Vehicle electromagnetic compatibility test method and device based on big data platform

Abstract

The invention discloses a vehicle electromagnetic compatibility test method and device based on a big data platform, and relates to the technical field of vehicle testing, and the method comprises the steps: creating a vehicle electromagnetic compatibility detection item in a cloud platform, and generating a detection task; detecting equipment and a to-be-detected piece are connected to the cloud platform through the Internet of Things technology, and standardized parameters and a hardware connection template of a detection task are configured; physical connection of the detection system is completed based on the hardware connection template; calling an automatic test module to execute a standardized test process, and collecting test data in real time; performing multi-dimensional analysis and intelligent evaluation on the test data to generate a detection report and authentication data; synchronizing the detection report and the authentication data to a service platform for secondary data application; visualization and collaborative management of the test process are carried out through the remote monitoring module.

Description

Technical Field

[0001] The present application relates to the field of vehicle testing technology, and in particular to a vehicle electromagnetic compatibility test method and device based on a big data platform. Background Art

[0002] In recent years, due to the sharp increase in vehicle production, the workload of vehicle electromagnetic compatibility testing has also increased dramatically. Traditional electromagnetic compatibility testing mainly relies on manpower for physical testing and verification. This testing method has problems such as long cycle, low efficiency and data silos, and can no longer meet the growing testing needs.

[0003] At present, some digital platforms and systems have been applied in laboratories for data collection and data analysis of laboratory equipment. However, the existing platforms and systems are very limited and relatively simple for data collection and analysis of equipment, and still cannot change the problems of long electromagnetic compatibility test cycle, low efficiency and data islands. Summary of the invention

[0004] The purpose of this application is to provide a vehicle electromagnetic compatibility test method and device based on a big data platform.

[0005] To achieve the above objectives, this application provides the following solutions: In a first aspect, the present application provides a vehicle electromagnetic compatibility test method based on a big data platform, comprising: Create vehicle electromagnetic compatibility testing projects and generate testing tasks in the cloud platform; Connect the testing equipment and the test piece to the cloud platform through the Internet of Things technology, and configure the standardized parameters and hardware connection template of the testing task; Complete the physical connection of the detection system based on the hardware connection template; Call the automated testing module to execute standardized testing procedures and collect test data in real time; Conduct multi-dimensional analysis and intelligent evaluation on the test data to generate test reports and certification data; Synchronize the test report and the authentication data to the business platform for secondary data application; Visualization and collaborative management of the test process are carried out through the remote monitoring module.

[0006] Optionally, the step of creating a vehicle electromagnetic compatibility test project and generating a test task in the cloud platform includes: Receive the test project application information submitted by the user, wherein the test project application information includes vehicle type, test items and sample quantity; Automatically generate a project contract and a commission form based on the test project application information; Assign project managers and inspectors to the said order; Prioritize the multi-sample testing tasks based on the test item type of the order and the matching degree of laboratory resources; The sorted detection tasks are sent to the corresponding automatic testing system according to preset rules.

[0007] Optionally, the step of configuring the standardized parameters of the detection task and the hardware connection template includes: Enter the basic information and communication protocol parameters of the detection equipment; Setting a test frequency range, a calibration mode and a limit line threshold associated with the detection task; Drawing a hardware connection template based on the graphical interface provided by the cloud platform, wherein the hardware connection template includes the physical connection logic of the receiver, the sensor and the device under test; Saving the hardware connection template to a device list and associating it with the detection task; Perform device connectivity verification tests and generate device operation status reports.

[0008] Optionally, the step of calling the automated testing module to execute a standardized testing process includes: Selecting a standard test mode or a conventional test mode according to the detection task type; In the standard test mode, the preset hardware template, limit line parameters and document template are automatically loaded; In the conventional test mode, the user is allowed to customize and adjust the hardware template and test parameters; the test data curve and annotation information collected from the detection equipment are displayed in real time; Provide the functions of pausing, terminating and warning of abnormal data in the test process; The test data is synchronized to a cloud storage unit.

[0009] Optionally, the step of performing multi-dimensional analysis and intelligent evaluation on the test data includes: Applying a preset algorithm to perform noise filtering and feature extraction on the test data; Comparing the processed data with the limit line threshold to generate a compliance evaluation result; Calculating the electromagnetic compatibility performance score of the vehicle based on the compliance evaluation result; Generate test data trend analysis reports using data mining technology; The test data trend analysis report is associated with a vehicle model database to generate a vehicle model ranking list.

[0010] Optionally, the step of visualizing and collaboratively managing the test process through the remote monitoring module includes: Deploy a large visual data screen in the cloud platform to display the equipment status and test progress in real time; Open the test process data interface for remote users to support remote monitoring and operation instruction issuance; Record the operating hours and maintenance cycles of the detection equipment and trigger equipment maintenance reminders; Statistics are collected on the task completion and resource consumption data of inspectors, and production capacity analysis reports are generated.

[0011] Optionally, the step of synchronizing the test report and the authentication data to a business platform for secondary data application includes: Automatically convert the test report into a certification document in a format specified by a preset standard; Importing the authentication data into a data analysis platform for clustering and association analysis; Generate a vehicle electromagnetic compatibility optimization suggestion plan based on the data analysis results; Establish a test data sharing channel to support OEMs to retrieve historical test data through the business platform. In the second aspect, the present application provides a vehicle electromagnetic compatibility test device based on a big data platform, comprising: Configuration module, used to create vehicle electromagnetic compatibility testing projects and generate testing tasks in the cloud platform; Connect the testing equipment and the test piece to the cloud platform through the Internet of Things technology, and configure the standardized parameters and hardware connection template of the testing task; Complete the physical connection of the detection system based on the hardware connection template; The test module is used to call the automated test module to execute the standardized test process and collect test data in real time; An analysis module, used to perform multi-dimensional analysis and intelligent evaluation on the test data, and generate a test report and certification data; Synchronize the test report and the authentication data to the business platform for secondary data application; Visualization and collaborative management of the test process are carried out through the remote monitoring module.

[0012] Optionally, the configuration module is further used to: Receive the test project application information submitted by the user, wherein the test project application information includes vehicle type, test items and sample quantity; Automatically generate a project contract and a commission form based on the test project application information; Assign project managers and inspectors to the said order; Prioritize the multi-sample testing tasks based on the test item type of the order and the matching degree of laboratory resources; The sorted detection tasks are sent to the corresponding automatic testing system according to preset rules.

