensor circuit has problems such as open circuit, short circuit or poor contact, and at the same time, check whether the engine circuit is damaged or short-circuited. 3. Consider the control unit: Replace the engine control unit (ECU).

[0064] In one embodiment of the present application, a fault statistics visualization system is proposed to realize the functions of real-time visualization display of DTC reported by each ECU in vehicle diagnosis problems, key data indicator monitoring, alarm, automatic generation of fault reports, etc. In the vehicle, most of the data communication between ECUs is carried out through the CAN protocol, and the vehicle gateway controller (gateway, hereinafter referred to as GW) is the bridge for these ECUs to communicate. These ECUs are connected to the GW through the CAN bus, which is called the lower pendant of the GW, and the DTCs of these ECUs can be sent to the GW. Therefore, in order to upload all the DTC data on the vehicle, the DTC data can be sent to the gateway through the CAN bus first, and then the GW with an Ethernet interface will upload the data through Ethernet. The functions of uploading the DTC data of all ECUs in the vehicle to the server, visualizing the DTC data, monitoring and alarming, and automatically generating fault reports are solved.

[0065] The fault statistics visualization system in this embodiment has the following functions: 1. Establish a time series database based on InfluxDB to save DTC information in the form of time series data, and save the DTC of all ECUs on the vehicle through the dot interface deployed on the GW. 2. Configure a data visualization interface based on Grafana. After the engineer configures the data of interest, it can be displayed to anyone who accesses the page in a graphical way, and different permissions can be opened to different personnel. 3. Configure a monitoring alarm system (service monitoring system) based on the Alertmanager function in Prometheus. It can be configured to promptly notify engineers, emergency handling personnel, etc. through office software group chat (such as DingTalk, Feishu), email, mobile phone text messages and phone calls when the vehicle has different degrees of fault DCT. That is, the prompt method is determined according to the severity of the fault. Specifically, the target prompt method is determined from the preset prompt methods according to the matching result of the severity of the diagnostic fault code and the preset severity, and the target user is prompted in the target prompt method, wherein the preset prompt method includes but is not limited to one or more of text prompts, voice prompts, etc. Text prompts include but are not limited to prompts through office software group chats, emails, mobile phone text messages, etc. Voice prompts include but are not limited to prompts through alarm sounds, calling the target user, playing prompt voice, etc. 4. Design a tool for automatic generation of fault reports. According to the preset content and statistics of the faults that occur in the vehicle for a period of time (preset time period), an online fault report, i.e., a fault statistics report, is automatically generated, which includes one or more of the contents such as the number of faults, severity, and frequency of occurrence, so as to realize a concise display of the fault occurrence on the web page, and can regularly send fault reports to the user terminal corresponding to the target user, such as the user's mobile phone.

[0066] Figure 3FIG. 1 is a schematic diagram of a system architecture of a method for visualizing fault statistics data, shown in an exemplary embodiment of the present application. Figure 3 As shown, in an exemplary embodiment, the diagnostic trouble code visualization system is intended to provide a real-time, intuitive data display platform for vehicle fault status. By establishing an influxdb time series database on the server and using Grafana to connect to Prometheus as a visualization tool, the monitoring alarm function is configured in the Prometheus-Alertmanager function. The system can effectively collect, store and display DTC data reported during vehicle use, helping developers, testers, users, maintenance personnel, and emergency response personnel to quickly understand fault information and respond in a timely manner. The fault statistics data visualization system includes a data collection layer, a data storage layer, a data visualization layer, a network communication layer, and a security and permission management layer. Reference Figure 4 , Figure 4 FIG. 1 is a schematic diagram of a system architecture of a method for visualizing fault statistics data shown in another exemplary embodiment of the present application. The following is a brief description of each layer:

[0067] 1. Data collection layer, responsible for collecting DTC data from the CAN bus and sending this data to the influxdb database on the server side through the GW. Its key components include: the data collection agent is an agent software installed on the GW, responsible for monitoring the CAN bus message and capturing the DTC data when the DTC data changes; the dot api, an api provided to the data collection agent in the GW, used to send the captured data to the server in a specific format; ECU, each ECU obtains DTC data, and saves the DCT data to be uploaded by each ECU (ECU1 to ECUn) under the GW in a preset format through the CAN bus. When these ECUs send DTC data to the GW and change, the DCT data of the message is parsed according to the communication protocol and the dot api of the influxdb database is called to complete the dot saving of the DTC data of the ECU under the GW. Among them, the dot API, also known as the tracking API or logging API, is a technical interface used in the software system to collect and record user behavior, system status, performance data or other important information. These APIs are usually integrated into applications to automatically record key events or data points when the application is running, and then send these data to the backend service for storage, analysis or display.

