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

Abstract

The present application discloses a vehicle electromagnetic compatibility test method and device based on a big data platform, which relates to the field of vehicle testing technology. The method comprises: creating a vehicle electromagnetic compatibility test project in a cloud platform and generating a test task; connecting the test equipment and the test piece to the cloud platform through the Internet of Things technology, and configuring the standardized parameters and hardware connection template of the test task; completing the physical connection of the test system based on the hardware connection template; calling the automated test module to execute the standardized test process and collect test data in real time; performing multi-dimensional analysis and intelligent evaluation on the test data to generate a test report and certification data; synchronizing the test report and the certification data to the business platform for secondary data application; and visualizing and collaboratively managing the test process through a 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 dramatic 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 in terms of equipment data collection and analysis, and still cannot change the problems of long electromagnetic compatibility test cycles, low efficiency and data silos. 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:

[0006] In a first aspect, the present application provides a vehicle electromagnetic compatibility test method based on a big data platform, comprising:

[0007] Create vehicle electromagnetic compatibility testing projects and generate testing tasks on the cloud platform;

[0008] Connecting the testing equipment and the test piece to the cloud platform via the Internet of Things technology, and configuring the standardized parameters and hardware connection template of the testing task;

[0009] Complete the physical connection of the detection system based on the hardware connection template;

[0010] Call the automated testing module to execute standardized testing processes and collect test data in real time;

[0011] Conduct multi-dimensional analysis and intelligent evaluation of the test data to generate test reports and certification data;

[0012] Synchronize the test report and the certification data to the business platform for secondary data application;

[0013] Visualization and collaborative management of the testing process are achieved through the remote monitoring module.

[0014] Optionally, the step of creating a vehicle electromagnetic compatibility test project and generating a test task in the cloud platform includes:

[0015] Receive the test item application information submitted by the user, wherein the test item application information includes vehicle type, test items and sample quantity;

[0016] Automatically generate a project contract and a commission form based on the test project application information;

[0017] Assign project managers and inspectors to the order;

[0018] Prioritize the multi-sample testing tasks based on the test item type of the order and the matching degree of laboratory resources;

[0019] The sorted detection tasks are sent to the corresponding automated testing system according to preset rules.

[0020] Optionally, the step of configuring standardized parameters of the detection task and a hardware connection template includes:

[0021] Enter the basic information and communication protocol parameters of the detection equipment;

[0022] Setting the test frequency range, calibration mode and limit line threshold associated with the detection task;

[0023] 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, sensor, and device under test;

[0024] Saving the hardware connection template to a device list and associating it with the detection task;

[0025] Perform device connectivity verification tests and generate device operational status reports.

[0026] Optionally, the step of calling the automated testing module to execute the standardized testing process includes:

[0027] Selecting a standard test mode or a conventional test mode according to the type of the detection task;

[0028] In the standard test mode, the preset hardware template, limit line parameters and document template are automatically loaded;

[0029] 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;

[0030] Provides the functions of pausing and terminating the test process and providing warning of data anomalies;

[0031] Synchronize the test data to a cloud storage unit.

[0032] Optionally, the step of performing multi-dimensional analysis and intelligent evaluation on the test data includes:

[0033] Applying a preset algorithm to perform noise filtering and feature extraction on the test data;

[0034] Comparing the processed data with the limit line threshold to generate a compliance evaluation result;

[0035] Calculating a vehicle electromagnetic compatibility performance score based on the compliance evaluation results;

[0036] Generate test data trend analysis reports using data mining technology;

[0037] The test data trend analysis report is associated with a vehicle model database to generate a vehicle model ranking list.

[0038] Optionally, the step of visualizing and collaboratively managing the test process through the remote monitoring module includes:

[0039] Deploy a large visual data screen on the cloud platform to display the equipment status and test progress in real time;

[0040] Open the test process data interface for remote users to support remote monitoring and operation instruction issuance;

[0041] Record the operating hours and maintenance cycles of the testing equipment and trigger equipment maintenance reminders;

[0042] Collect statistics on the task completion and resource consumption data of inspection personnel and generate production capacity analysis reports.

[0043] Optionally, the step of synchronizing the test report and the authentication data to a business platform for secondary data application includes:

[0044] Automatically convert the test report into a certification document in the format specified by the preset standard;

[0045] Importing the authentication data into a data analysis platform for clustering and association analysis;

[0046] Generating a vehicle electromagnetic compatibility optimization proposal based on the data analysis results;

[0047] Establish a test data sharing channel to support OEMs to retrieve historical test data through the business platform.

[0048] In a second aspect, the present application provides a vehicle electromagnetic compatibility test device based on a big data platform, comprising:

[0049] Configuration module, used to create vehicle electromagnetic compatibility testing projects and generate testing tasks in the cloud platform;

[0050] Connecting the testing equipment and the test piece to the cloud platform via the Internet of Things technology, and configuring the standardized parameters and hardware connection template of the testing task;

[0051] Complete the physical connection of the detection system based on the hardware connection template;

[0052] The test module is used to call the automated test module to execute the standardized test process and collect test data in real time;

[0053] An analysis module, used to perform multi-dimensional analysis and intelligent evaluation of the test data, and generate a test report and certification data;

[0054] Synchronize the test report and the certification data to the business platform for secondary data application;

[0055] Visualization and collaborative management of the testing process are achieved through the remote monitoring module.