[0013] Optionally, the configuration module is further used to: Enter the basic information and communication protocol parameters of the detection equipment; Setting a test frequency range, a calibration mode and a limit line threshold associated with the detection task; Drawing a hardware connection template based on the graphical interface provided by the cloud platform, wherein the hardware connection template includes the physical connection logic of the receiver, the sensor and the device under test; Saving the hardware connection template to a device list and associating it with the detection task; Perform device connectivity verification tests and generate device operation status reports.

[0014] Optionally, the test module is further used to: Selecting a standard test mode or a conventional test mode according to the detection task type; In the standard test mode, the preset hardware template, limit line parameters and document template are automatically loaded; In the conventional test mode, the user is allowed to customize and adjust the hardware template and test parameters; the test data curve and annotation information collected from the detection equipment are displayed in real time; Provide the functions of pausing, terminating and warning of abnormal data in the test process; The test data is synchronized to a cloud storage unit.

[0015] Optionally, the analysis module is further used to: Applying a preset algorithm to perform noise filtering and feature extraction on the test data; Comparing the processed data with the limit line threshold to generate a compliance evaluation result; Calculating the electromagnetic compatibility performance score of the vehicle based on the compliance evaluation result; Generate test data trend analysis reports using data mining technology; The test data trend analysis report is associated with a vehicle model database to generate a vehicle model ranking list.

[0016] Optionally, the analysis module is further used to: Deploy a large visual data screen in the cloud platform to display the equipment status and test progress in real time; Open the test process data interface for remote users to support remote monitoring and operation instruction issuance; Record the operating hours and maintenance cycles of the detection equipment and trigger equipment maintenance reminders; Statistics are collected on the task completion and resource consumption data of inspectors, and production capacity analysis reports are generated.

[0017] Optionally, the analysis module is further used to: Automatically convert the test report into a certification document in a format specified by a preset standard; Importing the authentication data into a data analysis platform for clustering and association analysis; Generate a vehicle electromagnetic compatibility optimization suggestion plan based on the data analysis results; A test data sharing channel is established to support OEMs to retrieve historical test data through the business platform.

[0018] In a third aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any one of the above-mentioned vehicle electromagnetic compatibility test methods based on a big data platform.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the above-mentioned vehicle electromagnetic compatibility test methods based on a big data platform.

[0020] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any of the above-mentioned vehicle electromagnetic compatibility test methods based on a big data platform.

[0021] According to the specific embodiments provided in this application, this application discloses the following technical effects: The present application provides a vehicle electromagnetic compatibility test method and device based on a big data platform. Through the deep integration of the cloud platform and the Internet of Things technology, the full process automation of the vehicle electromagnetic compatibility test is realized. The system reduces manual intervention, improves test efficiency, solves the problem of data islands, and optimizes vehicle design through intelligent analysis. The remote collaboration function further supports cross-regional resource sharing, ultimately forming an efficient, accurate, and scalable test system. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1A schematic diagram of a flow chart of a vehicle electromagnetic compatibility test method based on a big data platform provided in one embodiment of the present application; Figure 2 A system schematic diagram of a vehicle electromagnetic compatibility test method based on a big data platform provided in one embodiment of the present application; Figure 3 A schematic diagram of sample information of a vehicle electromagnetic compatibility test method based on a big data platform provided in one embodiment of the present application; Figure 4 One of the effect schematic diagrams of a vehicle electromagnetic compatibility test method based on a big data platform provided in one embodiment of the present application; Figure 5 A schematic diagram of functional modules of a vehicle electromagnetic compatibility test device based on a big data platform provided in one embodiment of the present application; Figure 6 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0025] like Figure 1 As shown, some embodiments of the present application provide a vehicle electromagnetic compatibility test method based on a big data platform, which includes: Reference Figure 2 The automated testing system based on the edge-cloud collaborative architecture with software and hardware decoupling in the embodiment of the present application is a highly intelligent solution. It utilizes cloud resources and automated management tools, and adopts domestic advanced Internet of Things technologies to achieve interconnection between domestic and foreign measuring instrument manufacturers and establish connections with the cloud platform. It adapts to different test equipment and needs through the flexibility and elastic expansion capabilities of the cloud platform, and can provide automatic collection, analysis, mining and use of raw test data for vehicle electromagnetic compatibility test and certification. It has real-time monitoring, data analysis and report generation functions, which greatly improves test efficiency, shortens test cycle, and solves the problems of equipment heterogeneity and data heterogeneity. Figure 1 Evaluate system composition for automated testing.

[0026] Step 101, creating a vehicle electromagnetic compatibility testing project in the cloud platform and generating a testing task.

[0027] In the embodiments of the present application, cloud platform: a resource pooling service platform based on cloud computing technology, which provides centralized management and elastic expansion capabilities for computing, storage, network and other resources. Vehicle electromagnetic compatibility testing project: a test task for the electromagnetic compatibility performance of a vehicle, including test standards, test items, sample information and other elements. Testing task: an execution plan generated by the system based on the testing project, including task parameters, execution time, personnel allocation, etc.

[0028] The system receives the vehicle electromagnetic compatibility test project application submitted by the user on the cloud platform, automatically parses the application content (such as vehicle model, manufacturer, test standard, etc.), and generates a unique project identifier. Subsequently, the system assigns a project manager according to the preset rules, and automatically generates detailed parameters of the test task (such as test items, frequency range, execution standard, time node, etc.), and marks the task status as "to be executed".

[0029] Specifically, first apply for the inspection project in the cloud platform, generate the corresponding project contract and commission, enter the relevant vehicle sample information, including manufacturer, model, inspection items and other information, automatically assign the relevant project manager, and the project manager assigns the inspection personnel. The inspection personnel collect the relevant inspection equipment and samples. After receiving the commission for the project application, the automated testing system establishes the inspection task and configures the inspection start and end time, inspection personnel, execution standards, test items, test methods, test frequency range, antenna position and other parameters.

[0030] For example, sample information can refer to Figure 3 .

[0031] Step 102: Connect the testing equipment and the test piece to the cloud platform through the Internet of Things technology, and configure the standardized parameters and hardware connection template of the testing task.