[0068] 2. Data storage layer, responsible for receiving DCT data from ECU and storing it in influxdb time series database. Its key components include: influxdb database: a high-performance time series database for storing data points from GW; data receiving service: a service running on the server, responsible for receiving data points sent by ECU and writing them into influxdb.

[0069] 3. Network communication layer, to ensure that data transmission between GW and the server is secure and reliable. Its key components include: Ethernet communication hardware and software: an ECU (Electronic Control Unit) that supports Ethernet communication should have Ethernet MAC (Media Access Control) and PHY (Physical Layer) chips, MII / RMII / GMII / RGMII interfaces, necessary software protocol stacks, and related network testing and security mechanisms; Setting up the network environment: ensuring that the environment in which the FreeRTOS operating system on the ECU runs has been configured with a network protocol stack, such as lwIP, which supports TCP / IP protocols, including HTTP protocols; Ethernet connection: GW is connected to the server via Ethernet to ensure stable network communication. Connection methods include: ordinary Ethernet gateway: connected to the Internet via T-BOX (Telematics BOX); central gateway: its own 4G / 5G communication function. Data transmission protocol: defines the communication protocol between GW and the server, using the HTTP protocol. For specific connection methods, please refer to Figure 5 , Figure 5 FIG. 1 is a data transmission diagram of a method for visualizing fault statistics data, shown in an exemplary embodiment of the present application. Figure 5 It can be seen that GW is connected to the InfluxDB server via Ethernet.

[0070] 4. Data visualization layer, including visualization panel, which is used to provide user interface and allow users to configure and view the visualization of data. Its key components include: Prometheus: an open source monitoring and alarm tool for querying and displaying data from influxdb; Grafana visualization panel: use Grafana to connect to Prometheus. Configure the grafana dashboard to display key indicators such as interface success rate. It also includes a fault report automatic generation tool, which is used to automatically generate online fault reports based on the set content and statistics of vehicle faults over a period of time, including the number, severity, frequency of occurrence, etc., to achieve a streamlined display of fault occurrence on the web page, and can regularly send fault reports to the user terminal corresponding to the target user, such as the user's mobile phone. Its key steps include: fault report layout design: design an HTML template suitable for displaying vehicle DTC fault data; back-end development: use Python's web framework such as Flask to build back-end services and obtain the Flask framework. The framework implements functions such as routing, time series database connection and report sending API to achieve report generation and sending functions. Report generation code: Write Python code to classify the severity of DTC data, count its number and occurrence comments based on the collected DTC data, and dynamically fill in the designed report template to generate a report. Report push: Write code to send fault reports to users regularly (for example, monthly) and count the fault occurrence information within the monthly statistical period. Tool deployment: Deploy the fault report automatic generation tool to the server and connect to the time series database to start collecting and counting DTC data.

[0071] 5. Security and permission management layer, used to protect the security of the system and prevent unauthorized access. The key includes: Authentication mechanism: ensure that only authenticated users can access the system's visualization interface URL. Authorization strategy: define the permissions of different users, such as viewing, editing or managing the DTC data visualization panel. For example, development engineers have the permission to view, edit or manage the DTC data visualization panel; test engineers have the permission to view the DTC data visualization panel; maintenance personnel have the permission to view the DTC data visualization panel, and car companies can provide DTC data visualization panel accounts to regular 4S stores and repair shops; emergency response personnel have the permission to view the DTC data visualization panel, and car companies can provide DTC data visualization panel accounts to professionals, as well as configure automatic direct alarms and reports to car company customer service when specific fault DTCs (such as braking, power abnormalities, etc.) occur. Users have the permission to view the DTC data visualization panel and have editing permissions for some data information.