[0056] Optionally, the configuration module is further configured to:

[0057] Receive the test item application information submitted by the user, wherein the test item application information includes vehicle type, test items and sample quantity;

[0058] Automatically generate a project contract and a commission form based on the test project application information;

[0059] Assign project managers and inspectors to the order;

[0060] Prioritize the multi-sample testing tasks based on the test item type of the order and the matching degree of laboratory resources;

[0061] The sorted detection tasks are sent to the corresponding automated testing system according to preset rules.

[0062] Optionally, the configuration module is further configured to:

[0063] Enter the basic information and communication protocol parameters of the detection equipment;

[0064] Setting the test frequency range, calibration mode and limit line threshold associated with the detection task;

[0065] 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, sensor, and device under test;

[0066] Saving the hardware connection template to a device list and associating it with the detection task;

[0067] Perform device connectivity verification tests and generate device operational status reports.

[0068] Optionally, the testing module is further configured to:

[0069] Selecting a standard test mode or a conventional test mode according to the type of the detection task;

[0070] In the standard test mode, the preset hardware template, limit line parameters and document template are automatically loaded;

[0071] 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;

[0072] Provides the functions of pausing and terminating the test process and providing warning of data anomalies;

[0073] Synchronize the test data to a cloud storage unit.

[0074] Optionally, the analysis module is further configured to:

[0075] Applying a preset algorithm to perform noise filtering and feature extraction on the test data;

[0076] Comparing the processed data with the limit line threshold to generate a compliance evaluation result;

[0077] Calculating a vehicle electromagnetic compatibility performance score based on the compliance evaluation results;

[0078] Generate test data trend analysis reports using data mining technology;

[0079] The test data trend analysis report is associated with a vehicle model database to generate a vehicle model ranking list.

[0080] Optionally, the analysis module is further configured to:

[0081] Deploy a large visual data screen on the cloud platform to display the equipment status and test progress in real time;

[0082] Open the test process data interface for remote users to support remote monitoring and operation instruction issuance;

[0083] Record the operating hours and maintenance cycles of the testing equipment and trigger equipment maintenance reminders;

[0084] Collect statistics on the task completion and resource consumption data of inspection personnel and generate production capacity analysis reports.

[0085] Optionally, the analysis module is further configured to:

[0086] Automatically convert the test report into a certification document in the format specified by the preset standard;

[0087] Importing the authentication data into a data analysis platform for clustering and association analysis;

[0088] Generating a vehicle electromagnetic compatibility optimization proposal based on the data analysis results;

[0089] A test data sharing channel is established to support OEMs in retrieving historical test data through the business platform.

[0090] 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.

[0091] 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.

[0092] 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 one of the above-mentioned vehicle electromagnetic compatibility test methods based on a big data platform.

[0093] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0094] This application provides a vehicle electromagnetic compatibility test method and device based on a big data platform. Through the deep integration of cloud platform and Internet of Things technology, the full process automation of vehicle electromagnetic compatibility test is realized. The system reduces manual intervention, improves test efficiency, solves the problem of data silos, and optimizes vehicle design through intelligent analysis. The remote collaboration function further supports cross-regional resource sharing, ultimately forming an efficient, accurate and scalable testing system. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. 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 creative work.

[0096] Figure 1 A flowchart of a vehicle electromagnetic compatibility test method based on a big data platform provided in one embodiment of the present application;

[0097] Figure 2A system diagram of a vehicle electromagnetic compatibility test method based on a big data platform provided in one embodiment of the present application;

[0098] 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;

[0099] Figure 4 This is a schematic diagram showing the effect of a vehicle electromagnetic compatibility test method based on a big data platform provided in one embodiment of the present application;

[0100] Figure 5 A schematic diagram of the functional modules of a vehicle electromagnetic compatibility test device based on a big data platform provided in one embodiment of the present application;

[0101] Figure 6 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0102] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0103] 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:

[0104] Reference Figure 2 The automated testing system of the embodiment of the present application based on the edge-cloud collaborative architecture with decoupling of software and hardware is a highly intelligent solution. It utilizes cloud resources and automated management tools, and adopts domestic advanced Internet of Things technology to achieve interconnection between various domestic and foreign measuring instrument and equipment 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 data of vehicle electromagnetic compatibility test and certification tests. It has real-time monitoring, data analysis and report generation functions, which greatly improves test efficiency and shortens test cycle, and solves the problems of equipment heterogeneity and data heterogeneity. Figure 1 Evaluate system composition for automated testing.

[0105] Step 101: Create a vehicle electromagnetic compatibility testing project in the cloud platform and generate a testing task.

[0106] In the embodiments of this application, a cloud platform is a resource pooling service platform based on cloud computing technology that provides centralized management and elastic expansion capabilities for computing, storage, network, and other resources. A vehicle electromagnetic compatibility testing project is a test task for vehicle electromagnetic compatibility performance, including testing standards, test items, sample information, and other elements. A testing task is an execution plan generated by the system based on the testing project, including task parameters, execution time, personnel allocation, and so on.

[0107] The system receives user-submitted vehicle EMC testing project applications on the cloud platform, automatically parses the application content (such as vehicle model, manufacturer, and testing standards), and generates a unique project identifier. The system then assigns a project manager based on pre-set rules and automatically generates detailed testing task parameters (such as test items, frequency range, execution standards, and timeframes), marking the task status as "pending."

