A method, system, medium and product for simulating electromagnetic environment of display module

Abstract

A method, system, medium and product for simulating the electromagnetic environment of a display module, which relates to the field of electromagnetic variable measurement. The method includes: receiving a test identification code input by a user, extracting multiple target scenes corresponding to the test identification code from a preset scene library, and generating a scene change sequence; determining a combination of radio frequency interference sources and mechanical vibration parameters corresponding to the target scene; setting test parameters for test time periods corresponding to multiple target scenes, and generating a dynamic test sequence; receiving key test scenes marked by a user, adjusting the test time periods and test parameters corresponding to the key test scenes, and obtaining a target test sequence; simulating the electromagnetic environment of a target display module, and recording the simulated test parameters of the target display module; the simulated test parameters include display brightness, contrast and response time; and determining an electromagnetic compatibility evaluation result based on the target test sequence and the simulated test parameters. The implementation of this application can improve the accuracy of the electromagnetic compatibility test results.

Description

Technical Field

[0001] The present application relates to the field of electromagnetic variable measurement, and in particular to a method, system, medium and product for simulating the electromagnetic environment of a display module. Background Art

[0002] With the rapid development of mobile medical technology, medical display modules need to work stably in a variety of mobile scenarios such as ambulances and helicopters. In such scenarios, there are multiple electromagnetic interference sources from medical equipment, communication equipment, vehicle systems, etc., accompanied by drastic environmental changes and mechanical vibrations, which pose severe challenges to the electromagnetic compatibility of display modules.

[0003] At present, the electromagnetic environment test of mobile medical display modules mainly adopts the standard laboratory method. This method arranges a single radio frequency source in an electromagnetic darkroom and performs electromagnetic compatibility test on the display module by adjusting the frequency and power of the signal generator. During the test, according to the pre-set test specifications, the display module is scanned point by point at a fixed frequency interval and time interval, and the performance indicators of the display module at each test point are recorded.

[0004] However, in actual application scenarios, when an ambulance is traveling at high speed or a helicopter is taking off and landing, the display module will be subjected to the superposition effect of multiple electromagnetic interference sources and strong mechanical vibrations; there is a large difference between the actual use environment and the test environment, and the electromagnetic environment simulation method of related technologies is difficult to obtain accurate and actual test results. Summary of the invention

[0005] The present application provides an electromagnetic environment simulation method, system, medium and product for a display module, which are used to improve the accuracy of electromagnetic compatibility test results.

[0006] In the first aspect, the present application provides an electromagnetic environment simulation method for a display module, which is applied to an electromagnetic simulation system, and the method includes: receiving a test identification code input by a user, extracting multiple target scenes corresponding to the test identification code from a preset scene library, and generating a scene change sequence; according to the multiple target scenes in the scene change sequence, determining the RF interference source combination and mechanical vibration parameters corresponding to the target scene; the RF interference source combination includes multiple simulated RF sources; the simulated RF source includes a medical device RF source, a communication device RF source, and a vehicle system RF source; based on the multiple RF interference source combinations and multiple mechanical vibration parameters corresponding to the multiple target scenes, setting test parameters for test time periods corresponding to the multiple target scenes, and generating a dynamic test sequence; receiving key test scenes marked by the user, adjusting the test time periods and test parameters corresponding to the key test scenes in the dynamic test sequence, and obtaining a target test sequence; simulating the electromagnetic environment of the target display module based on the target test sequence, and recording the simulated test parameters of the target display module; the simulated test parameters include display brightness, contrast, and response time; determining the electromagnetic compatibility assessment result based on the target test sequence and the simulated test parameters.

[0007] In the above embodiment, the electromagnetic simulation system receives the test identification code and extracts the corresponding scene from the preset scene library, generates a dynamic test sequence by combining the RF interference source combination and the mechanical vibration parameters, and then adjusts the test parameters according to the key scenes marked by the user, thereby realizing the simulation of the actual working environment, making the electromagnetic interference evaluation of the display module more accurate, avoiding the problem of large differences between the traditional single RF source testing method and the actual use environment, and improving the accuracy of the test results.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the steps of receiving key test scenarios marked by users, adjusting the test time periods and test parameters corresponding to the key test scenarios in the dynamic test sequence, and obtaining the target test sequence specifically include: obtaining user rating marks for multiple target scenarios in the dynamic test sequence, and determining the target scenarios whose rating levels are higher than a preset level threshold as key test scenarios; calculating the optimal test duration and test parameter adjustment coefficients for the key test scenarios based on historical test data; extending or shortening the test time period corresponding to the key test scenarios in the dynamic test sequence according to the optimal test duration to obtain the optimized test time; adjusting the combined output power and mechanical vibration parameters of the RF interference source of the key test scenario according to the test parameter adjustment coefficient to obtain the optimized test parameters; and determining the target test sequence based on the dynamic test sequence, the optimized test time, and the optimized test parameters.

[0009] In the above embodiment, the electromagnetic simulation system identifies key test scenarios through user rating tags, and calculates the optimal test duration and parameter adjustment coefficients based on historical test data, thereby achieving optimal allocation of test resources and focused verification of key scenarios, thereby improving test efficiency and reliability.

[0010] In combination with some embodiments of the first aspect, in some embodiments, the steps of calculating the optimal test duration and test parameter adjustment coefficient of key test scenarios based on historical test data specifically include: performing cluster analysis on the historical test data, classifying the scenarios whose data similarity between electromagnetic environment characteristics and test results is higher than a preset similarity threshold into test scenario clusters, and calculating the feature vector of the test scenario cluster; mapping the feature vector to a multidimensional feature space, calculating the scene similarity between the key test scenario and each test scenario cluster; determining the target scene cluster with the highest scene similarity, extracting the historical test data in the target scene cluster as optimization reference data, and determining the optimal test duration and test parameter adjustment coefficient.

[0011] In the above embodiment, the electromagnetic simulation system optimizes the optimal parameters of key test scenarios by performing cluster analysis on historical test data and calculating scene similarity in a multi-dimensional feature space, utilizing historical test experience to improve the accuracy and efficiency of parameter optimization.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the step of mapping the feature vector to a multidimensional feature space and calculating the scene similarity between the key test scene and each test scene cluster specifically includes: constructing an N-dimensional feature space, and mapping the feature vector to a feature point in the N-dimensional feature space; the coordinate axes of the N-dimensional feature space correspond to the radio frequency signal strength, frequency distribution, vibration amplitude, ambient temperature and electromagnetic field strength, respectively; based on the kernel density estimation method, calculating the Mahalanobis distance between the feature point and the center point of each test scene cluster, and converting the Mahalanobis distance into a similarity score; dynamically adjusting the weight of the test scene cluster, and determining the weight coefficient of each test scene cluster according to the confidence of the historical test data; and calculating the scene similarity between the key test scene and each test scene cluster based on the similarity score and the weight coefficient.

[0013] In the above embodiment, the electromagnetic simulation system achieves accurate matching and similarity evaluation of the test scenes by constructing an N-dimensional feature space and using a kernel density estimation method to calculate similarity, combined with a dynamic weight adjustment mechanism, thereby improving the accuracy of scene matching.

[0014] In combination with some embodiments of the first aspect, in some embodiments, the step of determining the electromagnetic compatibility assessment result based on the target test sequence and the simulation test parameters specifically includes: determining the dynamic response data of the target display module based on the simulation test parameters; the dynamic response data includes a display brightness fluctuation curve, a contrast change curve and a response time distribution; performing time-frequency domain analysis on the dynamic response data to extract multiple feature parameters; determining a preset scoring rule based on the target test sequence; calculating the feature score of each feature parameter based on the preset scoring rule, and weightedly calculating the feature score to obtain a comprehensive evaluation score; and grading the electromagnetic compatibility performance of the target display module according to the comprehensive evaluation score to obtain an electromagnetic compatibility assessment result.

