An electromagnetic compatibility automated detection optimization method and system

Abstract

The application discloses an electromagnetic compatibility automatic detection optimization method and system, the method comprises: the method comprises: calculating the initial frequency of the device and measuring the interference source intensity, and updating the frequency of the device and the interference source intensity according to the recursive feedback of the environmental conditions; dynamically adjusting the environmental weight, and optimizing the placement position and signal receiving angle of the test device, and further adjusting the interference source intensity combined with the environmental conditions; the test data in the device test process is classified, the work period of multiple devices is scheduled, and it is ensured that multiple devices can complete the test without interfering with each other. The application can automatically adjust the working parameters of the device according to real-time data, can reduce manual intervention, and can improve the test efficiency.

Description

Technical Field

[0001] The present invention belongs to the technical field of electromagnetic compatibility testing, and relates to an electromagnetic compatibility automated detection optimization method and system. Background Art

[0002] With the widespread use of electronic devices across various industries, the electromagnetic radiation they generate and their ability to withstand external electromagnetic interference have become important aspects of electromagnetic compatibility (EMC) testing. The primary goal of EMC testing is to ensure that devices can operate stably in various complex electromagnetic environments while not causing electromagnetic interference to surrounding devices or the environment. As electronic devices continue to increase in complexity and integration, electromagnetic interference between devices becomes more prominent, leading to increasing requirements for EMC.

[0003] During electromagnetic compatibility (EMC) testing, test equipment is typically tested at different operating frequencies to assess its anti-interference capabilities and electromagnetic radiation levels within various frequency bands. Traditional EMC testing relies on manual operations and fixed test procedures. Parameters such as test frequency and interference source strength are typically pre-set before the test begins, making it impossible to dynamically adjust them during the test to adapt to changes in the environment and device status. Furthermore, with the diversification of test scenarios, the environmental conditions of electronic equipment, such as temperature, humidity, and electric field distribution, are increasingly impacting test results. Adapting test equipment to real-time environmental conditions has become a key challenge in EMC testing.

[0004] Existing electromagnetic compatibility testing technologies lack effective consideration of environmental factors and a recursive feedback control mechanism, making them prone to test result deviations due to environmental changes or unstable equipment operating conditions. They are unable to stabilize the equipment's operating conditions through adaptive adjustment mechanisms, and thus are unable to guarantee test accuracy or optimize equipment placement, resulting in low test efficiency and accuracy. Summary of the Invention

[0005] In order to solve the deficiencies in the prior art, the present invention provides an electromagnetic compatibility automated detection optimization method and system.

[0006] The present invention adopts the following technical solutions.

[0007] The first aspect of the present invention provides an electromagnetic compatibility automated detection optimization method, comprising:

[0008] Measure the initial interference source strength and monitor the electromagnetic environment in real time to calculate the initial frequency of the electromagnetic compatibility automated testing equipment. Recursively update the equipment frequency and interference source strength based on changes in temperature, humidity, and electric field strength in the environment.

[0009] Dynamically adjust the environmental weight based on the updated device frequency and interference source strength after recursive feedback. Optimize the placement of the test equipment and the signal reception angle according to the dynamically adjusted environmental weight, and further adjust the interference source strength.

[0010] The test data during the device testing process is classified based on the device frequency updated by recursive feedback and the adjusted interference source strength. The working time periods of multiple devices are scheduled according to the classified data and the adjusted interference source strength of each device to ensure that multiple devices can complete the test without interfering with each other.

[0011] Preferably, the calculation formula of the initial frequency is:

[0012]

[0013] Among them, f init is the initial frequency of the device, which is the initial frequency of the electromagnetic interference emitted by the device during testing;

[0014] P init is the initial interference source strength;

[0015] N is the number of sampling points; i is the index of the sampling point;

[0016] f max is the maximum test frequency of the device;

[0017] T and H are the temperature and humidity of the environment, respectively;

[0018] α is the environmental correction factor.