[0108] Specifically, first apply for the inspection project in the cloud platform, generate the corresponding project contract and order, 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, and the inspection personnel collect the relevant inspection equipment and samples. After receiving the order 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.

[0109] For example, sample information can be found at Figure 3 .

[0110] Step 102: Connect the testing equipment and the device to be tested to the cloud platform via the Internet of Things technology, and configure the standardized parameters and hardware connection template of the testing task.

[0111] In the embodiments of this application, testing equipment refers to instruments used for vehicle electromagnetic compatibility testing (e.g., receivers, antennas, amplifiers, etc.). Device under test refers to the vehicle or component that requires electromagnetic compatibility testing. Internet of Things technology refers to technology that interconnects devices with the cloud through communication protocols (e.g., MQTT, HTTP). Standardized parameters refer to predefined testing parameters (e.g., frequency range, calibration mode, limit lines, etc.). Hardware connection template refers to a graphical configuration template that describes the physical connection between devices.

[0112] The system connects the test equipment (e.g., receiver) and the device under test to the cloud platform via IoT protocols (e.g., Modbus, TCP / IP). It automatically identifies the device model and enters basic information (e.g., IP address, port number). The system then loads pre-stored standardized parameters (e.g., frequency ranges specified in the GB34660-2017 standard) and allows users to edit hardware connection templates (e.g., antenna-to-receiver connection paths) through a graphical interface. Once the template is configured, it is saved to a database for subsequent use.

[0113] Specifically, the test personnel will connect the test equipment and the tested device to the automated test system through the Internet of Things technology. They 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 to the device list of the automated test system. When the user uses this system to draw the hardware connection template diagram, 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.

[0114] The automated testing system supports testing personnel in setting the testing standards, testing frequency, calibration, result reporting and limit lines of the testing items. The automated testing system can set the standards for the testing items, enter relevant standard files, and automatically apply them to subsequent testing processes; the system can set the relevant parameters of the testing frequency and result reporting, and automatically update them to the testing process; the system can set the calibration mode, start frequency, end frequency, step mode and step size. After the settings are 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 settings are completed, the limit line graph can be seen. After the editing is completed, the limit data will be immediately applied to the testing process.

[0115] Step 103: Complete the physical connection of the detection system based on the hardware connection template.

[0116] In this embodiment, the system sends control commands (such as activating the antenna lift mechanism or switching the coaxial cable connection) to the detection device based on the configuration information of the hardware connection template. Simultaneously, the system verifies the compliance of the physical connection (such as cable impedance matching and normal device status) through sensors. If an anomaly is detected, an alarm is triggered and the process is suspended.

[0117] Specifically, hardware connection templates can be drawn within the automated test system and edited in a graphical interface. The edited templates are then applied to the test process. Hardware templates combine the devices selected from the device list, along with the path and frequency information for the test. Each hardware template can include several frequency bands, guiding test personnel in configuring system hardware. The nodes in a hardware template represent instruments such as receivers, sensors such as antennas, the device under test (EUT), or other devices. These are connected via cables such as coaxial cables, GPIB cables, and network cables.

[0118] Step 104: call the automated testing module to execute the standardized testing process and collect test data in real time.

[0119] In the embodiments of this application, the automated test module refers to a pre-defined software program that controls the device to execute test steps. The standardized test process refers to the test sequence (e.g., calibration, scanning, data logging) defined by the test standard. Test data refers to the raw data collected during the test (e.g., radiation intensity, frequency response).

[0120] The system utilizes automated testing modules to execute tests in phases according to a standardized process. The system automatically controls the equipment to perform frequency calibration and generate a correction table. It then traverses test points within a preset frequency range, collecting real-time data. This data is stored in a cloud platform database and synchronized to a visual interface. The system utilizes real-time data streaming technologies (such as WebSocket) to ensure continuous data collection and low latency.

[0121] Specifically, the automated testing system provides two automated testing modes: standard testing and conventional testing. After receiving the project application order, the automated testing system can establish a test task and automatically match the test mode.

[0122] When the test item to be executed is a standard test item, it matches the standard test. 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 use the configured data, and click the test button to perform the test.

[0123] When the user needs to change the relevant parameters or templates of the test items being executed, 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.

[0124] Step 105: Perform multi-dimensional analysis and intelligent evaluation on the test data to generate a test report and certification data.

[0125] In the embodiments of this application, multi-dimensional analysis analyzes data from multiple perspectives, including time, frequency, and space. Intelligent evaluation evaluates test results based on algorithms (e.g., threshold comparison and trend prediction). Test report produces a standard document containing test conclusions and data charts. Certification data formatted to meet industry certification requirements.

[0126] The system performs the following operations on the raw test data: preprocessing, filtering, denoising, and data normalization; analysis, calculating the peak and mean radiation values, and comparing them to limit lines; and evaluation, where the AI ​​model determines whether the device has passed certification and generates a performance ranking. Finally, the system uses the report template engine to automatically generate a PDF test report and package the certification data in JSON or XML format.

[0127] Step 106: Synchronize the test report and the authentication data to the business platform for secondary data application.

[0128] In the embodiments of this application, the business platform is a core system for managing the testing business, supporting functions such as data query and statistics. Secondary data application is the use of test data in other scenarios (such as design optimization and market analysis).