[0015] In the above embodiment, the electromagnetic simulation system performs time-frequency domain analysis on the dynamic response data and conducts comprehensive evaluation in combination with preset scoring rules, thereby achieving an objective quantitative evaluation of the electromagnetic compatibility performance of the display module and improving the comparability and reliability of the evaluation results.

[0016] In combination with some embodiments of the first aspect, in some embodiments, before receiving a test identification code input by a user, extracting multiple target scenes corresponding to the test identification code from a preset scene library, and generating a scene change sequence, the method also includes: real-time collection of spatial electromagnetic field distribution data in multiple mobile medical scenes, vibration information during equipment operation, and radio frequency signal characteristics of multiple radio frequency interference sources; performing time synchronization and spatial alignment processing on the spatial electromagnetic field distribution data, vibration information, and radio frequency signal characteristics to obtain measured standard data; based on the measured standard data, establishing a scene feature model including the location of the electromagnetic interference source, signal characteristics, and environmental parameters; and storing the scene feature model in association with the scene identification code to generate a preset scene library.

[0017] In the above embodiment, the electromagnetic simulation system collects electromagnetic environment data of multiple mobile medical scenarios in real time and performs time-space synchronization processing to establish a complete scenario feature model library, thereby improving the authenticity and accuracy of the simulation test.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after the step of simulating the electromagnetic environment of the target display module based on the target test sequence and recording the simulation test parameters of the target display module, the method also includes: when it is detected that the fluctuation value of the simulation test parameter is greater than the preset normal threshold, extracting the electromagnetic field distribution data and mechanical vibration data of the fluctuation time period; determining the triggering condition of the fluctuation according to the electromagnetic field distribution data and mechanical vibration data of the fluctuation time period; the triggering condition includes the RF source combination, vibration frequency and environmental parameters; screening out historical abnormal scenes corresponding to the triggering conditions from the preset scene library, and extracting the protection measures and optimization schemes corresponding to the historical abnormal scenes; based on the protection measures and optimization schemes, adjusting the test parameters of the fluctuation time period in the target test sequence, and re-executing the electromagnetic environment simulation test.

[0019] In the above embodiment, the electromagnetic simulation system realizes real-time optimization of the test process and rapid problem solving by real-time monitoring of fluctuations in simulation test parameters, analyzing the triggering conditions of abnormal fluctuations, and providing optimization solutions based on historical abnormal scenarios, thereby improving the reliability and efficiency of the test.

[0020] In a second aspect, an embodiment of the present application provides an electromagnetic simulation system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the electromagnetic simulation system to perform the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when the computer program product is run on an electromagnetic simulation system, enables the electromagnetic simulation system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on an electromagnetic simulation system, enable the electromagnetic simulation system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] It can be understood that the electromagnetic simulation system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0025] 1. Due to the use of a dynamic test sequence generation method based on a preset scenario library and user tags, combined with the joint simulation technology of multi-source RF interference and mechanical vibration, it can accurately restore the complex electromagnetic environment faced by the display module in the actual application environment, effectively solving the problem in the existing technology that a single RF source test cannot simulate the actual use scenario and there is a large deviation between the test results and the actual application, thereby realizing the accurate evaluation and reliable verification of the electromagnetic compatibility performance of the display module.

[0026] 2. Due to the adoption of N-dimensional feature space mapping and kernel density estimation scene similarity calculation method, and the introduction of dynamic weight adjustment mechanism based on historical data confidence, it is possible to accurately characterize and match the characteristics of the test scene from multiple dimensions, effectively solving the problems of low scene matching accuracy and inaccurate similarity assessment in the existing technology, and thus realizing accurate identification of test scenes and automatic recommendation of optimal parameters.

[0027] 3. Due to the use of multi-scenario real-time data acquisition and time-space synchronous registration processing technology, and the establishment of a scene feature model that includes the location of the electromagnetic interference source, signal characteristics and environmental parameters, it is possible to comprehensively and accurately obtain and save the electromagnetic feature data of the actual application environment, effectively solving the problem of large differences between the test scene data and the actual environment in the existing technology, and thus realizing the precise construction and continuous optimization of the test scene library. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a flow chart of the electromagnetic environment simulation method of the display module in the embodiment of the present application;

[0029] Figure 2 is another flow chart of the electromagnetic environment simulation method of the display module in the embodiment of the present application;

[0030] Figure 3 It is a schematic diagram of the structure of a physical device of the electromagnetic simulation system in the embodiment of the present application. DETAILED DESCRIPTION

[0031] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0032] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0033] For ease of understanding, the application scenarios of the embodiments of the present application are introduced below.

[0034] The emergency center of a tertiary hospital is equipped with multiple high-definition medical displays, which are used to display the patient's vital signs in real time during the ambulance transfer process. During the transfer of a critically ill patient, when the ambulance was driving at high speed, the display was subject to multiple electromagnetic interferences from on-board equipment, medical equipment and communication equipment, coupled with the violent vibration caused by road bumps, resulting in abnormal phenomena such as flickering and distortion on the display screen, affecting the medical staff's judgment of the patient's condition. Similar situations are more serious during helicopter transfers. The display module needs to deal with complex environmental factors such as engine vibration, communication equipment interference and airflow turbulence at the same time. Mobile medical display modules have reliability issues in complex electromagnetic environments.

[0035] In the related art, the electromagnetic compatibility of the display module can be verified by using a single RF source test method and a fixed parameter scanning method. Specifically, a signal generator is used in an electromagnetic darkroom to generate a single frequency RF signal, and the test is performed at a preset frequency interval and a fixed time interval, and the performance indicators of the display module at each test point are recorded. The following introduces the scenario of using the electromagnetic environment simulation method of the display module in the related art.

[0036] A medical device manufacturer uses traditional laboratory testing methods to verify the electromagnetic compatibility of display modules. Testers set up a single RF source in an electromagnetic darkroom and scan point by point at fixed frequency intervals, with each test point maintaining the same test duration. For example, a signal generator is used to generate a 900MHz RF signal, which is scanned to 2.4GHz in steps of 20MHz, and each frequency point is tested for 3 minutes. However, when the display module was actually installed on an ambulance for use, it was found that the test results were significantly different from the actual situation. The reason is that laboratory testing cannot simulate the superposition effect of multiple interference sources, nor does it take into account the impact of mechanical vibration, resulting in a lack of practical reference value for the test results.

[0037] The electromagnetic environment simulation method of the display module in the embodiment of the present application is used to establish a scene library by real-time acquisition of real environment data, and combined with the joint simulation of multiple RF source combinations and mechanical vibration parameters, to achieve accurate restoration of complex electromagnetic environments, which can not only accurately evaluate the performance of the display module in the actual application environment, but also dynamically optimize the test parameters according to abnormal conditions during the test. The following introduces the scenarios in which the electromagnetic environment simulation method of the display module in the present application is used.

[0038] Medical equipment manufacturers use the electromagnetic environment simulation method of the display module of this application for testing. The system first collects environmental data in multiple real scenes (such as ambulances and helicopters) and establishes a scene library. During the test, the system automatically configures multiple radio frequency sources (including 850MHz signals of vehicle-mounted communication equipment, 2.4GHz signals of medical equipment, etc.) and vibration parameters according to the "ambulance high-speed driving" scene identification code. The system can also dynamically adjust the test parameters according to abnormal conditions during the test (such as sudden changes in display brightness) to accurately restore the actual use environment. This method effectively verifies the actual performance of the display module in a complex environment.