[0019] Preferably, the recursive feedback update formula of the frequency is as follows:

[0020]

[0021] Among them, f n+1 Recursively feedback the updated device frequency;

[0022] f n is the device frequency of the current recursive level;

[0023] n is the recursive level index;

[0024] η f is the learning rate of frequency;

[0025] β is the adjustment factor;

[0026] ΔP n is the change in the intensity of the interference source at the current recursive level.

[0027] Preferably, the recursive feedback update formula of the interference source strength is as follows:

[0028]

[0029] wherein P n+1 is the updated interference source strength by recursive feedback;

[0030] P n is the interference source strength of the current recursive level;

[0031] n is the recursive level index;

[0032] η P is the learning rate of the interference source strength;

[0033] γ P is the feedback response coefficient of the interference source strength;

[0034] κ P is the environmental adaptive coefficient of the interference source strength;

[0035] ΔE n is the change of the electric field strength;

[0036] T n is the environmental temperature of the current recursive level;

[0037] H n is the humidity of the current recursive level.

[0038] Preferably, the device frequency and the interference source strength updated by recursive feedback are used to dynamically adjust the environmental weight, and the formula is as follows:

[0039]

[0040] wherein w env,adj is the adjusted environmental weight;

[0041] V is the integral volume of the physical space region where the test device is located;

[0042] E f (x, y, z) is the electric field distribution function affected by f n+1 and P n+1 ;

[0043] f n+1 and P n+1 are the device frequency and the interference source strength updated by recursive feedback;

[0044] (x0, y0, z0) is the initial placement position of the device;

[0045] T and H are the temperature and humidity in the current environment, respectively;

[0046] σ is the standard deviation of the device position distribution;

[0047] λ is a humidity correction coefficient.

[0048] Preferably, the electric field distribution function is:

[0049]

[0050] where d(x, y, z) is the distance from the device position (x, y, z) to the interference source;

[0051] t is the time.

[0052] Preferably, the further adjustment formula of the interference source intensity is as follows:

[0053]

[0054] where P adj is the adjusted interference source intensity;

[0055] w env,adj is the adjusted environmental weight based on the adjusted environment;

[0056] Ω is the physical space range or test area for electromagnetic compatibility testing;

[0057] E(t) is the electric field intensity at time t;

[0058] θ is the adjustment coefficient of the signal receiving angle;

[0059] Y and H are the temperature and humidity in the current environment, respectively;

[0060] is the standard deviation of the device position fluctuation range;

[0061] φ is the frequency adjustment factor;

[0062] f n+1 is the device frequency updated by recursive feedback.

[0063] Preferably, the test data in the device test process is classified based on the device frequency updated by recursive feedback and the adjusted interference source intensity, and the formula is as follows:

[0064]

[0065] where D class (t) is the classified data at time t;

[0066] X k (t) is the test data of the kth device at time t in the test process;

[0067] P adj is the adjusted interference source intensity;

[0068] f n+1 is the device frequency after recursive feedback update;

[0069] T k is the influence of ambient temperature on the kth device;

[0070] M is the number of devices;

[0071] γ k is the classification adjustment coefficient;

[0072] ΔE k is the change in electric field intensity emitted by the kth test device.

[0073] Preferably, the working periods of multiple devices are scheduled according to the classified data and the interference source strength adjusted by each device, and the formula is as follows:

[0074]

[0075] Among them, T sched is the working period of each device;

[0076] P adj (k) is the interference source strength after adjustment of the kth device;

[0077] D class (t) is the classified data at time t;

[0078] is the scheduling adjustment factor;

[0079] f n+1 is the device frequency after recursive feedback update;

[0080] T k and H k are the temperature and humidity of the environment of the kth device respectively.

[0081] A second aspect of the present invention provides an electromagnetic compatibility automated detection and optimization system, comprising:

[0082] The recursive feedback update module is used to measure the initial interference source strength and monitor the electromagnetic environment in real time. It calculates the initial frequency of the electromagnetic compatibility automated testing equipment and recursively updates the equipment frequency and interference source strength based on changes in temperature, humidity, and electric field strength in the environment.