[0032] In the embodiments of the present application, detection equipment: instruments used for vehicle electromagnetic compatibility testing (such as receivers, antennas, power amplifiers, etc.). PUT: vehicles or components that require electromagnetic compatibility testing. Internet of Things technology: technology that enables interconnection between devices and the cloud through communication protocols (such as MQTT, HTTP). Standardized parameters: predefined detection parameters (such as frequency range, calibration mode, limit lines, etc.). Hardware connection template: a graphical configuration template that describes the physical connection relationship between devices.

[0033] The system connects the test equipment (such as receivers) and the DUT to the cloud platform through the Internet of Things protocol (such as Modbus, TCP / IP), automatically identifies the device model and enters basic information (such as IP address, port number). Subsequently, the system loads the pre-stored standardized parameters (such as the frequency range in the GB34660-2017 standard) and allows users to edit the hardware connection template (such as the connection path between the antenna and the receiver) through a graphical interface. After the template configuration is completed, the system saves it to the database for subsequent calls.

[0034] Specifically, the test personnel will connect the received test equipment and the tested device to the automated test system through the Internet of Things technology, and can enter the basic information of the equipment, such as model, name, connection information protocol, port, address, and the unique information frequency of the equipment. When the settings are completed, the device information will be saved in the equipment list of the automated test system. When the user uses this system to draw the hardware connection template graphics, he can select all the devices saved in the system. At the same time, the system also provides a test function for the configured equipment. The equipment test of the power amplifier is as follows Figure 4 shown.

[0035] The automated test system supports test personnel to set the test standards, test frequency, calibration, result report and limit lines of the test items. The automated test system can set the standards for the test items, enter relevant standard files, and automatically apply them to subsequent test processes; the system can set the relevant parameters of the test frequency and result report, and automatically update them to the test process; the system can set the calibration mode, start frequency, end frequency, step mode and step size. After the setting is completed, the calibration is performed and a calibration correction table is generated; the system can use tables to flexibly edit the limit lines. After the setting is completed, the limit line graph can be seen. After the editing is completed, the limit data will be immediately applied to the test process.

[0036] Step 103: completing the physical connection of the detection system based on the hardware connection template.

[0037] In the embodiment of the present application, the system sends control instructions to the detection device (such as starting the antenna lifting device and switching the coaxial cable connection) according to the configuration information of the hardware connection template. At the same time, the system verifies the compliance of the physical connection (such as cable impedance matching and normal device status) through sensors. If an abnormality is found, an alarm is triggered and the process is suspended.

[0038] Specifically, a hardware connection template can be drawn in the automated test system. The template can be edited in a graphical interface, and the editing result is valid for the test process. The hardware template can combine the equipment, path and frequency information selected for the test in the equipment list. Each hardware template can contain several frequency bands to guide the test personnel to configure the system hardware. The nodes of the hardware template represent instruments such as receivers, sensors such as antennas, equipment under test (EUT) or other devices, which are connected by coaxial cables, GPIB cables, network cables and other cables.

[0039] Step 104, calling the automated testing module to execute the standardized testing process and collect test data in real time.

[0040] In the embodiments of the present application, automated test module: a preset software program used to control the device to perform test steps. Standardized test process: a test sequence defined by the test standard (such as calibration, scanning, data recording). Test data: raw data collected during the test process (such as radiation intensity, frequency response).

[0041] The system calls the automated test module and performs the test in stages according to the standardized process: the automatic control device performs frequency calibration and generates a correction table; traverses the test points according to the preset frequency range and collects real-time data; stores the data in the cloud platform database and synchronizes it to the visual interface. The system ensures the continuity and low latency of the collection through real-time data streaming technology (such as WebSocket).

[0042] Specifically, the automated testing system provides two automated testing modes: standard testing and conventional testing. After receiving the commission form of the project application, the automated testing system can establish an automatic matching testing mode for the detection task.

[0043] When the test item to be executed is a standard test item, the standard test is matched. The system automatically calls the corresponding test equipment, hardware template, extreme value line, document template, etc. to generate pre-test parameters. The user can choose to modify the corresponding parameters or choose to use the configured data and click the test button to perform the test.

[0044] When the user needs to change the relevant parameters or templates of the executed test items, routine tests can be performed. The system provides a simple, functional and user-friendly test interface. Users can set hardware templates and report templates as well as set pre-test parameters. The curve display area can display the data information collected from the instrument and the annotation of the curve points in real time. The operation interface has automatic control functions, such as pause and termination of the test process, characteristic data monitoring, movement of curve points, report generation and other functions.

[0045] Step 105, performing multi-dimensional analysis and intelligent evaluation on the test data to generate a test report and certification data.

[0046] In the embodiments of the present application, multi-dimensional analysis: parsing data from multiple perspectives such as time, frequency, and space. Intelligent evaluation: evaluating test results based on algorithms (such as threshold comparison and trend prediction). Test report: a standard document containing test conclusions and data charts. Certification data: a formatted data package that meets industry certification requirements.

[0047] The system performs the following operations on the original test data: preprocessing, filtering, denoising, and data normalization; analysis, calculating the radiation peak and mean, and comparing the limit line; evaluation, the AI ​​model determines whether it has passed the certification and generates a performance ranking. Finally, the system calls the report template engine to automatically generate a test report in PDF format and packages the certification data in JSON or XML format.

[0048] Step 106: Synchronize the test report and the authentication data to the business platform for secondary data application.

[0049] In the embodiments of the present application, the business platform is a core system for managing the testing business, supporting functions such as data query and statistics. Secondary data application: using the test data for other scenarios (such as design optimization and market analysis).

[0050] The system pushes the test report and certification data to the business platform through the API interface, triggering the following operations: data entry and structured storage in the business database; permission allocation, opening data access rights by role; application triggering, starting the preset secondary analysis task (such as generating a vehicle electromagnetic compatibility performance ranking).

[0051] Step 107, visualizing and collaboratively managing the test process through a remote monitoring module.

[0052] In the embodiments of the present application, remote monitoring module: a software component that supports real-time viewing of test status. Visualization: displaying data in the form of charts, curves, etc. Collaborative management: a mechanism for simultaneous operation and information sharing by multiple users.

[0053] The system provides the following functions through the remote monitoring module: real-time images and video streams to display the status of laboratory equipment; large data screen to dynamically update test curves and alarm information; collaborative interface to support remote users to access through the Web terminal and synchronize operation logs and task progress.

[0054] The embodiment of the present application realizes the full process automation of vehicle electromagnetic compatibility testing through the deep integration of cloud platform and Internet of Things technology. The system reduces manual intervention, improves test efficiency, solves the problem of data islands, optimizes vehicle design through intelligent analysis, and the remote collaboration function further supports cross-regional resource sharing, ultimately forming an efficient, accurate and scalable testing system.