[0129] The system pushes test reports 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 preset secondary analysis tasks (such as generating vehicle electromagnetic compatibility performance rankings).

[0130] Step 107: Visualize and collaboratively manage the test process through the remote monitoring module.

[0131] 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 multiple users to operate and share information simultaneously.

[0132] The system provides the following functions through the remote monitoring module: real-time images and video streams displaying the status of laboratory equipment; a large data screen that dynamically updates test curves and alarm information; and a collaborative interface that supports remote users to access the system through the Web and synchronize operation logs and task progress.

[0133] 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 silos, and optimizes vehicle design through intelligent analysis. The remote collaboration function further supports cross-regional resource sharing, ultimately forming an efficient, accurate and scalable testing system.

[0134] Optionally, step 101 includes:

[0135] Step 1011: Receive the inspection project application information submitted by the user, wherein the inspection project application information includes vehicle type, inspection items and sample quantity.

[0136] In this embodiment of the present application, test project application information refers to the data set submitted by the user to initiate the test task, including key information such as vehicle model, test items, and sample quantity. Vehicle model: The model of the vehicle requiring electromagnetic compatibility testing. Test items: The specific test items (such as radiated emissions, conducted emissions, etc.). Sample quantity: The number of vehicles or components to be tested.

[0137] The system receives test application information through the user interface, parses and verifies the data's integrity and compliance (e.g., whether the vehicle model is on the supported list and whether the test items meet the standards). The system then stores the application information in a database and generates a unique application number for subsequent tracking and management.

[0138] Step 1012: Automatically generate a project contract and a commission form based on the inspection project application information.

[0139] In the embodiments of this application, a project contract is a legal document that specifies the rights and obligations of both parties involved in a testing task. A commission is an execution document that describes the content of the testing task in detail, including task parameters, time points, etc.

[0140] Based on the inspection project application information, the system calls a pre-set contract template, automatically filling in key fields (such as vehicle model, inspection items, sample quantity, and implementation standards), and generates a PDF-formatted project contract. Simultaneously, the system generates a commission form detailing the inspection task execution parameters (such as test frequency range, antenna position, and calibration mode), and associates the contract with the commission form and stores it in the database.

[0141] Step 1013: assign a project manager and inspectors to the order.

[0142] In this embodiment of the present application, the system selects suitable project managers and inspectors from the database based on the inspection item type in the order and the current resource status (such as staff availability and skill matching). The system then updates the order with task assignment information and notifies the relevant personnel via a message queue. Once the assignment is complete, the system marks the order status as "Assigned."

[0143] Step 1014 : Prioritize the multi-sample testing tasks based on the test item type of the order and the matching degree of laboratory resources.

[0144] In the embodiments of this application, the detection item type refers to the specific category of the detection task (e.g., radiated emissions, conducted emissions, etc.). Laboratory resource matching refers to the degree of compatibility between the detection task and laboratory equipment, personnel, and other resources. Priority sorting refers to the order in which multiple detection tasks are executed based on pre-set rules.

[0145] The system analyzes the test item type in the order (e.g., radiated emissions testing requires an antenna with a specific frequency range) and, combined with the real-time status of laboratory resources (e.g., equipment availability and staffing), calculates a compatibility 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.

[0146] Step 1015: Send the sorted detection tasks to the corresponding automated testing system according to preset rules.

[0147] In this embodiment of the present application, the system dispatches testing tasks to the corresponding automated testing system based on the sorting results and preset rules (e.g., prioritizing high-priority tasks and prioritizing low-load labs). During the dispatch process, the system simultaneously transmits task parameters (e.g., hardware connection template, test frequency range) to the target system and updates the task status to "dispatched." Upon receiving the task, the target system automatically initiates the test process.

[0148] Optionally, step 102 includes:

[0149] Step 1021: input basic information and communication protocol parameters of the detection device.

[0150] In this embodiment of the present application, testing equipment refers to the instrument used to perform vehicle electromagnetic compatibility testing (e.g., receiver, antenna, amplifier, etc.). Basic information refers to the basic attributes of the device (e.g., model, name, serial number, etc.). Communication protocol parameters refer to the communication configuration required for the device to interact with the system (e.g., IP address, port number, protocol type, etc.).

[0151] The system receives basic information and communication protocol parameters from the testing device through a user interface or automated interface, verifying the data's integrity and compliance (e.g., whether the IP address format is correct). The system then stores the device information in a database and generates a unique device identifier. Once the communication protocol parameters are configured, the system verifies the connection between the device and the cloud platform using a handshake protocol (e.g., the TCP three-way handshake) to ensure the reliability of subsequent communications.

[0152] Step 1022: Set the test frequency range, calibration mode, and limit line threshold associated with the detection task.

[0153] In this embodiment of the present application, test frequency range refers to the frequency range that needs to be covered in the detection task (e.g., 30MHz-1000MHz). Calibration mode refers to the method of device calibration (e.g., automatic calibration, manual calibration). Limit line threshold refers to the boundary value used to determine whether the test result is qualified (e.g., the upper limit of radiation intensity).

[0154] Based on the requirements of the inspection task, the system loads a preset test frequency range (such as that specified in the GB34660-2017 standard) and allows the user to adjust specific parameters through the user interface. The system then configures the calibration mode (such as the frequency step size for automatic calibration) and limit line thresholds (such as editing limit line data through a table). Once configured, the system stores the parameters in the task configuration file for subsequent testing processes.