[0072] In one embodiment of the present application, the steps for building a fault statistics visualization system are described as follows: install and configure the influxdb database on a preset server; install Prometheus and configure the connection to influxdb; develop the influxdb database dotting API on the server; configure the network environment to ensure that GW can communicate with the server through Ethernet; develop or integrate a data acquisition agent on the GW, and implement the influxdb dotting API code integration and compilation; ensure that the vehicle's key ECUs can send DTC data to the GW via the CAN bus; after the gateway receives the DTC information of the ECU carrying the lower pendant, it parses the dotting data of the message according to the communication protocol and calls the dotting API of the influxdb database to complete the dotting and saving of the DTC data of the lower pendant ECU; connect Prometheus on Grafana, create a visualization panel, configure the data indicators of interest, namely the fault statistics indicators; implement security measures, including user authentication and authorization. Users are divided into administrators and ordinary users, namely the first role authority and the second role authority. Administrators can view and configure the data indicators of interest at any time, and users can view these indicators at any time. Open the URL of the Grafana data visualization panel to facilitate all development engineers, test engineers, users, maintenance personnel, emergency response personnel and other users to observe the real-time DTC data of the vehicle; configure the real-time alarm system and configure the timely alarm service through Alertmanager in Prometheus. Configure the data indicator danger level classification. When the monitored DTC data has preset specific anomalies (such as braking, power, and vehicle collision status), select different ways to notify engineers, car company customer service personnel, and related staff and other professionals through office software group chats (such as DingTalk, Feishu), emails, mobile phone text messages, and phone calls based on these danger levels; deploy the fault report automatic generation tool to the server; conduct system testing to ensure the accuracy of data and the correctness of visualization.

[0073] In one embodiment of the present application, the visualization of fault statistics data also needs to be maintained and upgraded. Specifically, it includes but is not limited to the following: regularly check system performance, optimize database and query efficiency; update data collection points and visualization panels, i.e., visualization pages, according to test requirements; open Grafana data visualization panel URL to account application, so that all practitioners (such as 4S stores, repair shops) can obtain accounts to view the company's vehicle DTC visualization panel through formal channels.

[0074] This application realizes the complete process of DTC data collection, storage and visualization from most of the vehicle's lower-mounted ECUs to the server, which not only improves the accessibility and comprehensibility of the vehicle's DTC data, but also greatly improves the efficiency and quality of vehicle fault discovery, location analysis, and response processing through real-time monitoring and analysis. With the continuous operation and maintenance of the system, it will become a powerful tool to help relevant personnel better locate and handle vehicle faults.

[0075] The present application has the following advantages: through the visualization interface display, DTC data can be intuitively displayed, without the need to interpret the information saved by DTC according to the protocol, and DTC data can be quickly viewed and analyzed, thereby reducing the time for manual interpretation of DTC information and improving the efficiency of fault handling. All DTC information can be viewed by accessing the URL of the visualization interface. The viewing method is simple and can be viewed anywhere without professional diagnostic equipment, wiring harnesses and professional diagnostic engineers. By real-time monitoring of the operating status of each ECU and through visual analysis of a large amount of DTC data, the rules and trends in the fault data can be discovered, which helps to timely discover potential problems and avoid faults. By managing the account authority of the URL of the visualization interface, different authorities are distributed to different personnel, thereby improving the security of DTC data. When a serious fault occurs in the vehicle, the monitoring system can promptly notify the customer service personnel of the car company, professional emergency handling personnel and other relevant personnel to improve the response speed of fault diagnosis, especially when the vehicle has a preset serious fault, such as a brake fault, a collision, and other faults that affect the life safety of the passengers, it can be discovered and responded to in the first time; statistics of the collected DTC information are realized through code, such as statistics on the number, frequency, and severity of vehicle faults. A fault statistics report is generated based on the statistical data to display the fault information intuitively and concisely, and the fault information after periodic statistics can be sent to the user terminal corresponding to the target user, such as the user's mobile phone.

[0076] Figure 6 is a block diagram of a fault statistics data visualization system shown in an exemplary embodiment of the present application. The device can be applied to Figure 1 The implementation environment shown in the figure is specifically configured in the computer device 102. The device can also be applied to other exemplary implementation environments and specifically configured in other devices. This embodiment does not limit the implementation environment to which the device is applied.