[0055] Optionally, the step 101 includes: Step 1011, receiving the test project application information submitted by the user, wherein the test project application information includes vehicle type, test items and sample quantity.

[0056] In the embodiment of the present application, the test project application information is the data set submitted by the user for starting the test task, including key information such as vehicle model, test items, and sample quantity. Vehicle model: the vehicle model that needs to be tested for electromagnetic compatibility. Test items: specific test items (such as radiated emission, conducted emission, etc.). Sample quantity: the number of vehicles or components to be tested.

[0057] The system receives the application information of the test project through the user interface, parses and verifies the integrity and compliance of the data (such as whether the vehicle model is in the supported list and whether the test items meet the standards). Subsequently, the system stores the application information in the database and generates a unique application number for tracking and management of subsequent processes.

[0058] Step 1012, automatically generating a project contract and a commission form based on the inspection project application information.

[0059] In the embodiments of the present application, project contract: a legal document that specifies the rights and obligations of both parties to the inspection task. Commission order: an execution document that describes the content of the inspection task in detail, including task parameters, time nodes, etc.

[0060] The system calls the preset contract template based on the application information of the inspection project, automatically fills in key fields (such as vehicle model, inspection items, sample quantity, execution standards, etc.), and generates a project contract in PDF format. At the same time, the system generates a commission, lists the execution parameters of the inspection task in detail (such as test frequency range, antenna position, calibration mode, etc.), and associates the contract with the commission and stores it in the database.

[0061] Step 1013, assigning a project manager and a tester to the order.

[0062] In the embodiment of the present application, the system selects suitable project managers and inspectors from the database based on the inspection item type of the order and the current resource status (such as personnel idleness and skill matching). Subsequently, the system updates the task assignment information to the order and notifies the relevant personnel through the message queue. After the assignment is completed, the system marks the order status as "assigned".

[0063] Step 1014: Prioritize the multi-sample testing tasks based on the test item type of the order and the matching degree of laboratory resources.

[0064] In the embodiments of the present application, the detection item type: the specific category of the detection task (such as radiated emission, conducted emission, etc.). Laboratory resource matching degree: the degree of adaptation between the detection task and laboratory equipment, personnel and other resources. Priority sorting: the order of execution of multiple detection tasks according to preset rules.

[0065] The system analyzes the types of test items in the order (e.g., radiated emission testing requires antennas in a specific frequency range), and combines the real-time status of laboratory resources (e.g., equipment availability, personnel load) to calculate the matching score for each test task. The system then prioritizes the multi-sample test tasks based on the scores and stores the ranking results in the task queue.

[0066] Step 1015: Send the sorted detection tasks to the corresponding automatic testing system according to preset rules.

[0067] In the embodiment of the present application, the system sends the detection task to the corresponding automated test system according to the sorting results and preset rules (such as high-priority tasks are sent first, and low-load laboratories are assigned first). During the sending process, the system synchronously transmits the task parameters (such as hardware connection templates, test frequency range) to the target system and updates the task status to "sent". After the target system receives the task, it automatically starts the test process.

[0068] Optionally, the step 102 includes: Step 1021, input the basic information and communication protocol parameters of the detection device.

[0069] In the embodiments of the present application, the detection equipment: the instrument used to perform the electromagnetic compatibility test of the vehicle (such as a receiver, antenna, power amplifier, etc.). Basic information: the basic properties of the device (such as model, name, serial number, etc.). Communication protocol parameters: the communication configuration required for the device to interact with the system (such as IP address, port number, protocol type, etc.).

[0070] The system receives the basic information and communication protocol parameters of the detection equipment through the user interface or automation interface, and verifies the integrity and compliance of the data (such as whether the IP address format is correct). Subsequently, the system stores the device information in the database and generates a unique device identifier. After the communication protocol parameters are configured, the system verifies the connection status between the device and the cloud platform through a handshake protocol (such as the TCP three-way handshake) to ensure the reliability of subsequent communications.

[0071] Step 1022, setting the test frequency range, calibration mode and limit line threshold associated with the detection task.

[0072] In the embodiments of the present application, the test frequency range is the frequency range that needs to be covered in the detection task (such as 30MHz-1000MHz). Calibration mode is the way of equipment calibration (such as automatic calibration, manual calibration). Limit line threshold is the boundary value for determining whether the test result is qualified (such as the upper limit of the radiation intensity).

[0073] The system loads the preset test frequency range (such as the frequency range in the GB34660-2017 standard) according to the requirements of the detection task, and allows the user to adjust specific parameters through the interface. Subsequently, the system configures the calibration mode (such as the frequency step size of the automatic calibration) and the limit line threshold (such as editing the limit line data through a table). After the configuration is completed, the system stores the parameters in the task configuration file for subsequent test processes to call.

[0074] Step 1023: Draw a hardware connection template based on the graphical interface provided by the cloud platform, wherein the hardware connection template includes the physical connection logic of the receiver, the sensor, and the device under test.

[0075] In the embodiment of the present application, the system provides a drag-and-drop editing function through a graphical interface. The user can select the receiver, sensor and DUT from the device list and draw the connection relationship between them (such as connecting the receiver and the antenna with a coaxial cable). The system verifies the compliance of the connection logic (such as impedance matching, interface type) in real time and dynamically displays the connection status in the interface. After the drawing is completed, the system generates a graphical representation of the hardware connection template and stores it in the database.

[0076] Step 1024, save the hardware connection template to the device list, and associate it with the detection task.

[0077] In the embodiment of the present application, the system stores the drawn hardware connection template in the device list and generates a unique template identifier. Subsequently, the system associates the template with the detection task and updates the hardware connection information in the task configuration file. After the association is completed, the system marks the template status as "enabled" and synchronously updates the task status to "configuration completed".

[0078] Step 1025, perform device connectivity verification test and generate a device operation status report.

[0079] In the embodiment of the present application, the system calls the automated test script to verify the connectivity of each device in turn. The communication test verifies the communication status between the device and the system through the Ping command or protocol handshake; the functional test verifies the device response by sending control instructions (such as starting the antenna lifting device); the data acquisition test simulates the data acquisition process to verify the integrity and real-time nature of the data upload. After the test is completed, the system generates a device operation status report, including information such as device status, communication delay, error log, etc., and stores the report in the database for subsequent reference.