[0039] It can be seen that the electromagnetic environment simulation method of the display module in the embodiment of the present application can not only realize the electromagnetic compatibility verification of the display module, but also effectively avoid the problem of differences between traditional testing methods and actual application environments, thereby achieving high reliability and practicality of the test results.

[0040] For ease of understanding, the following describes the process of the method provided by this implementation in combination with the above scenario. Figure 1 , is a flow chart of a method for simulating an electromagnetic environment of a display module in an embodiment of the present application.

[0041] S101, receiving a test identification code input by a user, extracting a plurality of target scenes corresponding to the test identification code from a preset scene library, and generating a scene change sequence.

[0042] Among them, the test identification code represents the code used to uniquely identify a specific test scenario, which may include information such as scenario type, environmental conditions and test requirements; the preset scenario library refers to a database that stores multiple standardized test scenarios, each of which contains a complete description of electromagnetic environment parameters and test conditions; the target scenario is used to represent specific application scenarios that match the current test requirements, such as hospitals, ambulances, helicopters, patient communities and other medical areas or the environment of mobile medical equipment; the scene change sequence represents a combination of multiple target scenarios arranged in chronological order.

[0043] After receiving the test identification code input by the user through the human-computer interaction interface, the electromagnetic simulation system starts to perform the scene extraction operation. Specifically, the system first parses the scene type and test requirement information contained in the test identification code, then retrieves the scene record matching the identification code in the preset scene library, and extracts the target scene that meets the matching conditions. The system arranges and combines the extracted multiple target scenes according to the temporal relationship in the actual application to form a complete scene change sequence.

[0044] In some embodiments, the scene extraction and sequence generation process can be implemented in a variety of ways: Optionally, the system can be implemented through the following steps: string parsing of the test identification code to extract the scene type code and environmental parameter code; fuzzy matching in the scene library based on the scene type code to generate a set of candidate scenes; screening and sorting the candidate scenes based on the environmental parameter code to determine the final target scene set; constructing a scene change sequence based on the association between scenes. Optionally, the system can also map the test identification code to a predefined scene template; automatically extract related scenes according to the template rules; calculate similarity based on scene attributes; select the target scene according to the degree of similarity; generate a scene sequence according to timing constraints. It is understandable that other scene matching and sequence generation algorithms can also be used, which are not limited here.

[0045] S102: Determine, according to multiple target scenes in the scene change sequence, a combination of radio frequency interference sources and mechanical vibration parameters corresponding to the target scenes.

[0046] Among them, the RF interference source combination represents the interference environment composed of multiple electromagnetic interference sources, including RF signals generated by medical equipment, communication equipment and vehicle-mounted systems; mechanical vibration parameters refer to physical quantities that describe the environmental vibration characteristics, including vibration frequency, amplitude and acceleration.

[0047] After obtaining the scene change sequence, the electromagnetic simulation system begins to determine the interference source and vibration parameters. Specifically, the system first analyzes the environmental characteristics of each target scene and identifies the types and location distribution of possible RF interference sources in the scene. Then, the system determines the operating parameters of each RF source based on the scene characteristics, including frequency range, transmission power, and modulation mode. At the same time, the system also calculates the corresponding mechanical vibration parameters based on the scene characteristics, including vibration spectrum characteristics and intensity distribution.

[0048] S103: Based on multiple RF interference source combinations and multiple mechanical vibration parameters corresponding to multiple target scenarios, test parameters of test time periods corresponding to the multiple target scenarios are set to generate a dynamic test sequence.

[0049] Among them, the test time period represents the duration of each target scenario and the test execution interval; the test parameters refer to the various configurations that control the test process, including signal strength, frequency scanning range and vibration intensity; the dynamic test sequence is used to represent the complete test process arranged in chronological order.

[0050] After determining the interference source combination and vibration parameters, the electromagnetic simulation system sets the test parameters and generates the sequence. Specifically, the system first determines the preset test time period for each target scenario, and then converts the RF interference source combination and mechanical vibration parameters into specific test control parameters, including the configuration parameters of the signal generator and the control parameters of the vibration table. Finally, the system integrates these parameters into a complete dynamic test sequence in chronological order.

[0051] S104: Receive the key test scenario marked by the user, adjust the test time period and test parameters corresponding to the key test scenario in the dynamic test sequence, and obtain the target test sequence.

[0052] Among them, key test scenarios refer to test scenarios that are selected and marked by users as being particularly important or requiring key verification; test time period adjustment refers to the extension or shortening of the test duration of a specific scenario; and test parameter adjustment refers to the optimization and modification of the test configuration.

[0053] After generating the dynamic test sequence, the electromagnetic simulation system performs targeted optimization according to the user input. Specifically, the system receives the key test scene marked by the user and extracts the personalized setting information of the key test scene set by the user. The system adjusts the test time allocation accordingly based on the personalized setting information, and generally increases the test duration. Here, the extension of the test duration also represents the increase in the number of tests, because under the preset circumstances, the time of a round of tests is fixed. Extending the test duration means adding one or more rounds of tests. Similarly, in some cases, the test duration of each round can also be extended to test the stability of the display module in this scenario. At the same time, the system will also modify the test parameter configuration of the key test scene based on the personalized setting information to improve the accuracy and reliability of the test. Finally, after adjusting the test time period and test parameters corresponding to the key test scene in the dynamic test sequence, the dynamic test sequence will be determined as the target test sequence.

[0054] In some embodiments, the key test scenario can also be a combination of multiple target scenes. For example, the ambulance scene and the hospital scene can be combined into a key test scene to test the anti-interference of the display module when the scene changes from an ambulance to a hospital. Other scene combinations may also be an ambulance to a residential area, from one department to another, etc., which can all be based on user settings and serve as key test scenarios.

[0055] S105 , simulating the electromagnetic environment of the target display module based on the target test sequence, and recording simulation test parameters of the target display module.

[0056] Among them, the simulation test parameters refer to the display module performance indicators recorded during the test process, which are used to characterize the display effect and response characteristics, including display brightness, contrast and response time.

[0057] After obtaining the target test sequence, the electromagnetic simulation system begins to execute the actual test process. Specifically, the system first configures various test equipment according to the test sequence, including signal generators, vibration tables, etc. Then, the system controls the operation of the test equipment according to the preset timing to simulate the electromagnetic environment of the target scene. At the same time, the system monitors and records various performance parameters of the display module in real time, including display brightness, contrast, response time and other indicators.

[0058] S106. Determine an electromagnetic compatibility assessment result based on the target test sequence and the simulation test parameters.

[0059] Among them, the electromagnetic compatibility assessment results represent a comprehensive evaluation of the working performance of the display module in a complex electromagnetic environment.

[0060] After the electromagnetic simulation system completes the test, it will analyze and evaluate the results. Specifically, the system first performs statistical analysis on the recorded simulation test parameters and calculates the statistical characteristics of various performance indicators. Then, the system compares these indicators with the preset evaluation criteria and integrates the performance in different scenarios. Finally, the system generates a complete electromagnetic compatibility evaluation report based on the comparison results.

[0061] In the above embodiment, the system realizes the simulation test of complex electromagnetic environment through the scene feature model and dynamic test sequence. In practical application, the system can identify key test scenes according to historical test data, optimize the test parameter configuration, and improve the test efficiency and accuracy. The following is a supplement to the scene of this embodiment.