[0077] like Figure 6 As shown, the exemplary fault statistics data visualization system includes: a target vehicle 610 and a server 620 .

[0078] Among them, the target vehicle 610 is used to generate time series data, wherein the time series data includes diagnostic fault codes arranged according to fault time; the server side 620 is used to set fault statistical indicators and indicator display types corresponding to the fault statistical indicators, wherein the fault statistical indicators include the number of faults, severity, and frequency of occurrence, obtain the time series data generated by the target vehicle, classify the diagnostic fault codes according to the fault statistical indicators, obtain the classification results, perform data statistics on the fault time and the diagnostic fault codes according to the classification results, obtain the statistical data to be displayed, visualize the data to be displayed according to the indicator display type, obtain visualized data, and generate a fault statistical report based on the visualized data.

[0079] In one embodiment of the present application, the target vehicle includes a vehicle gateway and at least one electronic controller; the electronic controller is used to generate a diagnostic fault code; the vehicle gateway is connected to each electronic controller, and the vehicle gateway is used to collect the diagnostic fault code of each electronic controller, obtain the fault time, generate time series data according to the fault time and the diagnostic fault code, and send the time series data to the server.

[0080] In one embodiment of the present application, the server side includes at least one of the following: a time series database for storing time series data sent by a vehicle gateway; a visualization module for visually rendering the data to be displayed according to the indicator display type to obtain visualization data, generating a fault statistics report based on the visualization data, and displaying the fault statistics report; a service monitoring system for monitoring diagnostic fault codes, and if a new diagnostic fault code is generated by the target vehicle, sending a fault statistics report to a user terminal corresponding to the target user.

[0081] It should be noted that the fault statistics data visualization system provided in the above embodiment and the fault statistics data visualization method provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs operations has been described in detail in the method embodiment, and will not be repeated here. In practical applications, the fault statistics data visualization system provided in the above embodiment can allocate the above functions to different functional modules as needed, that is, divide the internal structure of the device into different functional modules to complete all or part of the functions described above, and this is not limited here.

[0082] An embodiment of the present application also provides an electronic device, including: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by one or more processors, the electronic device implements the fault statistics data visualization method provided in the above-mentioned embodiments.

[0083] Figure 7The structure diagram of the computer system suitable for implementing the electronic device of the embodiment of the present application is shown. It should be noted that: Figure 7 The computer system 700 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0084] like Figure 7 As shown, the computer system 700 includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 702 or the program loaded from the storage part 708 to the random access memory (RAM) 703, such as executing the methods provided in the above-mentioned various embodiments. In the RAM 703, various programs and data required for system operation are also stored. The CPU 701, the ROM 702 and the RAM 703 are connected to each other through the bus 704. The input / output (I / O) interface 705 is also connected to the bus 704.

[0085] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, a mouse, etc.; an output section 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed so that a computer program read therefrom is installed into the storage section 708 as needed.

[0086] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 709, and / or installed from a removable medium 711. When the computer program is executed by a central processing unit (CPU) 701, various functions defined in the system of the present application are executed.

[0087] It should be noted that the computer-readable medium shown in the embodiment of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. This propagated data signal can take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. A computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0088] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0089] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0090] Another aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor of a computer, enables the computer to execute the fault statistics data visualization method provided in the above-mentioned embodiments. The computer-readable storage medium may be included in the electronic device described in the above-mentioned embodiments, or may exist independently without being assembled into the electronic device.

[0091] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0092] Another aspect of the present application also provides a computer program product or a computer program, the computer program product or the computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the fault statistics data visualization method provided in each of the above embodiments.

[0093] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0094] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0095] The above embodiments are merely illustrative of the principles and effects of the present application, and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A method for visualizing fault statistical data, characterized in that: include: Pre-set fault statistical indicators and indicator display types corresponding to the fault statistical indicators, wherein the fault statistical indicators include the number of faults, severity, and frequency of occurrence; Acquiring time series data generated by a target vehicle, wherein the time series data includes diagnostic fault codes arranged according to fault time; Classifying the diagnostic fault codes according to the fault statistical index to obtain a classification result, and performing data statistics on the fault time and the diagnostic fault code according to the classification result to obtain statistical data to be displayed; The data to be displayed is visually rendered according to the indicator display type to obtain visual data, and a fault statistics report is generated according to the visual data.