[0083] Interference source strength adjustment module, which is used to dynamically adjust the environment weight based on the device frequency and interference source strength updated by recursive feedback, optimize the placement of the test equipment and the signal reception angle according to the adjusted environment weight, and further adjust the interference source strength;

[0084] The multi-device collaborative detection module is used to classify the test data during the device testing process based on the recursive feedback updated device frequency and the adjusted interference source strength. The working time periods of multiple devices are scheduled according to the classified data and the adjusted interference source strength of each device to ensure that multiple devices can complete the test without interfering with each other.

[0085] A third aspect of the present invention provides a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; and the processor is used to operate according to the instructions to execute the steps of the method.

[0086] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0087] Compared with the prior art, the beneficial effects of the present invention include at least:

[0088] 1. When calculating the initial frequency, the present invention combines the maximum frequency of the device and the initial interference source strength, and utilizes the distribution of sine and cosine functions to ensure that the frequency distribution is extensive and adaptable to a variety of test scenarios. At the same time, the correction of frequency by temperature and humidity has environmental adaptive characteristics. The environmental correction factor α is introduced to adjust the initial frequency by utilizing the influence of environmental temperature and humidity. By adjusting α, it can automatically adapt to the influence of the external environment on the electromagnetic compatibility test, thereby improving the test accuracy. This calculation method is highly flexible and can dynamically calculate the initial frequency and interference source strength based on the maximum frequency of the device, the interference source strength and the external environmental conditions, thereby improving the adaptability of the system; at the same time, it has strong adaptability and is corrected by environmental factors (such as temperature and humidity), ensuring the accuracy of the test process and the stability of the equipment under different environments.

[0089] 2. The present invention uses a multi-layer recursive and feedback mechanism to recursively feedback and update the frequency and interference source strength of the device according to the changes in temperature, humidity and electric field strength in the environment. It can dynamically adjust the frequency and interference source strength of the device in an adaptive manner to the environment, and can automatically adjust the operating parameters of the device according to real-time data, which can reduce manual intervention, improve test efficiency, and ensure the accuracy and stability of the test process.

[0090] The present invention combines the time derivative when recursively feedback updating the frequency of the device Dynamically adjust the frequency to cope with frequency changes, and not only consider the frequency change, but also the change in the intensity of the interference source, using the modification factor Smoothly respond to changes in interference source strength, making frequency adjustment more sensitive.

[0091] When recursively updating the interference source strength of the device, the present invention considers the change in electric field strength ΔE n and ambient temperature and humidity difference |T n -H n | Dynamically adjust the intensity of the interference source to accurately reflect the actual environmental impact, through the change of the electric field intensity (ΔE n ) square term strengthens the effect of electric field changes on the interference source intensity regulation, ensuring that the fluctuation of electromagnetic interference can have an effective impact on the interference source intensity.

[0092] The present invention adjusts η in each recursive process. f ,η p , γ p 、k p , β controls the adjustment range of frequency and interference source strength and the influence of environmental factors, thereby optimizing the adjustment pace of frequency and interference source strength.

[0093] The present invention can ensure that the frequency and interference source strength can be adjusted in real time with time changes, environmental changes and electric field feedback, avoiding the instability of the equipment under fixed frequency and interference source strength. By comprehensively considering the influence of changes in ambient temperature and humidity and electric field strength, the equipment can always maintain the optimal frequency and interference source strength under complex environmental conditions.

[0094] The present invention combines the feedback of ambient temperature and humidity, frequency and time variations, interference source strength, and electric field strength. The comprehensive adjustment of multiple factors can ensure real-time optimization of device frequency and interference sources. It achieves efficient response and avoids over-response or lag through the smooth response of the sigmoid function to the interference source strength, thus ensuring the high efficiency of recursive adjustment.