[0155] Step 1023: Draw a hardware connection template based on the graphical interface provided by the cloud platform, where the hardware connection template includes the physical connection logic of the receiver, sensor, and device under test.

[0156] In this embodiment of the present application, the system provides drag-and-drop editing via a graphical interface. Users can select receivers, sensors, and DUTs from a device list and draw the connections between them (e.g., connecting a coaxial cable to a receiver and antenna). The system verifies the compliance of the connection logic (e.g., impedance matching, interface type) in real time and dynamically displays the connection status within the interface. Once the drawing is complete, the system generates a graphical representation of the hardware connection template and stores it in a database.

[0157] Step 1024: Save the hardware connection template to the device list and associate it with the detection task.

[0158] In this embodiment of the present application, the system stores the completed hardware connection template in the device list and generates a unique template identifier. The system then associates the template with the inspection task and updates the hardware connection information in the task configuration file. Once the association is complete, the system marks the template status as "Enabled" and simultaneously updates the task status to "Configuration Completed."

[0159] Step 1025: Perform device connectivity verification test and generate a device operation status report.

[0160] In this embodiment, the system invokes automated test scripts to sequentially verify the connectivity of each device. Communication testing verifies the communication status between the device and the system through ping commands or protocol handshakes. Functional testing verifies the device's response by sending control commands (such as activating an antenna lift). Data collection testing simulates the data collection process to verify the integrity and real-time nature of data uploads. Upon completion of the test, the system generates a device status report containing information such as device status, communication latency, and error logs, and stores the report in a database for subsequent review.

[0161] The embodiments of this application ensure efficient execution of testing tasks and accurate data collection through a systematic device configuration and verification process. This system reduces manual intervention, improves configuration efficiency, and ensures device reliability through connectivity verification testing. Graphical editing and automated verification of hardware connection templates further optimize the testing process, ultimately forming an efficient, accurate, and scalable testing task execution system.

[0162] Optionally, step 104 includes:

[0163] Step 1041 : Select a standard test mode or a regular test mode according to the detection task type.

[0164] In the embodiments of this application, the detection task type is the classification of the detection task (such as standard detection items and custom detection items). Standard test mode is an automated test process executed according to preset standards without user intervention. Conventional test mode is a flexible test mode that allows users to customize test parameters and processes.

[0165] The system automatically selects a test mode based on the task type: if the task is a standard test (such as the GB34660-2017 vehicle electromagnetic radiation emission test), the system selects the standard test mode; if the task is a custom test (such as testing within a user-specified frequency range), the system selects the conventional test mode. Once selected, the system updates the test mode identifier in the task configuration file and prepares to load the corresponding test parameters and templates.

[0166] Step 1042: In the standard test mode, automatically load the preset hardware template, limit line parameters, and document template.

[0167] In the embodiments of this application, a hardware template is a graphical configuration template that describes the physical connection relationship between devices. A limit line parameter is a boundary value (such as the upper limit of radiation intensity) that determines whether a test result is qualified. A document template is a standard format template for generating a test report.

[0168] 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 connections between the receiver, antenna, and other devices; the limit line parameters load the preset frequency range and radiation intensity thresholds; and 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."

[0169] Step 1043: In the conventional test mode, the user is allowed to customize the hardware template and test parameters, and display the test data curve and annotation information collected from the detection equipment in real time.

[0170] In the embodiments of this application, custom adjustments allow users to modify hardware connections or test parameters as needed. Test data curves graphically display data collected from the test equipment (e.g., a curve showing how radiation intensity changes over frequency). Annotations mark key points on the data curve (e.g., peak values, limit values).

[0171] In regular test mode, the system provides a user interface for adjusting hardware templates (e.g., modifying antenna connection paths) and test parameters (e.g., changing frequency ranges and step sizes). Once adjustments are complete, the system displays the test data curve collected from the test equipment in real time, annotating key points (e.g., peak frequencies and limit values) on the curve. A dynamic refresh mechanism ensures the real-time and accuracy of the curve and annotation information.

[0172] Step 1044 provides the functions of pausing, terminating and warning of data anomalies in the test process.

[0173] In this embodiment of the present application, the system provides the following control functions during the test process: pause, which allows the user to pause the test process through the interface, and the system saves the current test status (such as frequency points and collected data); terminate, which allows the user to terminate the test process through the interface, and the system clears the current status and releases device resources; and data anomaly warning, which monitors test data in real time. If limit thresholds are exceeded or abnormal fluctuations occur, an alarm is triggered and the user is notified. The system logs all operations and warning events for subsequent analysis and review.

[0174] Step 1045: Synchronize the test data to a cloud storage unit.

[0175] In this embodiment of the present application, during the test process, the system synchronizes collected test data (e.g., frequency points and radiation intensity values) to a cloud storage unit in real time via an encrypted transmission protocol (e.g., HTTPS). After synchronization is complete, the system verifies the integrity and consistency of the data and updates the task status to "Data Synchronized." The cloud storage unit then categorizes and stores the data (e.g., by task ID and timestamp) and triggers subsequent data analysis and report generation processes.

[0176] The embodiments of this application flexibly switch between standard and conventional test modes to meet the needs of different testing tasks. The system provides real-time data display and process control, ensuring controllability and transparency of the testing process. Data synchronization and anomaly warning mechanisms further guarantee 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.