[0062] The electromagnetic simulation system has accumulated test data and built a historical database during long-term use. When testing new display modules, the system can identify key test scenarios, such as the superposition of transient interference when an ambulance starts and brakes suddenly. By analyzing the test results of similar scenarios in historical data, the system automatically optimizes the test duration and parameter configuration. At the same time, the system can also automatically adjust the test plan according to the characteristics of the electromagnetic environment in different regions (such as high-density communication interference in urban areas, industrial equipment interference in suburban areas, etc.), and provide more targeted verification results.

[0063] After combining the above scenarios, the following is a more detailed description of the process of the method provided by this implementation. Figure 2, is another flow chart of the electromagnetic environment simulation method of the display module in the embodiment of the present application.

[0064] S201, receiving a test identification code input by a user, extracting a plurality of target scenes corresponding to the test identification code from a preset scene library, and generating a scene change sequence.

[0065] Referring to step S101 , the electromagnetic simulation system generates a scene change sequence.

[0066] In some embodiments, the electromagnetic simulation system will collect in real time the spatial electromagnetic field distribution data in multiple mobile medical scenarios, the vibration information during the operation of the equipment, and the radio frequency signal characteristics of multiple radio frequency interference sources; perform time synchronization and spatial registration processing on the spatial electromagnetic field distribution data, vibration information and radio frequency signal characteristics to obtain measured standard data; based on the measured standard data, establish a scene feature model that includes the location of the electromagnetic interference source, signal characteristics and environmental parameters; store the scene feature model in association with the scene identification code to generate a preset scene library.

[0067] Among them, mobile medical scenarios refer to the environments in which medical equipment are used, such as hospitals, ambulances, helicopters, and patient communities; spatial electromagnetic field distribution data refers to a set of numerical values ​​that characterize the electromagnetic field strength at each point in space; vibration information is used to represent the mechanical vibration characteristics generated when the equipment is running; radio frequency signal characteristics represent the electromagnetic wave characteristics emitted by various interference sources; time synchronization refers to unifying the acquisition time of different data sources to the same time reference; spatial alignment is used to represent the mapping of data at different spatial locations to a unified coordinate system; and a scene feature model refers to a mathematical model that describes the complete characteristics of the electromagnetic environment of a specific scene.

[0068] Before building a preset scenario library, the electromagnetic simulation system needs to collect actual environmental data. Specifically, the system first deploys a sensor network in multiple typical mobile medical scenarios to collect environmental data in real time. The collected data is then preprocessed to ensure consistency in time and space. Based on the processed data, the system builds a scenario feature model that contains complete environmental features, and establishes a corresponding relationship with the scenario identification code to form a standardized scenario library.

[0069] It should be noted that the scene feature model receives spatial electromagnetic field distribution data (including field strength, frequency distribution), equipment vibration information (including amplitude, frequency, acceleration) and radio frequency signal characteristics (including signal type, power, spectrum characteristics), and scene identification codes as training inputs, and is trained by minimizing the mean square error between the model prediction value and the measured data, with the scene feature data describing the scene characteristics as the training target. The scene feature model adopts a multi-layer feature mapping structure, including an electromagnetic field feature layer (recording spatial electromagnetic field distribution), a vibration feature layer (describing mechanical vibration characteristics), and an environmental parameter layer (including environmental factors such as temperature and humidity). By receiving the scene identification code, the scene feature model can output a standardized scene feature description, including the spatial distribution of electromagnetic interference sources, signal feature parameters, and environmental condition parameters, which are used to guide the generation of test sequences. The scene feature model supports incremental learning and can continuously optimize its accuracy based on newly collected environmental data.

[0070] S202: Determine, according to multiple target scenes in the scene change sequence, a combination of radio frequency interference sources and mechanical vibration parameters corresponding to the target scenes.

[0071] Referring to step S102 , the electromagnetic simulation system determines the RF interference source combination and the mechanical vibration parameters.

[0072] S203: Based on the multiple RF interference source combinations and the multiple mechanical vibration parameters corresponding to the multiple target scenarios, test parameters of the test time periods corresponding to the multiple target scenarios are set to generate a dynamic test sequence.

[0073] Referring to step S103 , the electromagnetic simulation system generates a dynamic test sequence.

[0074] S204: Obtain rating marks of the user for multiple target scenes in the dynamic test sequence, and determine the target scenes whose rating levels are higher than a preset level threshold as key test scenes.

[0075] Among them, the rating mark refers to the user's evaluation result of the importance of the test scenario; the rating level refers to the quantitative indicator of the importance of the scenario, including high, medium, and low levels; the preset level threshold is used to represent the standard value for identifying key scenarios.

[0076] After generating the dynamic test sequence, the electromagnetic simulation system needs to determine the key verification scenarios. Specifically, the system first collects the user's rating input for each scenario through the user interface and converts the rating results into standardized grade values. Then, the system compares the rating level of each scenario with the preset threshold, screens out the scenarios with ratings higher than the threshold, and marks these scenarios as key test scenarios.

[0077] S205. Calculate the optimal test duration and test parameter adjustment coefficients for key test scenarios based on historical test data.

[0078] Among them, historical test data refers to the test records and results of the system's past executions; the optimal test duration represents a reasonable duration that can fully verify the characteristics of the scenario; and the test parameter adjustment coefficient is used to represent the optimization ratio of each test parameter.

[0079] After determining the key test scenarios, the electromagnetic simulation system begins to calculate the optimization parameters. Specifically, the system first retrieves test records similar to the current key scenarios from the historical database and analyzes the duration distribution and parameter settings in these records. Then, the system uses statistical methods to calculate the most reasonable test duration and determines the adjustment coefficients of various parameters based on historical test results.

[0080] In some embodiments, parameter optimization calculation can be implemented in a variety of ways: Optionally, the system can establish a scene similarity calculation model; extract the duration distribution characteristics in the historical data; calculate parameter sensitivity; generate optimization recommendation values; and verify parameter rationality. Optionally, the system can also use machine learning algorithms to analyze historical data; establish parameter optimization models; predict test results; and dynamically adjust optimization strategies. It is understandable that other parameter optimization methods can also be used, which are not limited here.

[0081] It should be noted that the scene similarity calculation model is trained based on historical scene data. The input data includes N-dimensional feature vectors such as RF signal strength, frequency distribution, vibration amplitude, ambient temperature and electromagnetic field strength. The training goal is to optimize the Mahalanobis distance calculation parameters and kernel density estimation parameters to maximize the recognition accuracy of similar scenes. The scene similarity calculation model adopts a three-layer structure based on N-dimensional feature space, including a feature mapping layer (mapping scene features to feature space), a distance calculation layer (calculating Mahalanobis distance based on kernel density estimation) and a weight adjustment layer (dynamically adjusting weights according to data confidence). The scene similarity calculation model can receive current scene features and historical scene library data, and output a standardized similarity score for screening the closest historical reference scenes. It supports online updates and dynamic weight adjustments to ensure the accuracy of similarity calculations.

[0082] The parameter optimization model uses historical test data (including test parameter configuration, test duration, test results) and performance evaluation indicators (including display quality, response time, stability) as training data. The training goal is to maximize test efficiency (shortest test time) and accuracy (minimum error rate). The structure of the parameter optimization model includes a parameter sensitivity analysis layer (to evaluate the degree of parameter influence), an optimization strategy generation layer (to calculate parameter adjustment plans), and an effect evaluation layer (to predict optimization effects). In practical applications, the parameter optimization model can receive real-time test parameters and performance indicators as input, output optimized test duration and parameter adjustment coefficients, support dynamic parameter adjustment and real-time optimization, and can quickly adjust the test strategy according to abnormal conditions during the test process.