[0095] 3. Through environmental adaptive adjustment, the present invention can optimize the placement of the device and the signal reception angle according to factors such as electric field distribution and ambient temperature and humidity, ensuring that the device can operate effectively in different environments.

[0096] The present invention is to distribute the electric field E f The spatial integration of (x, y, z) and the temperature correction of the electric field (via 1 / (T+1)) are combined to dynamically adjust the environmental weights, accurately reflecting the interaction between the environment and the device. The influence of the position distribution standard deviation (σ) and the device placement on the electric field distribution is utilized to ensure the optimization of the device placement during testing. This method is highly adaptable to environmental conditions, capable of real-time adjustment of environmental weights and optimization of device placement to improve the effectiveness of electromagnetic compatibility testing. It also integrates environmental factors, leveraging the influence of temperature and humidity on environmental weights, allowing device placement to be optimized even in complex environments, ensuring test accuracy.

[0097] 4. This invention further dynamically adjusts the interference source strength by comprehensively considering factors such as electric field strength, temperature and humidity, and frequency adjustment to ensure its adaptability to the actual environment. Effective coupling between the interference source strength and the receiving angle and frequency is achieved through the θ and φ adjustment factors. This approach has strong environmental adaptability and can accurately adjust the interference source strength under different environmental temperature and humidity conditions to avoid excessive or weak interference. By adjusting multiple dimensions such as the receiving angle, humidity, and frequency, the interference source strength adjustment is ensured to meet actual test requirements, avoiding the impact of environmental changes on the test.

[0098] 5. The present invention performs high-dimensional data classification analysis on the test data during the equipment testing process based on the recursive feedback updated device frequency and the adjusted interference source strength, which can quickly identify electromagnetic compatibility problems, provide data support for equipment optimization, and improve the intelligence level of the test.

[0099] 6. The present invention schedules the working time periods of multiple devices according to the classified data and the interference source intensity adjusted by each device, which can efficiently schedule the working time of multiple devices, ensure that there is no mutual interference between the devices, and improve the testing efficiency of multiple devices working simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0100] Figure 1 The present invention is a flowchart of an electromagnetic compatibility automatic detection optimization method. DETAILED DESCRIPTION

[0101] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. The embodiments described in this application are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without making creative efforts are all within the scope of protection of the present invention.

[0102] like Figure 1 As shown, embodiment 1 of the present invention provides an electromagnetic compatibility automated detection optimization method, which includes the following steps:

[0103] S1. Measure the initial interference source strength P init , and monitor the electromagnetic environment in real time, obtain key parameters, calculate the initial frequency of the device, and recursively feedback the device frequency and interference source strength according to the changes in temperature, humidity and electric field strength in the environment to obtain the recursive feedback update result f n+1 and P n+1 ;

[0104] Further preferably, the electromagnetic environment is monitored in real time by a sensor array to obtain key parameters such as frequency, interference intensity, electric field intensity, temperature and humidity, etc., and the initial frequency of the device is calculated. The frequency and interference source intensity are recursively adjusted according to changes in environmental conditions and electric field intensity to ensure stable operation of the device in complex environments and continuous optimization;

[0105] Specifically, key parameters such as electric field strength, interference strength, temperature and humidity of the test equipment at different frequencies and interference source strengths will be obtained in real time. The sensor array will be distributed around the test equipment, and the collected data will not only cover the electromagnetic radiation of the equipment, but also the temperature and humidity of the environment.

[0106] All collected electric field and environmental data will be used to preliminarily calculate the initial frequency of the device, ensuring that the system can be dynamically adjusted and optimized based on actual measurement results.