[0177] Optionally, step 105 includes:

[0178] Step 1051: Apply a preset algorithm to perform noise filtering and feature extraction on the test data.

[0179] In this embodiment, the system first processes the test data using a pre-set noise filtering algorithm to remove noise and interference, ensuring data accuracy and reliability. Next, the system uses a feature extraction algorithm to extract key features from the filtered data. These features reflect the core indicators of the vehicle's electromagnetic compatibility performance. This step provides a high-quality data foundation for subsequent analysis.

[0180] Step 1052: Compare the processed data with the limit line threshold to generate a compliance evaluation result.

[0181] In this embodiment of the present application, "limit line thresholds" refer to pre-set EMC performance qualification standards or boundary values. Test data must meet these thresholds to be considered compliant. "Compliance evaluation results" refer to the system's conclusion on whether a vehicle's EMC performance complies with standards, based on a comparison of test data with the limit line thresholds.

[0182] The system compares the test data, after noise filtering and feature extraction, with the preset limit line threshold. The system calculates the difference between the test data and the threshold to determine whether the data is within the permitted range. If the data meets the threshold, the system generates a compliance evaluation result of "pass." If the data exceeds the threshold, the system generates a "fail" evaluation result. This step ensures the objectivity and accuracy of the test results.

[0183] Step 1053: Calculate the vehicle electromagnetic compatibility performance score based on the compliance evaluation result.

[0184] In the embodiments of this application, the electromagnetic compatibility performance score refers to a quantitative indicator of the vehicle's electromagnetic compatibility performance calculated by the system based on the compliance evaluation results using certain scoring rules. A higher score indicates better electromagnetic compatibility performance of the vehicle.

[0185] The system calculates the vehicle's EMC performance score based on the compliance evaluation results and pre-set scoring rules. The score is calculated based on factors such as the test data's proximity to the limit threshold and data stability. This step provides a quantitative evaluation standard for vehicle EMC performance, facilitating subsequent ranking and optimization.

[0186] Step 1054: Generate a test data trend analysis report using data mining technology.

[0187] In the embodiments of this application, data mining technology refers to the use of algorithms to extract useful information from large amounts of data, typically used to discover patterns, trends, and relationships within the data. Trend analysis reports: Trend analysis reports are reports on data trends generated by the system through analysis of historical and current data. These reports are used to predict future data trends or identify issues.

[0188] The system uses data mining techniques to conduct in-depth analysis of test data, extracting trends and patterns. By analyzing historical and current data, the system generates a trend analysis report. This report demonstrates the changing trends of a vehicle's electromagnetic compatibility performance, helping users understand long-term performance and potential issues.

[0189] Step 1055: Associate the test data trend analysis report with the vehicle model database to generate a vehicle model ranking list.

[0190] In the embodiments of this application, the vehicle model database refers to a database that stores information about different vehicle models, typically including basic information such as the model name, model, and year of production. The vehicle model ranking list refers to a list in which the system sorts vehicle models based on their electromagnetic compatibility scores, with models with higher scores ranking higher.

[0191] The system links the generated test data trend analysis report with the vehicle model database and, combined with the vehicle's electromagnetic compatibility performance score, generates a model ranking list. The system sorts the models by score, with higher-scoring models ranking higher. This step provides users with an intuitive vehicle performance comparison tool, making it easier for them to select the model with the best performance.

[0192] The embodiments of this application can perform a series of processing on vehicle EMC test data, including noise filtering, feature extraction, compliance evaluation, performance scoring, trend analysis, and vehicle model ranking. These steps work together to ensure the accuracy and reliability of test data, provide quantitative evaluation criteria for vehicle EMC performance, and generate trend analysis and vehicle model ranking reports. Ultimately, the system can help users fully understand the EMC performance of their vehicles, optimize vehicle design, improve testing efficiency, and provide data support for decision-making.

[0193] Optionally, step 107 includes:

[0194] Step 1071: deploy a large visual data screen in the cloud platform to display the device status and test progress in real time.

[0195] In the embodiment 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 for real-time monitoring and display of key information such as device status and test progress. It can present complex data in an intuitive manner, making it easy for users to quickly understand the operation of the current system. Device status: The device status refers to the operating status of the detection device during the test process, including the device's switch status, working mode, fault information, etc. 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.

[0196] The system deploys a large, visual data screen on the cloud platform, displaying device status and test progress in real time. The system collects data from various test devices and displays this data on the screen through a graphical interface. Device status information includes operational status and fault alarms, while test progress information includes the completion status of the current test task and the remaining test time. Through the visual data screen, users can monitor the test process in real time and promptly identify and address any anomalies.

[0197] Step 1072, open the test process data interface for remote users to support remote monitoring and operation instruction issuance.

[0198] In an embodiment of the present application, the system provides a data interface for remote users to monitor the test process, allowing them to access the system remotely via the network. This interface allows users to view data such as device status and test progress in real time during the test. Furthermore, the system supports users issuing operational instructions to the testing equipment through this interface, such as starting and stopping a test, adjusting test parameters, and so on. In this way, remote users can remotely monitor the test process and issue operational instructions as needed to ensure the smooth progress of the test task.

[0199] Step 1073: Record the operating hours and maintenance cycle of the detection equipment, and trigger an equipment maintenance reminder.

[0200] 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 between the time when the equipment needs to be maintained or serviced after a certain period of operation, which is usually determined by the equipment manufacturer or 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 equipment's operating hours and maintenance cycle.