[0080] The embodiments of the present application ensure efficient execution of detection tasks and accurate data collection through a systematic device configuration and verification process. The system reduces manual intervention, improves configuration efficiency, and ensures the reliability of equipment through connectivity verification testing. Graphical editing and automated verification of hardware connection templates further optimize the test process, ultimately forming an efficient, accurate, and scalable detection task execution system.

[0081] Optionally, the step 104 includes: Step 1041 , selecting a standard test mode or a conventional test mode according to the detection task type.

[0082] In the embodiments of the present application, the detection task type: the classification of the detection task (such as standard detection items, custom detection items). Standard test mode: an automated test process executed according to preset standards without user intervention. Conventional test mode: a flexible test mode that allows users to customize test parameters and processes.

[0083] The system automatically selects the test mode according to the type of detection task: if the detection task is a standard detection item (such as GB34660-2017 vehicle electromagnetic radiation emission test), the system selects the standard test mode; if the detection task is a custom detection item (such as a test in a user-specific frequency range), the system selects the conventional test mode. After the selection is completed, the system updates the test mode identifier in the task configuration file and prepares to load the corresponding test parameters and templates.

[0084] Step 1042, in the standard test mode, automatically load the preset hardware template, limit line parameters and document template.

[0085] In the embodiment of the present application, hardware template: a graphical configuration template that describes the physical connection relationship between devices. Limit line parameter: a boundary value (such as the upper limit of radiation intensity) for determining whether the test result is qualified. Document template: a standard format template for generating a test report.

[0086] In standard test mode, the system loads the hardware template, limit line parameters and document template associated with the test task from the database. The hardware template automatically configures the connection relationship of the receiver, antenna and other equipment; the limit line parameters load the preset frequency range and radiation intensity threshold; the document template prepares the standard format for generating the test report. After loading, the system verifies the integrity of the template and parameters and marks the test process as "ready".

[0087] Step 1043: In the conventional test mode, the user is allowed to customize and adjust the hardware template and test parameters, and display the test data curve and annotation information collected from the detection device in real time.

[0088] In the embodiments of the present application, the user can modify the hardware connection relationship or test parameters according to the user's needs. Test data curve, the data collected from the detection equipment is displayed in a graphical manner (such as a curve of radiation intensity changing with frequency). Annotation information, key points marked on the data curve (such as peak values, limit values).

[0089] In the normal test mode, the system provides a user interface for users to adjust the hardware template (such as modifying the antenna connection path) and test parameters (such as changing the frequency range and step size). After the adjustment is completed, the system displays the test data curve collected from the detection equipment in real time and marks key points on the curve (such as peak frequency and limit value). The system ensures the real-time and accuracy of the curve and annotation information through a dynamic refresh mechanism.

[0090] Step 1044 provides the functions of pausing, terminating and warning of abnormal data in the test process.

[0091] In the embodiment of the present application, the system provides the following control functions during the test process: pause, the user can pause the test process through the interface, and the system saves the current test status (such as frequency points, collected data); terminate, the user can terminate the test process through the interface, the system clears the current status and releases equipment resources; data abnormality warning, the system monitors the test data in real time, if it exceeds the limit line threshold or abnormal fluctuations occur, the warning is triggered and the user is notified. The system records all operations and warning events through logs for subsequent analysis and review.

[0092] Step 1045, synchronizing the test data to a cloud storage unit.

[0093] In the embodiment of the present application, the system synchronizes the collected test data (such as frequency points, radiation intensity values) to the cloud storage unit in real time during the test process through an encrypted transmission protocol (such as HTTPS). After the synchronization is completed, the system verifies the integrity and consistency of the data and updates the task status to "data synchronized". The cloud storage unit stores the data in categories (such as by task ID, timestamp), and triggers the subsequent data analysis and report generation process.

[0094] The embodiment of the present application meets the needs of different detection tasks by flexibly switching between standard and conventional test modes. The system provides real-time data display and process control functions to ensure the controllability and transparency of the test process. Data synchronization and abnormal warning mechanisms further ensure the accuracy and security of test data. Ultimately, the system forms an efficient, flexible and reliable automated testing system, significantly improving the efficiency and quality of vehicle electromagnetic compatibility testing.

[0095] Optionally, the step 105 includes: Step 1051, applying a preset algorithm to perform noise filtering and feature extraction on the test data.

[0096] In the embodiment of the present application, the system first applies a preset noise filtering algorithm to process the test data to remove noise and interference information in the data to ensure the accuracy and reliability of the data. Then, the system uses a feature extraction algorithm to extract key features from the filtered data. These features can reflect the core indicators of the vehicle's electromagnetic compatibility performance. Through this step, the system can provide a high-quality data foundation for subsequent analysis.

[0097] Step 1052, comparing the processed data with the limit line threshold to generate a compliance evaluation result.

[0098] In the embodiment of the present application, limit line threshold: The limit line threshold refers to the pre-set qualified standard or boundary value of electromagnetic compatibility performance. The test data must meet these thresholds to be considered compliant. Compliance evaluation result: The compliance evaluation result refers to the conclusion of the system on whether the electromagnetic compatibility performance of the vehicle meets the standard based on the comparison result of the test data and the limit line threshold.

[0099] The system compares the test data after noise filtering and feature extraction with the preset limit line threshold. The system determines whether the data is within the allowed range by calculating the difference between the test data and the threshold. If the data meets the threshold requirements, the system generates a compliance evaluation result of "qualified"; if the data exceeds the threshold, it generates an evaluation result of "unqualified". This step ensures the objectivity and accuracy of the test results.

[0100] Step 1053: Calculate the vehicle electromagnetic compatibility performance score based on the compliance evaluation result.

[0101] In the embodiment of the present application, the electromagnetic compatibility performance score: the electromagnetic compatibility performance score refers to a quantitative index of the electromagnetic compatibility performance of the vehicle calculated by the system according to the compliance evaluation results and certain scoring rules. The higher the score, the better the electromagnetic compatibility performance of the vehicle.

[0102] The system calculates the vehicle's electromagnetic compatibility performance score based on the compliance evaluation results and the preset scoring rules. The system will comprehensively calculate the score based on factors such as the proximity of the test data to the limit line threshold and the stability of the data. This step provides a quantitative evaluation standard for the vehicle's electromagnetic compatibility performance, which is convenient for subsequent ranking and optimization.