[0083] In some embodiments, the electromagnetic simulation system performs cluster analysis on historical test data, classifies scenarios whose data similarity between electromagnetic environment characteristics and test results is higher than a preset similarity threshold into test scenario clusters, and calculates feature vectors of the test scenario clusters; maps the feature vectors to a multidimensional feature space, and calculates the scene similarity between key test scenarios and each test scenario cluster; determines the target scene cluster with the highest scene similarity, extracts historical test data in the target scene cluster as optimization reference data, and determines the optimal test duration and test parameter adjustment coefficient.

[0084] Among them, cluster analysis refers to a data mining method that classifies similar data samples; the test scenario cluster represents a corresponding set of scenarios; the feature vector refers to a multidimensional numerical sequence that describes the characteristics of the scenario; and the optimization reference data is used to represent historical experience data that guides parameter optimization.

[0085] When optimizing parameters, the electromagnetic simulation system needs to use historical data to provide a basis for decision-making. Specifically, the system first extracts features and performs cluster analysis on historical test data to form corresponding scene clusters. Then, it calculates the similarity between the current key test scene and each scene cluster to find the most matching target scene cluster. Finally, it extracts valid historical data from the target scene cluster to optimize the current test parameters.

[0086] In some embodiments, the electromagnetic simulation system constructs an N-dimensional feature space and maps the feature vectors to feature points in the N-dimensional feature space; the coordinate axes of the N-dimensional feature space correspond to the RF signal strength, frequency distribution, vibration amplitude, ambient temperature and electromagnetic field strength respectively; based on the kernel density estimation method, the Mahalanobis distance between the feature points and the center points of each test scene cluster is calculated, and the Mahalanobis distance is converted into a similarity score; the test scene clusters are dynamically weighted, and the weight coefficients of each test scene cluster are determined according to the confidence of the historical test data; based on the similarity scores and weight coefficients, the scene similarity between the key test scenes and each test scene cluster is calculated.

[0087] Among them, N-dimensional feature space represents a multidimensional mathematical space used to describe scene features; feature points refer to the position of scenes in feature space; Mahalanobis distance is used to represent the distance measurement of feature correlation; similarity score represents the quantitative index of the similarity between scenes; weight coefficient refers to the adjustment factor reflecting the importance of each scene cluster; confidence is used to represent the evaluation index of the credibility of historical data.

[0088] Specifically, the electromagnetic simulation system first constructs a feature space containing multiple key feature dimensions and maps scene features into points in the space. Then, the kernel density estimation method is used to calculate the distance between feature points, and the weight of each scene cluster is dynamically adjusted based on the credibility of historical data. Finally, the distance and weight are combined to obtain the final similarity evaluation result.

[0089] Among them, the electromagnetic simulation system uses an exponential decay function to convert distance to similarity. First, the benchmark distance d0 is determined according to the distribution of historical data, and the value is 10% of the maximum Mahalanobis distance between all historical scene pairs. Then the exponential function similarity_score = exp(-d / d0) is used to map the Mahalanobis distance d to a similarity score in the interval [0, 1]. When the two scenes are exactly the same, the Mahalanobis distance is 0, and the highest similarity score of 1 is obtained; as the Mahalanobis distance increases, the similarity score decays exponentially. The decay rate of the score can be controlled by adjusting the benchmark distance d0. A larger d0 value will make the score decay more slowly, and a smaller d0 value will make the score decay faster. For example, when the measured Mahalanobis distance is 2.5 and the benchmark distance d0 is 3, the calculated similarity score is 0.435, indicating a moderate degree of similarity.

[0090] S206. According to the optimal test duration, extend or shorten the test time period corresponding to the key test scenario in the dynamic test sequence to obtain the optimized test time.

[0091] The optimized test time refers to the final test duration after adjustment.

[0092] After obtaining the optimal test duration, the electromagnetic simulation system makes time adjustments. Specifically, the system first analyzes the current time allocation of each key test scenario in the dynamic test sequence and compares it with the calculated optimal test duration. Then, based on the comparison results, the electromagnetic simulation system extends or shortens the test time of each key scenario accordingly to ensure that the test duration meets the verification requirements.

[0093] Among them, when the electromagnetic simulation system makes time adjustments based on the scene importance rating and historical test data, it will first calculate the importance score of each scene, which is weighted by the user rating (60%) and the historical abnormal frequency (40%). Then all scenes are arranged in descending order by score, and the 25% scenes with the highest scores extend the test time to twice the original time, the second highest 25% scenes extend to 1.5 times, the middle 25% scenes keep the original time, and the lowest 25% scenes are shortened to 0.5 times the original time. At the same time, ensure that the adjusted total test time does not exceed the preset upper limit. If it exceeds, the adjustment multiple of each scene is reduced proportionally. For example, for an experiment with an original planned test time of 60 minutes, including 4 test scenes of 15 minutes each, it may be adjusted according to the importance score to: 30 minutes for the most important scene, 22.5 minutes for the second most important scene, 15 minutes for the general scene, and 7.5 minutes for the least important scene. The extension of the test time can also be adjusted and set by the user on the visual interface.

[0094] S207. According to the test parameter adjustment coefficient, adjust the combined output power of the radio frequency interference source and the mechanical vibration parameters of the key test scenario to obtain optimized test parameters.

[0095] Among them, the combined output power of the RF interference sources represents the emission intensity of each RF source; the mechanical vibration parameters refer to the configuration parameters of the vibration equipment; and the optimized test parameters are used to represent the final test configuration after adjustment.

[0096] After obtaining the parameter adjustment coefficient, the electromagnetic simulation system performs test parameter optimization. Specifically, the system first calculates the target output power of each RF source based on the adjustment coefficient and determines the target parameter value of the vibration device. Then, the system verifies whether the optimized parameters are within the allowable range of the device and generates the final optimized test parameter configuration.

[0097] The determination of the target parameter values ​​of the vibration equipment includes: the electromagnetic simulation system determines the vibration parameters through mathematical modeling methods. First, a vibration feature space is established, which includes three dimensions: frequency, amplitude, and acceleration. Based on historical test data, a Gaussian mixture model is used to cluster the effective vibration parameter combinations to obtain typical vibration modes for various scenarios. For new test scenarios, the system calculates its Mahalanobis distance from each typical mode, selects the mode with the smallest distance as the parameter benchmark, and then fine-tunes it according to the characteristics of the scenario. The parameter range supported by the system is: frequency 5-200Hz, amplitude 0.1-2mm, and maximum acceleration 2g. Parameter adjustment follows the principle of continuity to ensure that parameter changes do not cause violent oscillations in the test system.

[0098] S208. Determine a target test sequence based on the dynamic test sequence, the optimized test time, and the optimized test parameters.

[0099] Among them, the target test sequence represents the final optimized test process; the optimized test time refers to the adjusted time arrangement; and the optimized test parameters are used to represent the adjusted configuration parameters.

[0100] After completing the time and parameter optimization, the electromagnetic simulation system generates the final test sequence. Specifically, the system first applies the optimized test time and parameter configuration to the original dynamic test sequence and updates the test configuration of the key test scenarios. Then, the system reorganizes the test process and generates a target test sequence that includes all the optimized content.