[0201] The system records the operating hours of testing equipment and automatically calculates maintenance time based on the equipment's maintenance cycle. When the equipment's operating hours reach the maintenance period, the system automatically triggers a maintenance reminder, notifying the user to perform maintenance and servicing. This ensures that the equipment operates in optimal condition, avoiding test interruptions or inaccurate data caused by equipment failure.

[0202] Step 1074: Count the task completion and resource consumption data of the inspection personnel and generate a production capacity analysis report.

[0203] In the embodiments of the present application, task completion volume: task completion volume 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 a report generated by the system based on the task completion volume and resource consumption data of the test personnel, which is used to analyze the work efficiency and resource utilization of the test personnel.

[0204] The system collects data on task completion and resource consumption by testers and generates capacity analysis reports based on this data. Task completion includes the number of test tasks completed by testers within a specific timeframe, while resource consumption includes time spent, equipment usage, and material consumption during the testing process. By analyzing this data and generating capacity analysis reports, the system helps managers assess tester efficiency and resource utilization, optimizing testing processes and resource allocation.

[0205] The embodiments of this application achieve comprehensive monitoring and management of the test process. A large visual data screen displays the equipment status and test progress in real time, ensuring that users can understand the test status in a timely manner. A data interface is opened for remote users to support remote monitoring and the issuance of operation instructions, improving the flexibility and operability of the system. The equipment's operating hours and maintenance cycles are recorded, triggering equipment maintenance reminders to ensure that the equipment is always in optimal condition. The task completion and resource consumption data of the test personnel are counted, and a production capacity analysis report is generated to help optimize resource allocation and improve work efficiency.

[0206] Optionally, step 106 includes:

[0207] Step 1061: Automatically convert the test report into a certification document according to the format specified by the preset standard.

[0208] In the embodiment of the present application, test report: The test report is a document generated by the automated test system after completing the vehicle electromagnetic compatibility test, which contains information such as test results, data analysis, and equipment status. The format specified by the preset standard: The format specified by the preset standard 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.

[0209] After completing the vehicle's EMC test, the system generates a test report. The system automatically converts the test report into a certification document based on a pre-set standard format. During the conversion process, the system extracts key data from the test report, such as test results, equipment status, and test time, and structures this data according to the requirements of the certification document. The system also automatically populates the necessary fields in the certification document to ensure that it meets the requirements of the certification body. Once converted, the certification document can be submitted to the certification body or client as proof of the vehicle's EMC performance.

[0210] Step 1062: Import the authentication data into a data analysis platform for clustering and association analysis.

[0211] In the embodiments of the present application, certification data refers to standardized test report data, including information such as the results of the vehicle's electromagnetic compatibility test, equipment status, and test time. Data analysis platform: The data analysis platform is a system for processing, analyzing, and mining data. It is capable of performing operations such as clustering and association analysis on large amounts of data to discover patterns and trends in the data. Clustering and association analysis: Cluster analysis is the process of grouping data according to similarity, and association analysis is the process of discovering associations between data.

[0212] The system imports the generated certification data into the data analysis platform. The platform then performs cluster analysis on this data, grouping test results with similar characteristics for easier analysis and comparison. The platform also conducts correlation analysis to identify relationships between different test results, such as how changes in certain test parameters affect a vehicle's electromagnetic compatibility performance. Through these analyses, the system can identify key patterns and trends in the test data, providing data support for subsequent optimization recommendations.

[0213] Step 1063: Generate a vehicle electromagnetic compatibility optimization proposal based on the data analysis results.

[0214] 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 affecting 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 can include hardware adjustments, software optimization, test process improvements 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.

[0215] Step 1064: Establish a test data sharing channel to support the OEM to retrieve historical test data through the business platform.

[0216] In an embodiment of the present application, the system establishes a test data sharing channel, allowing OEMs to access historical test data through the business platform. The system provides each OEM with a dedicated data access interface, through which the OEM can query and download historical test data. The data sharing channel supports exporting data in multiple formats, ensuring that OEMs can easily use this data for further analysis and optimization. Through the data sharing channel, OEMs can view historical test data at any time, understand the changing trends of the vehicle's electromagnetic compatibility performance, and adjust vehicle design or testing processes based on this data.

[0217] This embodiment of the application implements a complete process from test report generation to data analysis, optimization suggestion generation, and data sharing. The system automatically converts test reports into certification documents, ensuring compliance with industry standards. The data analysis platform performs clustering and correlation analysis on certification data to identify key factors affecting vehicle electromagnetic compatibility (EMC) performance. Based on the analysis results, optimization suggestions are generated to help OEMs improve vehicle EMC performance. Finally, the system establishes a test data sharing channel, allowing OEMs to access historical test data at any time, facilitating long-term data analysis and optimization.

[0218] Based on the same inventive concept, embodiments of the present application also provide a vehicle electromagnetic compatibility test device based on a big data platform for implementing the aforementioned vehicle electromagnetic compatibility test method based on a big data platform. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the vehicle electromagnetic compatibility test device based on a big data platform provided below can be found in the above-mentioned limitations of the vehicle electromagnetic compatibility test method based on a big data platform, and will not be repeated here.