2. The method for visualizing fault statistical data according to claim 1, characterized in that: After generating a fault statistics report according to the visualization data, the method further includes: Pre-setting the data permission label corresponding to the fault statistical indicator; Obtain a target user and user permissions corresponding to the target user; Determine target data from the fault statistics report according to a comparison result between the user authority and the data authority tag; A target report is generated according to the target data and the fault information corresponding to the diagnostic fault code.

3. The method for visualizing fault statistical data according to claim 2, characterized in that: The method further comprises: The target report is sent to a user terminal corresponding to the target user, wherein the user terminal is provided with a visualization page, and the visualization page is used to display the target report and / or execute a page operation instruction input by the target user based on the preset operation authority of the target user.

4. The method for visualizing fault statistical data according to claim 3, characterized in that: The visualization page executes the page operation instruction input by the target user based on the preset operation authority of the target user in at least one of the following ways: If the preset operation authority includes the first operation authority, executing at least one of the data viewing instruction, data editing instruction and data management instruction input by the target user; If the preset operation authority includes the second operation authority, the data viewing instruction input by the target user is executed.

5. The method for visualizing fault statistical data according to claim 2, characterized in that: The method further comprises at least one of the following: Generate a periodic task, wherein the periodic task is used to update the target report in each preset update period and send the updated target report to the user terminal corresponding to the target user; The diagnostic trouble code of the target vehicle is monitored by utilizing a preset service monitoring system, and if a new diagnostic trouble code is detected, a target report is updated and the updated target report is sent to a user terminal corresponding to the target user.

6. The method for visualizing fault statistical data according to any one of claims 1 to 5, characterized in that: The method further comprises: Obtaining historical fault codes, performing statistics on the historical fault codes, and determining minimum support and minimum confidence according to the statistical results; Extracting an initial item set corresponding to the diagnostic fault code from the historical fault code by a preset association rule mining algorithm, extracting a frequent item set corresponding to the diagnostic fault code from the initial item set based on the minimum support, and extracting association rules from the frequent item set; Screening the association rules based on the minimum confidence to obtain an association result; Determine an associated fault code of the diagnostic fault code according to the association result, and display the associated fault code through a visualization page.

7. A fault statistics visualization system, characterized in that: include: A target vehicle, used to generate time series data, wherein the time series data includes diagnostic trouble codes arranged according to the time of the trouble; The server side is used to set fault statistical indicators and indicator display types corresponding to the fault statistical indicators, wherein the fault statistical indicators include the number of faults, severity, and frequency of occurrence, obtain the time series data generated by the target vehicle, classify the diagnostic fault codes according to the fault statistical indicators, obtain the classification results, perform data statistics on the fault time and the diagnostic fault codes according to the classification results, obtain the statistical data to be displayed, visualize the data to be displayed according to the indicator display type, obtain visualized data, and generate a fault statistical report based on the visualized data.

8. The fault statistics data visualization system according to claim 7, characterized in that: The target vehicle includes a vehicle gateway and at least one electronic controller; The electronic controller is used to generate the diagnostic fault code; The vehicle gateway is connected to each of the electronic controllers, and is used to collect diagnostic fault codes of each of the electronic controllers, obtain fault time, generate the time series data according to the fault time and the diagnostic fault code, and send the time series data to the server.

9. The fault statistics data visualization system according to claim 8, characterized in that: The server side includes at least one of the following: A time series database, used to store time series data sent by the vehicle gateway; A visualization module, used for visually rendering the data to be displayed according to the indicator display type to obtain visualization data, generating a fault statistics report according to the visualization data, and displaying the fault statistics report; The service monitoring system is used to monitor the diagnostic fault code, and if it is monitored that the target vehicle generates a new diagnostic fault code, the fault statistics report is sent to the user terminal corresponding to the target user.

10. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device, used to store one or more programs, when the one or more programs are executed by the one or more processors, enables the electronic device to implement the fault statistics data visualization method according to any one of claims 1 to 6.

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