[0101] It should be noted that when the electromagnetic simulation system performs the optimization process of steps S206-S208, it first adjusts the time of the key test scene according to the optimal test duration. For each key test scene, the system calculates the difference between the current test time of the scene and the optimal test duration. If the difference is positive, it means that the test time needs to be extended. The system will extend the test time of the scene to the optimal duration without affecting other scenes. If the difference is negative, it means that the test time can be appropriately shortened, and the system will allocate the excess time to other key scenes; specifically, the electromagnetic simulation system will calculate the similarity matrix between the current scene and the historical scene, and for scenes with a similarity greater than 0.85, analyze the shortest effective test duration in its historical test data (i.e., the shortest time in which stable performance indicators can be observed). Based on this shortest effective duration, combined with the importance rating of the current scene, the final test duration is determined. The specific calculation formula is: adjusted duration = shortest effective duration × (1 + importance coefficient), where the importance coefficient range is [-0.2, 0.4]. The system gradually adjusts the test duration of each scenario through an iterative optimization method until the total duration meets the preset constraints.

[0102] Next, the electromagnetic simulation system optimizes each test parameter based on the test parameter adjustment coefficient. For the combination of RF interference sources, the system adjusts the output power, frequency and modulation mode of each RF source respectively. For example, if the adjustment coefficient shows that the interference effect of a certain RF source is insufficient, the system will gradually increase its output power. The standard of increase is based on the initial power P0 (usually 20% of the rated power of the device), and each time it is adjusted in steps of 5% of the current power value. After each adjustment, the system monitors the change trend of the performance indicators of the display module within a 10-second window. If the standard deviation of the performance indicator is less than the preset threshold (indicating stable performance) and the average value meets the test requirements, the power will continue to be increased; if performance abnormalities are detected (such as exceeding the normal range by 20%), the power will be immediately reduced to the previous stable point. During the whole process, ensure that the output power does not exceed 80% of the rated power of the device. If it is determined that the interference in a certain frequency band is particularly obvious (the detection fluctuation in this frequency band is higher than the preset stability threshold), the signal strength of this frequency band will be reduced accordingly. For mechanical vibration parameters, the system adjusts the parameters such as frequency, amplitude and acceleration of the vibration table to make it closer to the actual application environment.

[0103] After each parameter adjustment, the electromagnetic simulation system will conduct a small-scale verification test to check the effect of the adjustment. If it is found that a certain adjustment leads to a significant improvement in display performance, the system will maintain the adjustment direction; if the adjustment effect is not obvious or causes performance degradation, it will fall back to the previous set of parameter settings. Through this step-by-step adjustment and verification method, the system will eventually obtain the optimized test parameter configuration. The electromagnetic simulation system will integrate the optimized test time and parameter configuration into the original dynamic test sequence. For critical test scenarios, new time allocation and parameter settings are used; for non-critical scenarios, the original test configuration is maintained. Finally, a target test sequence containing all optimization content is generated as the final test execution plan.

[0104] S209 , simulating the electromagnetic environment of the target display module based on the target test sequence, and recording simulation test parameters of the target display module.

[0105] Referring to step S105 , the electromagnetic simulation system records the simulation test parameters.

[0106] S210: When it is detected that the fluctuation value of the simulation test parameter is greater than a preset normal threshold, the electromagnetic field distribution data and the mechanical vibration data of the fluctuation time period are extracted.

[0107] Among them, the fluctuation value indicates the variation range of the test parameter; the preset normal threshold refers to the allowable parameter fluctuation range; and the fluctuation time period is used to indicate the duration of the parameter abnormality.

[0108] The electromagnetic simulation system monitors parameter changes in real time during the test. Specifically, the system continuously compares the real-time value of the test parameter with the preset threshold. When a fluctuation beyond the normal range is detected, the system records the complete environmental data of the abnormal period, including information such as electromagnetic field intensity distribution and mechanical vibration characteristics.

[0109] In some embodiments, abnormality monitoring and data collection can be achieved in a variety of ways: Optionally, the system can establish a real-time monitoring model; calculate fluctuation characteristics; trigger data collection; store environmental information; and mark abnormal time periods. Optionally, the system can also set multi-level alarm thresholds; analyze fluctuation trends; predict abnormal occurrences; and automatically adjust the sampling rate. It is understandable that other abnormality detection methods can also be used, which are not limited here.

[0110] S211. Determine the triggering condition of the fluctuation according to the electromagnetic field distribution data and the mechanical vibration data in the fluctuation time period.

[0111] Among them, the triggering condition of fluctuation represents the combination of environmental factors that cause parameter abnormality; the electromagnetic field distribution data refers to the distribution characteristics of the electromagnetic field intensity in space; the mechanical vibration data is used to represent the characteristic parameters of environmental vibration; and the fluctuation time period represents the time interval when the abnormality occurs.

[0112] After obtaining abnormal data, the electromagnetic simulation system needs to determine the cause of the fluctuation. Specifically, the system first performs time-frequency domain analysis on the environmental data during the fluctuation period to extract the characteristic parameters of the electromagnetic field and vibration signals. Then, through correlation analysis, the system identifies environmental factors that are highly correlated with parameter fluctuations and determines the specific triggering conditions that cause the abnormality.

[0113] Specifically, the time-frequency domain analysis is as follows: the electromagnetic simulation system uses a comprehensive signal processing method to analyze the test data. In the time domain, the system calculates the statistical characteristics of the signal, including the mean, standard deviation, peak factor, etc., to characterize the overall distribution characteristics of the signal. In the frequency domain, the system uses fast Fourier transform (FFT) to analyze the spectral composition of the signal and identify the main frequency components and their amplitudes. At the same time, the system uses continuous wavelet transform to perform time-frequency joint analysis on the signal, and uses Morlet wavelet as the basis function to accurately locate the occurrence time and frequency characteristics of transient anomalies. By calculating the cross-correlation function and cross-power spectrum between different parameters, a causal relationship model of parameter changes is established. For example, when it is detected that the display brightness changes suddenly at a certain moment, the system can locate the specific frequency interference source that causes this anomaly through time-frequency analysis.

[0114] S212: Filter out historical abnormal scenarios corresponding to the trigger conditions from the preset scenario library, and extract protective measures and optimization solutions corresponding to the historical abnormal scenarios.

[0115] Among them, historical abnormal scenarios refer to test records in which similar problems have occurred; the determination of similar problems includes: the electromagnetic simulation system represents the similarity of problems through multi-dimensional feature vectors. The system constructs a feature vector for each abnormal event, including: fluctuation type (such as encoding values ​​of brightness, contrast, etc.), trigger condition parameters (RF band, power, vibration frequency, etc.), fluctuation amplitude, scene type and other dimensions. The similarity of two problems is obtained by calculating the cosine similarity of their feature vectors. When the feature similarity of two problems exceeds 0.8 and the difference in their key parameters (such as fluctuation amplitude, frequency range, etc.) is within the range of ±20%, they are determined to be similar problems. For example, when two display brightness abnormal events both occur near the 2.4GHz frequency band and the brightness change amplitudes are -25% and -30% respectively, they can be determined to be similar problems.

[0116] After determining the trigger conditions, the electromagnetic simulation system searches for solutions. Specifically, the system first retrieves similar historical abnormal records in the preset scenario library based on the trigger condition characteristics. Then, the system extracts proven effective protection measures and parameter optimization solutions from the matching historical records to provide a reference for solving the current problem. In some embodiments, solutions can be obtained in a variety of ways: Optionally, the system can calculate scene similarity; filter historical records; evaluate solution effectiveness; integrate optimization suggestions; and generate execution plans. Optionally, the system can also establish a knowledge graph; analyze solution effects; predict optimization results; and formulate protection strategies. It is understandable that other solution matching methods can also be used, which are not limited here.

[0117] S213. Based on the protection measures and optimization scheme, adjust the test parameters of the fluctuation time period in the target test sequence, and re-execute the electromagnetic environment simulation test.