[0219] In an exemplary embodiment, Figure 5 As shown, a vehicle electromagnetic compatibility test device 20 based on a big data platform is provided, comprising:

[0220] Configuration module 201, used to create a vehicle electromagnetic compatibility test project and generate a test task in the cloud platform;

[0221] Connecting the testing equipment and the test piece to the cloud platform via the Internet of Things technology, and configuring the standardized parameters and hardware connection template of the testing task;

[0222] Complete the physical connection of the detection system based on the hardware connection template;

[0223] 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;

[0224] Analysis module 203, used to perform multi-dimensional analysis and intelligent evaluation on the test data, and generate a test report and certification data;

[0225] Synchronize the test report and the certification data to the business platform for secondary data application;

[0226] Visualization and collaborative management of the testing process are achieved through the remote monitoring module.

[0227] Optionally, the configuration module 201 is further configured to:

[0228] Receive the test item application information submitted by the user, wherein the test item application information includes vehicle type, test items and sample quantity;

[0229] Automatically generate a project contract and a commission form based on the test project application information;

[0230] Assign project managers and inspectors to the order;

[0231] Prioritize the multi-sample testing tasks based on the test item type of the order and the matching degree of laboratory resources;

[0232] The sorted detection tasks are sent to the corresponding automated testing system according to preset rules.

[0233] Optionally, the configuration module 201 is further configured to:

[0234] Enter the basic information and communication protocol parameters of the detection equipment;

[0235] Setting the test frequency range, calibration mode and limit line threshold associated with the detection task;

[0236] 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, sensor, and device under test;

[0237] Saving the hardware connection template to a device list and associating it with the detection task;

[0238] Perform device connectivity verification tests and generate device operational status reports.

[0239] Optionally, the testing module 202 is further configured to:

[0240] Selecting a standard test mode or a conventional test mode according to the type of the detection task;

[0241] In the standard test mode, the preset hardware template, limit line parameters and document template are automatically loaded;

[0242] 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;

[0243] Provides the functions of pausing and terminating the test process and providing warning of data anomalies;

[0244] Synchronize the test data to a cloud storage unit.

[0245] Optionally, the analysis module 203 is further configured to:

[0246] Applying a preset algorithm to perform noise filtering and feature extraction on the test data;

[0247] Comparing the processed data with the limit line threshold to generate a compliance evaluation result;

[0248] Calculating a vehicle electromagnetic compatibility performance score based on the compliance evaluation results;

[0249] Generate test data trend analysis reports using data mining technology;

[0250] The test data trend analysis report is associated with a vehicle model database to generate a vehicle model ranking list.

[0251] Optionally, the analysis module 203 is further configured to:

[0252] Deploy a large visual data screen on the cloud platform to display the equipment status and test progress in real time;

[0253] Open the test process data interface for remote users to support remote monitoring and operation instruction issuance;

[0254] Record the operating hours and maintenance cycles of the testing equipment and trigger equipment maintenance reminders;

[0255] Collect statistics on the task completion and resource consumption data of inspection personnel and generate production capacity analysis reports.

[0256] Optionally, the analysis module 203 is further configured to:

[0257] Automatically convert the test report into a certification document in the format specified by the preset standard;

[0258] Importing the authentication data into a data analysis platform for clustering and association analysis;

[0259] Generating a vehicle electromagnetic compatibility optimization proposal based on the data analysis results;

[0260] Establish a test data sharing channel to support OEMs to retrieve historical test data through the business platform

[0261] 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 silos, and optimizes vehicle design through intelligent analysis. The remote collaboration function further supports cross-regional resource sharing, ultimately forming an efficient, accurate and scalable testing system.

[0262] 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 6 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. 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 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.

[0263] 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 shown in the figure, or combine certain components, or have a different component arrangement.

[0264] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0265] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0266] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0267] 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.

[0268] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. 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 above-mentioned embodiments. In particular, any reference to memory, database, or other media 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), magnetic 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).

[0269] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0270] The technical features of the above embodiments can be combined arbitrarily. 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.

[0271] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may 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 on 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, sensor, and 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 processes and collect test data in real time; Conduct multi-dimensional analysis and intelligent evaluation of the test data to generate test reports and certification data; Synchronize the test report and the certification data to the business platform for secondary data application; Visualization and collaborative management of the testing process are achieved through the remote monitoring module.

2. The vehicle electromagnetic compatibility test method based on a 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 type of the detection task; 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; Provides the functions of pausing and terminating the test process and providing warning of data anomalies; Synchronize the test data to a cloud storage unit.

3. The vehicle electromagnetic compatibility test method based on a 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 a vehicle electromagnetic compatibility performance score based on the compliance evaluation results; 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 a 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 on 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 testing equipment and trigger equipment maintenance reminders; Collect statistics on the task completion and resource consumption data of inspection personnel and generate production capacity analysis reports.

5. The vehicle electromagnetic compatibility test method based on a 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 the format specified by the preset standard; Importing the authentication data into a data analysis platform for clustering and association analysis; Generating a vehicle electromagnetic compatibility optimization proposal based on the data analysis results; A test data sharing channel is established to support OEMs in retrieving 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, sensor, and 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 of the test data, and generate a test report and certification data; Synchronize the test report and the certification data to the business platform for secondary data application; Visualization and collaborative management of the testing process are achieved 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, characterized in that the processor executes the computer program to implement the steps of the vehicle electromagnetic compatibility test method based on a big data platform according to 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 to 5 are implemented.

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