[0103] Step 1054, using data mining technology to generate a test data trend analysis report.

[0104] In the embodiments of the present application, data mining technology: data mining technology refers to the technology of extracting useful information from a large amount of data through algorithms, which is usually used to discover patterns, trends and associations in data. Trend analysis report: trend analysis report refers to the data change trend report generated by the system through analysis of historical data and current data, which is used to predict future data trends or discover problems.

[0105] The system uses data mining technology to conduct in-depth analysis of test data and extract trends and patterns in the data. The system generates a trend analysis report by analyzing the changing trends of historical data and current data. The report can show the changing trends of the vehicle's electromagnetic compatibility performance and help users understand the long-term performance and potential problems.

[0106] Step 1055, associating the test data trend analysis report with the vehicle model database to generate a vehicle model ranking list.

[0107] In the embodiment of the present application, vehicle model database: the vehicle model database refers to a database that stores information on different vehicle models, usually including basic information such as vehicle model name, model, and year of production. Vehicle model ranking list: the vehicle model ranking list refers to a list in which the system sorts the vehicle models according to the electromagnetic compatibility performance scores of the vehicles, and the higher the score, the higher the ranking of the vehicle.

[0108] The system associates the generated test data trend analysis report with the vehicle model database, and generates a model ranking list based on the vehicle's electromagnetic compatibility performance score. The system sorts the models according to the scores, with models with higher scores ranking higher. This step provides users with an intuitive model performance comparison tool, making it easier for users to choose models with better performance.

[0109] The embodiment of the present application can perform a series of processing such as noise filtering, feature extraction, compliance evaluation, performance scoring, trend analysis and vehicle model ranking on the vehicle electromagnetic compatibility test data. These steps work together to ensure the accuracy and reliability of the test data, provide quantitative evaluation criteria for the electromagnetic compatibility performance of the vehicle, and generate trend analysis and vehicle model ranking reports. Ultimately, the system can help users fully understand the electromagnetic compatibility performance of the vehicle, optimize vehicle design, improve test efficiency, and provide data support for decision-making.

[0110] Optionally, the step 107 includes: Step 1071, deploying a large visual data screen in the cloud platform to display the device status and test progress in real time.

[0111] In the embodiments of the present application, the visual data screen: The visual data screen refers to a system that displays data through a graphical interface, which is usually used to monitor and display key information such as device status and test progress in real time. It can present complex data in an intuitive way, so that users can quickly understand the operation of the current system. Device status: The device status refers to the operation of the detection device during the test process, including the switch status, working mode, fault information, etc. of the device. Test progress: The test progress refers to the completion status of the current test task, including completed test items, ongoing test items, and remaining test items.

[0112] The system deploys a large visual data screen in the cloud platform, which displays the status of the equipment and the test progress in real time. The system collects data from various testing devices and displays the data on the large screen through a graphical interface. The equipment status information includes the equipment's operating status, fault alarms, etc., and the test progress information includes the completion of the current test task, the remaining test time, etc. Through the large visual data screen, users can monitor the test process in real time and promptly discover and handle abnormal situations.

[0113] Step 1072, opening the test process data interface for remote users to support remote monitoring and issuing of operation instructions.

[0114] In the embodiment of the present application, the system opens a data interface of the test process to remote users, allowing users to remotely access the system through the network. Users can view data such as device status and test progress in real time during the test through this interface. At the same time, the system supports users to issue operating instructions to the detection equipment through this interface, such as starting the test, stopping the test, adjusting the test parameters, etc. In this way, remote users can remotely monitor the test process and issue operating instructions as needed to ensure the smooth progress of the test task.

[0115] Step 1073, recording the operating hours and maintenance cycle of the detection equipment, and triggering equipment maintenance reminder.

[0116] In the embodiments of the present application, operating hours: operating hours refer to the cumulative working time of the detection equipment during the test process, which is usually used to evaluate the usage and maintenance needs of the equipment. Maintenance cycle: the maintenance cycle refers to the time interval at which the equipment needs to be maintained or serviced after a certain period of operation, which is usually determined by the equipment manufacturer or the user unit based on the usage of the equipment. Equipment maintenance reminder: equipment maintenance reminder refers to the system automatically triggering a notification to remind the user to perform equipment maintenance based on the operating hours and maintenance cycle of the equipment.

[0117] The system records the operating hours of the testing equipment and automatically calculates the maintenance time of the equipment according to the equipment's maintenance cycle. When the equipment's operating hours reach the maintenance cycle, the system will automatically trigger the equipment maintenance reminder to notify the user to perform equipment maintenance. In this way, the system can ensure that the equipment operates in the best condition and avoid test interruptions or inaccurate data caused by equipment failure.

[0118] Step 1074, count the task completion and resource consumption data of the inspection personnel, and generate a capacity analysis report.

[0119] In the embodiments of the present application, task completion: task completion refers to the number of test tasks completed by the test personnel within a specific time, which is usually used to evaluate the work efficiency of the test personnel. Resource consumption data: resource consumption data refers to the resources consumed by the test personnel during the test process, including time, equipment usage, material consumption, etc. Capacity analysis report: the capacity analysis report refers to the report generated by the system based on the task completion and resource consumption data of the test personnel, which is used to analyze the work efficiency and resource utilization of the test personnel.

[0120] The system counts the task completion and resource consumption data of the inspectors, and generates a capacity analysis report based on these data. Task completion includes the number of test tasks completed by the inspectors within a specific time, and resource consumption data includes the time consumed by the inspectors during the test process, equipment usage, material consumption, etc. The system generates a capacity analysis report by analyzing these data to help managers evaluate the work efficiency and resource utilization of inspectors and optimize the test process and resource allocation.

[0121] The embodiment of the present application realizes comprehensive monitoring and management of the test process. The large visual data screen displays the equipment status and test progress in real time, ensuring that users can understand the test situation in a timely manner; the data interface is opened for remote users to support remote monitoring and the issuance of operation instructions, which improves the flexibility and operability of the system; the operating hours and maintenance cycles of the equipment are recorded, and equipment maintenance reminders are triggered to ensure that the equipment is always in the best condition; the task completion volume and resource consumption data of the inspection personnel are counted, and the capacity analysis report is generated to help optimize resource allocation and improve work efficiency.

[0122] Optionally, the step 106 includes: Step 1061, automatically converting the test report into a certification document according to the format specified by a preset standard.