[0118] Among them, protective measures refer to specific operations to prevent parameter fluctuations; optimization plans refer to adjustment strategies to improve test results; test parameters are used to indicate configuration items that need to be adjusted; and fluctuation time periods indicate test intervals that need to be optimized.

[0119] After obtaining the solution, the electromagnetic simulation system performs optimization and adjustment. Specifically, the system first calculates the adjustment amount of the test parameters in the fluctuation period according to the protection measures and optimization scheme. Then, the system updates the parameter configuration of the corresponding period in the target test sequence and restarts the test process of this period to verify the optimization effect.

[0120] It should be noted that during the fluctuation processing of steps S210-S213, the electromagnetic simulation system continuously monitors performance parameters such as display brightness, contrast and response time during the test. Parameter data is collected every fixed time interval (such as 100ms) and the change value from the previous moment is calculated. If the change value of a parameter exceeds the preset normal threshold (such as brightness change exceeding 20%, contrast change exceeding 15%), the system will mark it as a fluctuation.

[0121] After the fluctuation is detected, the electromagnetic simulation system will immediately save the environmental data before and after the fluctuation period. Specifically, it includes: the working status of each RF source (frequency, power, modulation mode), the operating parameters of the vibration equipment (frequency, amplitude, acceleration), and the electromagnetic field strength value of each measuring point in space. At the same time, it records the start time, duration and amplitude of the fluctuation.

[0122] By analyzing these environmental data, the electromagnetic simulation system determines the specific cause of the fluctuation. For example, if a certain RF source happens to switch the operating frequency band when the fluctuation occurs, or the vibration frequency enters a certain range, these may be conditions that trigger the fluctuation. The system will record these possible triggering factors and their parameter values. Then the system searches for similar abnormal records in the preset scenario library. When searching, the main comparison is the similarity of the triggering conditions, such as whether the frequency range of the RF source is close, whether the vibration parameters are in the same order of magnitude, etc. After finding similar cases, extract the solutions used in these cases, such as adjusting the working mode of the RF source, changing the vibration parameters, increasing the buffer time, etc.

[0123] Finally, the electromagnetic simulation system resets the test parameters for the fluctuation period. For example, if it is found that the fluctuation is caused by radio frequency interference in a certain frequency band, the signal strength of the frequency band will be reduced; if the problem is caused by vibration resonance, the corresponding frequency range will be avoided. The system re-executes the test with the new parameter configuration and continues to monitor whether similar fluctuations will occur again.

[0124] S214. Determine an electromagnetic compatibility assessment result based on the target test sequence and simulation test parameters.

[0125] Referring to step S106 , the electromagnetic simulation system generates an electromagnetic compatibility assessment result.

[0126] In this step, the electromagnetic simulation system will first process the raw test data and convert the continuously collected display performance parameters into a data form that is easy to analyze. For display brightness, the maximum, minimum, and average values ​​during the test are counted, and the fluctuation range and stability are calculated. For contrast, the changing trends in different scenarios are analyzed, and whether there is temporary distortion or continuous degradation. For response time, the response delay of each test point is counted, and the average response time and maximum delay are calculated.

[0127] The electromagnetic simulation system sets different scoring standards according to the test scenario. For example, in an ambulance scenario, more attention may be paid to display stability; in a hospital environment, more attention may be paid to image quality. For each performance indicator, a baseline value and an allowable range are set. If the fluctuation of the display brightness does not exceed ±10%, full marks can be obtained, and points will be deducted according to the degree of deviation if it exceeds; full marks are obtained for response time within 50ms, and a certain number of points will be deducted for each additional 10ms. Finally, the electromagnetic simulation system calculates the overall evaluation score and determines the grade. For example, 90 points or more can be divided into Grade A (fully meet the requirements), 80-90 points into Grade B (basically meet the requirements), 70-80 points into Grade C (needs improvement), and below 70 points into Grade D (does not meet the requirements). The system will also mark abnormal conditions and key issues during the test to provide a reference for subsequent optimization.

[0128] In some embodiments, the electromagnetic simulation system determines the dynamic response data of the target display module based on the simulation test parameters; the dynamic response data includes a display brightness fluctuation curve, a contrast change curve and a response time distribution; the dynamic response data is analyzed in the time-frequency domain to extract multiple characteristic parameters; according to the target test sequence, a preset scoring rule is determined; based on the preset scoring rule, the characteristic score of each characteristic parameter is calculated, and the characteristic score is weighted to obtain a comprehensive evaluation score; the electromagnetic compatibility performance of the target display module is graded according to the comprehensive evaluation score to obtain an electromagnetic compatibility evaluation result.

[0129] Among them, dynamic response data represents the performance change record of the display module during the test process; time-frequency domain analysis refers to an analysis method that simultaneously examines the time domain and frequency domain characteristics of the signal; characteristic parameters are used to represent the key characteristic quantities of performance indicators; preset scoring rules represent the standard system for performance evaluation; characteristic scores refer to the evaluation scores of various indicators; and the comprehensive evaluation score is used to represent the quantitative indicator of the overall performance level.

[0130] After the electromagnetic simulation system completes the test, it needs to conduct a comprehensive evaluation of the test results. Specifically, the system first generates a complete performance response curve based on the recorded test parameters. Then, these curves are analyzed in the time and frequency domain to extract key characteristic parameters. The system scores each characteristic parameter according to the preset scoring rules and obtains a comprehensive evaluation result through weighted calculation. Finally, the electromagnetic compatibility level of the display module is determined based on the evaluation score.

[0131] The determination of the preset scoring rules includes: the electromagnetic simulation system adopts a weighted scoring method based on performance indicators, that is, the performance data of the display module is continuously collected and statistical analysis is performed on each indicator. The brightness stability score (full score 30 points) is determined by calculating the coefficient of variation (standard deviation / mean) of the brightness value during the test cycle, and 5 points are deducted for every 5% increase in the coefficient of variation. The contrast score (full score 30 points) is calculated based on the ratio of the measured contrast value to the nominal value, and 3 points are deducted for every 10% decrease in the ratio. The response time score (full score 40 points) adopts the step response test method to measure the rise time of the display from 10% to 90% of the target brightness, and 5 points are deducted for every 4ms increase in the response time. The final score is the sum of the scores of each item, and the grades are divided according to the total score: 90 points or more are grade A, 80-89 points are grade B, 70-79 points are grade C, and below 70 points are grade D.

[0132] Among them, the multidimensional evaluation model is a comprehensive performance evaluation framework, which is used to comprehensively analyze the working status of the display module in an electromagnetic environment. The multidimensional evaluation model adopts a multi-layer structure design, including a data acquisition layer, a feature extraction layer, and an evaluation decision layer. The data acquisition layer is responsible for real-time recording of original performance parameters such as display brightness, contrast, and response time; the feature extraction layer calculates the statistical characteristics, fluctuation characteristics, and trend characteristics of performance indicators through time-frequency domain analysis methods; the evaluation decision layer is based on preset scoring rules, combined with expert experience and historical data, to quantify and weight the characteristics of each dimension. The multidimensional evaluation model supports adaptive weight adjustment, and can dynamically adjust the weight coefficients of each dimensional indicator according to the importance requirements of different application scenarios. At the same time, the multidimensional evaluation model also has anomaly detection and early warning functions, which can timely identify and mark performance fluctuations that exceed the normal range.