[0123] In the embodiments of the present application, test report: the test report is a document generated by the automated test system after completing the electromagnetic compatibility test of the vehicle, which contains information such as test results, data analysis, and equipment status. Format specified by preset standards: the format specified by preset standards refers to converting the test report into a file format that meets the certification requirements based on the standards specified by the industry or the country, usually including specific data structures, field requirements, and document layout. Certification document: a certification document refers to a standardized document that is submitted to the relevant certification body or customer to prove that the vehicle's electromagnetic compatibility performance meets specific standards.

[0124] After the system completes the vehicle electromagnetic compatibility test, it will generate a test report. The system automatically converts the test report into a certification file according to the preset standard format. During the conversion process, the system extracts key data from the test report, such as test results, equipment status, test time, etc., and structures these data according to the requirements of the certification file. The system will also automatically fill in the necessary fields in the certification file to ensure that the file meets the requirements of the certification body. After the conversion is completed, the certification file can be submitted to the certification body or customer as proof of the vehicle's electromagnetic compatibility performance.

[0125] Step 1062, import the authentication data into a data analysis platform for clustering and association analysis.

[0126] In the embodiments of the present application, authentication data: authentication data refers to standardized test report data, including the results of the vehicle electromagnetic compatibility test, equipment status, test time and other information. Data analysis platform: the data analysis platform is a system for processing, analyzing and mining data, which can perform operations such as clustering and association analysis on large amounts of data to discover patterns and trends in the data. Clustering and association analysis: clustering analysis is the process of grouping data according to similarity, and association analysis is the process of discovering the association relationship between data.

[0127] The system imports the generated certification data into the data analysis platform. The data analysis platform will perform cluster analysis on the data and group test results with similar characteristics for subsequent analysis and comparison. At the same time, the platform will also perform correlation analysis to find the correlation between different test results, such as how changes in certain test parameters affect the electromagnetic compatibility performance of the vehicle. Through these analyses, the system can identify key patterns and trends in the test data and provide data support for subsequent optimization suggestions.

[0128] Step 1063: Generate a vehicle electromagnetic compatibility optimization suggestion plan based on the data analysis result.

[0129] In an embodiment of the present application, the system automatically generates a vehicle electromagnetic compatibility optimization proposal based on the analysis results generated by the data analysis platform. The system will identify the key factors that affect the electromagnetic compatibility performance of the vehicle and propose corresponding improvement measures. For example, if the data analysis results show that the electromagnetic radiation in a certain frequency range exceeds the standard, the system will recommend adjusting the design or test parameters of the vehicle to reduce electromagnetic radiation. The optimization proposal may include hardware adjustment, software optimization, test process improvement and other aspects. The optimization proposal generated by the system can be directly provided to the OEM to help it improve the electromagnetic compatibility performance of the vehicle.

[0130] Step 1064, establishing a test data sharing channel to support the OEM to retrieve historical test data through the business platform.

[0131] In an embodiment of the present application, the system establishes a test data sharing channel, allowing the OEM to retrieve historical test data through the business platform. The system will provide a dedicated data access interface for each OEM, through which the OEM can query and download historical test data. The data sharing channel supports the export of multiple data formats to ensure that the OEM can easily use this data for further analysis and optimization. Through the data sharing channel, the OEM can view historical test data at any time, understand the changing trend of the vehicle's electromagnetic compatibility performance, and adjust the vehicle design or test process based on this data.

[0132] The embodiment of the present application realizes the complete process from test report generation to data analysis, optimization suggestion generation and data sharing. The system can automatically convert the test report into a certification file to ensure that the file complies with industry standards; cluster and correlate the certification data through the data analysis platform to identify the key factors affecting the electromagnetic compatibility performance of the vehicle; generate optimization suggestions based on the analysis results to help the OEM improve the electromagnetic compatibility performance of the vehicle; finally, the system establishes a test data sharing channel to support the OEM to retrieve historical test data at any time, facilitating its long-term data analysis and optimization.

[0133] Based on the same inventive concept, the embodiment of the present application also provides a vehicle electromagnetic compatibility test device based on a big data platform for implementing the vehicle electromagnetic compatibility test method based on a big data platform. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the vehicle electromagnetic compatibility test device based on a big data platform provided below can refer to the limitations of the vehicle electromagnetic compatibility test method based on a big data platform above, and will not be repeated here.

[0134] In an exemplary embodiment, Figure 5 As shown, a vehicle electromagnetic compatibility test device 20 based on a big data platform is provided, comprising: Configuration module 201, used to create a vehicle electromagnetic compatibility test project and generate a test task in the cloud platform; Connect the testing equipment and the test piece to the cloud platform through the Internet of Things technology, and configure the standardized parameters and hardware connection template of the testing task; Complete the physical connection of the detection system based on the hardware connection template; The test module 202 is used to call the automated test module 202 to execute the standardized test process and collect test data in real time; Analysis module 203, used to perform multi-dimensional analysis and intelligent evaluation on the test data, and generate a test report and certification data; Synchronize the test report and the authentication data to the business platform for secondary data application; Visualization and collaborative management of the test process are carried out through the remote monitoring module.

[0135] Optionally, the configuration module 201 is further used to: Receive the test project application information submitted by the user, wherein the test project application information includes vehicle type, test items and sample quantity; Automatically generate a project contract and a commission form based on the test project application information; Assign project managers and inspectors to the said order; Prioritize the multi-sample testing tasks based on the test item type of the order and the matching degree of laboratory resources; The sorted detection tasks are sent to the corresponding automatic testing system according to preset rules.

[0136] Optionally, the configuration module 201 is further used to: Enter the basic information and communication protocol parameters of the detection equipment; Setting a test frequency range, a calibration mode and a limit line threshold associated with the detection task; Drawing a hardware connection template based on the graphical interface provided by the cloud platform, wherein the hardware connection template includes the physical connection logic of the receiver, the sensor and the device under test; Saving the hardware connection template to a device list and associating it with the detection task; Perform device connectivity verification tests and generate device operation status reports.

[0137] Optionally, the testing module 202 is further configured to: Selecting a standard test mode or a conventional test mode according to the detection task type; In the standard test mode, the preset hardware template, limit line parameters and document template are automatically loaded; In the conventional test mode, the user is allowed to customize and adjust the hardware template and test parameters; the test data curve and annotation information collected from the detection equipment are displayed in real time; Provide the functions of pausing, terminating and warning of abnormal data in the test process; The test data is synchronized to a cloud storage unit.