[0133] In the embodiment of the present application, due to the use of scene library construction technology based on actual environment data collection, a joint simulation method of multiple RF sources and mechanical vibrations, and a dynamic optimization mechanism based on historical data, it is possible to accurately restore and simulate the complex electromagnetic environment faced by the display module in the mobile medical scenario, effectively solving the problem of large differences between the single RF source test and the actual application environment in the traditional test method and low reliability of the test results, thereby achieving an accurate evaluation of the electromagnetic compatibility performance of the display module. This method not only supports the simulation of the superposition effect of multi-source interference, but also dynamically adjusts the test parameters according to abnormal conditions during the test process, automatically identifies key test scenarios through historical data analysis, improves test efficiency and accuracy, and provides a more scientific and practical solution for the reliability verification of mobile medical display modules.

[0134] The electromagnetic simulation system in the embodiment of the present invention is described below from the perspective of hardware processing. Figure 3 , which is a schematic diagram of a physical device structure of an electromagnetic simulation system in an embodiment of the present application.

[0135] It should be noted that Figure 3 The structure of the electromagnetic simulation system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0136] like Figure 3 As shown, the electromagnetic simulation system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0137] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0138] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0139] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0140] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0141] Specifically, the electromagnetic simulation system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the electromagnetic environment simulation method of the display module provided in the above embodiment is implemented.

[0142] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the electromagnetic simulation system described in the above embodiment; or may exist independently without being assembled into the electromagnetic simulation system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the electromagnetic simulation system, the electromagnetic simulation system implements the electromagnetic environment simulation method of the display module provided in the above embodiment.

[0143] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0144] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0145] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A method for simulating an electromagnetic environment of a display module, characterized in that: Applied to an electromagnetic simulation system, the method comprises: Receive a test identification code input by a user, extract multiple target scenes corresponding to the test identification code from a preset scene library, and generate a scene change sequence; According to the multiple target scenes in the scene change sequence, determine the RF interference source combination and mechanical vibration parameters corresponding to the target scene; the RF interference source combination includes multiple simulated RF sources; the simulated RF sources include medical equipment RF sources, communication equipment RF sources and vehicle-mounted system RF sources; Based on the multiple RF interference source combinations and the multiple mechanical vibration parameters respectively corresponding to the multiple target scenarios, setting the test parameters of the test time periods corresponding to the multiple target scenarios, and generating a dynamic test sequence; Receiving a key test scenario marked by a user, adjusting a test time period and a test parameter corresponding to the key test scenario in the dynamic test sequence, and obtaining a target test sequence; Simulating the electromagnetic environment of the target display module based on the target test sequence, and recording the simulation test parameters of the target display module; the simulation test parameters include display brightness, contrast and response time; An electromagnetic compatibility evaluation result is determined based on the target test sequence and the simulation test parameters.

2. The method according to claim 1, characterized in that The step of receiving a key test scenario marked by a user, adjusting a test time period and a test parameter corresponding to the key test scenario in the dynamic test sequence, and obtaining a target test sequence specifically includes: Obtaining rating marks of the user for the plurality of target scenes in the dynamic test sequence, and determining the target scenes whose rating levels of the rating marks are higher than a preset level threshold as key test scenes; Based on historical test data, calculate the optimal test duration and test parameter adjustment coefficient of the key test scenario; According to the optimal test duration, extending or shortening the test time period corresponding to the key test scenario in the dynamic test sequence to obtain an optimized test time; According to the test parameter adjustment coefficient, the combined output power of the radio frequency interference source and the mechanical vibration parameters of the key test scenario are adjusted to obtain optimized test parameters; A target test sequence is determined based on the dynamic test sequence, the optimized test time and the optimized test parameters.

3. The method according to claim 2, characterized in that The step of calculating the optimal test duration and test parameter adjustment coefficient of the key test scenario based on the historical test data specifically includes: Performing cluster analysis on the historical test data, classifying the scenes whose data similarity between the electromagnetic environment characteristics and the test results is higher than a preset similarity threshold into test scene clusters, and calculating the feature vectors of the test scene clusters; Mapping the feature vector to a multidimensional feature space, and calculating the scene similarity between the key test scene and each of the test scene clusters; Determine the target scene cluster with the highest scene similarity, extract historical test data in the target scene cluster as optimization reference data, and determine the optimal test duration and test parameter adjustment coefficient.

4. The method according to claim 3, characterized in that The step of mapping the feature vector to a multidimensional feature space and calculating the scene similarity between the key test scene and each of the test scene clusters specifically includes: Constructing an N-dimensional feature space, and mapping the feature vector to a feature point in the N-dimensional feature space; the coordinate axes of the N-dimensional feature space correspond to the radio frequency signal strength, frequency distribution, vibration amplitude, ambient temperature and electromagnetic field strength respectively; Based on the kernel density estimation method, the Mahalanobis distance between the feature point and the center point of each test scene cluster is calculated, and the Mahalanobis distance is converted into a similarity score; Dynamically adjusting the weight of the test scenario clusters, and determining the weight coefficient of each test scenario cluster according to the confidence of the historical test data; The scene similarity between the key test scene and each of the test scene clusters is calculated according to the similarity score and the weight coefficient.

5. The method according to claim 1, characterized in that: The step of determining the electromagnetic compatibility evaluation result based on the target test sequence and the simulation test parameters specifically includes: Based on the simulation test parameters, determining the dynamic response data of the target display module; the dynamic response data includes a display brightness fluctuation curve, a contrast change curve and a response time distribution; Performing time-frequency domain analysis on the dynamic response data to extract multiple characteristic parameters; Determining a preset scoring rule according to the target test sequence; Calculating the feature score of each of the feature parameters based on the preset scoring rule, and weighting the feature score to obtain a comprehensive evaluation score; The electromagnetic compatibility performance of the target display module is graded according to the comprehensive evaluation score to obtain an electromagnetic compatibility evaluation result.

6. The method according to claim 1, characterized in that Before the step of receiving a test identification code input by a user, extracting a plurality of target scenes corresponding to the test identification code from a preset scene library, and generating a scene change sequence, the method further includes: Real-time collection of spatial electromagnetic field distribution data in multiple mobile medical scenarios, vibration information during equipment operation, and RF signal characteristics of multiple RF interference sources; Performing time synchronization and spatial registration processing on the spatial electromagnetic field distribution data, the vibration information and the radio frequency signal characteristics to obtain measured standard data; Based on the measured standard data, a scene feature model including the location of the electromagnetic interference source, signal characteristics and environmental parameters is established; The scene feature model is associated with the scene identification code and stored to generate a preset scene library.

7. The method according to claim 1, characterized in that After the step of simulating the electromagnetic environment of the target display module based on the target test sequence and recording the simulation test parameters of the target display module, the method further includes: When it is detected that the fluctuation value of the simulation test parameter is greater than a preset normal threshold, the electromagnetic field distribution data and the mechanical vibration data of the fluctuation time period are extracted; Determining a trigger condition for fluctuation according to the electromagnetic field distribution data and the mechanical vibration data in the fluctuation time period; the trigger condition includes a radio frequency source combination, a vibration frequency and an environmental parameter; Screening out historical abnormal scenarios corresponding to the trigger conditions from the preset scenario library, and extracting protective measures and optimization solutions corresponding to the historical abnormal scenarios; Based on the protection measures and optimization scheme, the test parameters of the fluctuation time period in the target test sequence are adjusted, and the electromagnetic environment simulation test is re-executed.

8. An electromagnetic simulation system, characterized in that: The electromagnetic simulation system comprises: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code comprises computer instructions, and the one or more processors call the computer instructions so that the electromagnetic simulation system executes the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on an electromagnetic simulation system, the electromagnetic simulation system is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on an electromagnetic simulation system, the electromagnetic simulation system is caused to perform the method according to any one of claims 1 to 7.

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