[0138] Optionally, the analysis module 203 is further used to: Applying a preset algorithm to perform noise filtering and feature extraction on the test data; Comparing the processed data with the limit line threshold to generate a compliance evaluation result; Calculating the electromagnetic compatibility performance score of the vehicle based on the compliance evaluation result; Generate test data trend analysis reports using data mining technology; The test data trend analysis report is associated with a vehicle model database to generate a vehicle model ranking list.

[0139] Optionally, the analysis module 203 is further used to: Deploy a large visual data screen in the cloud platform to display the equipment status and test progress in real time; Open the test process data interface for remote users to support remote monitoring and operation instruction issuance; Record the operating hours and maintenance cycles of the detection equipment and trigger equipment maintenance reminders; Statistics are collected on the task completion and resource consumption data of inspectors, and production capacity analysis reports are generated.

[0140] Optionally, the analysis module 203 is further used to: Automatically convert the test report into a certification document in a format specified by a preset standard; Importing the authentication data into a data analysis platform for clustering and association analysis; Generate a vehicle electromagnetic compatibility optimization suggestion plan based on the data analysis results; Establish a test data sharing channel to support OEMs to retrieve historical test data through the business platform The embodiment of the present application realizes the full process automation of vehicle electromagnetic compatibility testing through the deep integration of cloud platform and Internet of Things technology. The system reduces manual intervention, improves test efficiency, solves the problem of data islands, optimizes vehicle design through intelligent analysis, and the remote collaboration function further supports cross-regional resource sharing, ultimately forming an efficient, accurate and scalable testing system.

[0141] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 6As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store vehicle electromagnetic compatibility test data based on a big data platform. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a vehicle electromagnetic compatibility test method based on a big data platform is implemented.

[0142] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0143] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0144] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0145] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0146] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0147] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0148] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0149] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0150] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A vehicle electromagnetic compatibility test method based on a big data platform, characterized in that: The vehicle electromagnetic compatibility test method based on the big data platform includes: Create vehicle electromagnetic compatibility testing projects and generate testing tasks in the cloud platform; Connect the testing equipment and the test piece to the cloud platform through the Internet of Things technology, and input the basic information and communication protocol parameters of the testing equipment; Setting a test frequency range, a calibration mode and a limit line threshold associated with the detection task; Drawing a hardware connection template based on the graphical interface provided by the cloud platform, wherein the hardware connection template includes the physical connection logic of the receiver, the sensor and the device under test; Saving the hardware connection template to a device list and associating it with the detection task; Perform device connectivity verification tests and generate device operation status reports; Complete the physical connection of the detection system based on the hardware connection template; Call the automated testing module to execute standardized testing procedures and collect test data in real time; Conduct multi-dimensional analysis and intelligent evaluation on the test data to generate test reports and certification data; Synchronize the test report and the authentication data to the business platform for secondary data application; Visualization and collaborative management of the test process are carried out through the remote monitoring module.

2. The vehicle electromagnetic compatibility test method based on the big data platform according to claim 1 is characterized in that: The step of calling the automated testing module to execute the standardized testing process includes: Selecting a standard test mode or a conventional test mode according to the detection task type; In the standard test mode, the preset hardware template, limit line parameters and document template are automatically loaded; In the conventional test mode, the user is allowed to customize and adjust the hardware template and test parameters; the test data curve and annotation information collected from the detection equipment are displayed in real time; Provide the functions of pausing, terminating and warning of abnormal data in the test process; The test data is synchronized to a cloud storage unit.

3. The vehicle electromagnetic compatibility test method based on the big data platform according to claim 1 is characterized in that: The step of performing multi-dimensional analysis and intelligent evaluation on the test data includes: Applying a preset algorithm to perform noise filtering and feature extraction on the test data; Comparing the processed data with the limit line threshold to generate a compliance evaluation result; Calculating the electromagnetic compatibility performance score of the vehicle based on the compliance evaluation result; Generate test data trend analysis reports using data mining technology; The test data trend analysis report is associated with a vehicle model database to generate a vehicle model ranking list.

4. The vehicle electromagnetic compatibility test method based on the big data platform according to claim 1 is characterized in that: The steps of visualizing and collaboratively managing the test process through the remote monitoring module include: Deploy a large visual data screen in the cloud platform to display the equipment status and test progress in real time; Open the test process data interface for remote users to support remote monitoring and operation instruction issuance; Record the operating hours and maintenance cycles of the detection equipment and trigger equipment maintenance reminders; Statistics are collected on the task completion and resource consumption data of inspectors, and production capacity analysis reports are generated.

5. The vehicle electromagnetic compatibility test method based on the big data platform according to claim 1 is characterized in that: The step of synchronizing the test report and the authentication data to the business platform for secondary data application includes: Automatically convert the test report into a certification document in a format specified by a preset standard; Importing the authentication data into a data analysis platform for clustering and association analysis; Generate a vehicle electromagnetic compatibility optimization suggestion plan based on the data analysis results; A test data sharing channel is established to support OEMs to retrieve historical test data through the business platform.

6. A vehicle electromagnetic compatibility test device based on a big data platform, characterized in that: The vehicle electromagnetic compatibility test device based on the big data platform includes: Configuration module, used to create vehicle electromagnetic compatibility testing projects and generate testing tasks in the cloud platform; Connect the testing equipment and the test piece to the cloud platform through the Internet of Things technology, and input the basic information and communication protocol parameters of the testing equipment; Setting the test frequency range, calibration mode and limit line threshold associated with the detection task; Drawing a hardware connection template based on the graphical interface provided by the cloud platform, wherein the hardware connection template includes the physical connection logic of the receiver, the sensor and the device under test; Saving the hardware connection template to a device list and associating it with the detection task; Perform device connectivity verification tests and generate device operation status reports; Complete the physical connection of the detection system based on the hardware connection template; The test module is used to call the automated test module to execute the standardized test process and collect test data in real time; An analysis module, used to perform multi-dimensional analysis and intelligent evaluation on the test data, and generate a test report and certification data; Synchronize the test report and the authentication data to the business platform for secondary data application; Visualization and collaborative management of the test process are carried out through the remote monitoring module.

7. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the vehicle electromagnetic compatibility test method based on a big data platform as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the vehicle electromagnetic compatibility test method based on a big data platform described in any one of claims 1-5 are implemented.

Images