[0107] The initial frequency and initial interference intensity are used as the initial conditions of the test, where the initial interference source intensity P init The initial frequency is measured by an electromagnetic interference meter; the initial frequency is calculated based on the electromagnetic compatibility requirements of the device, such as the device's ability to effectively coexist with other devices or electromagnetic environments during operation, ensuring that the device does not generate unacceptable electromagnetic interference to the external environment during its design and use, and at the same time, it can resist external electromagnetic interference to ensure its normal operation, as well as environmental conditions. The calculation formula for the initial frequency is:

[0108]

[0109] Among them, f init It is the frequency of the initial operation of the equipment, that is, the frequency of the electromagnetic interference emitted by the equipment when it is tested;

[0110] P init is the initial interference source strength;

[0111] N is the number of sampling points, which represents the resolution when calculating the distribution of the frequency range;

[0112] i is the index of the sampling point;

[0113] f max It is the maximum test frequency that is set, indicating the upper limit of the maximum frequency that the device can handle;

[0114] T and H are the temperature and humidity of the environment, respectively;

[0115] α is the environmental correction factor, which is used to correct the impact of environmental parameters on the initial frequency.

[0116] The initial frequency and initial interference strength are taken as inputs of the recursive feedback control process, and the initial conditions are not only set once but will be continuously fed back and corrected throughout the detection process, i.e., the frequency and interference strength are constantly changing after the initial frequency and initial interference strength are set.

[0117] The recursive feedback control process dynamically adjusts the frequency and interference source strength in real time according to the feedback information in each step of the test: when the recursive feedback is updated, the device frequency and interference source strength are adjusted according to the changes of the current environmental conditions (such as temperature, humidity) and electric field strength in each recursive step, the updated device frequency is obtained, the updated device frequency is taken as the frequency input of the next recursive, and the recursive process is cycled to ensure that the frequency is continuously optimized according to the latest environmental data and electric field feedback, gradually approaching the optimal value (when the change value of the frequency is less than a preset threshold, it is considered that the frequency has converged, and the recursive process can be terminated), and finally the recursive feedback update result is obtained, including the updated device frequency f n+1 and the updated interference source strength P n+1 to ensure that the device can stably run in a changing environment. The frequency and interference source strength of the device are recursively updated according to the changes of temperature, humidity and electric field strength in the environment, and the formula is as follows:

[0118]

[0119] wherein, f n+1 is the updated frequency;

[0120] f n is the frequency of the current recursive level;

[0121] n is the recursive level index;

[0122] η f is the learning rate of the device frequency, used to control the size of the adjustment step; η f The value of η

[0123] represents the time derivative of the frequency, used to reflect the dynamic change of the frequency;

[0124] ΔE n is the change of the electric field strength, representing the change feedback of the electromagnetic field under the current environment;

[0125] T n is the environmental temperature of the current recursive level;

[0126] H n is the humidity of the current recursive level;

[0127] P n+1 is the updated interference source strength;

[0128] P n is the interference source strength at the current recursive level;

[0129] η P is the learning rate of the interference source strength, which is used to adjust the size of the step in the recursive process;

[0130] γ P It is the interference source intensity feedback responsivity coefficient, which is used to control the feedback strength of the system to the electric field change, and its value range is between 0.1 and 1;

[0131] κ P It is the environmental adaptive coefficient of the interference source intensity, which is used to control the system's sensitivity to changes in temperature and humidity.

[0132] In each recursion, the frequency is adjusted according to the above formula, and the new device frequency and interference source strength are used as the input for the next step. This process is repeated to ensure that the device frequency and interference source strength are continuously optimized based on the latest environmental data and electric field feedback, gradually approaching the optimal value. Finally, the device parameters after recursive feedback are obtained, including the updated frequency and interference strength.

[0133] To summarize, the formula for recursive feedback control is as follows:

[0134]

[0135] Among them, X n+1 is the device parameter after recursive feedback, including the updated frequency and interference intensity, X n+1 The frequency and interference intensity results after recursive calculation will be the core inputs in the subsequent steps;

[0136] X n are the device parameters at the current recursive level;

[0137] Δt is the time step of each recursion;

[0138] ΔP n is the change in the intensity of the interference source at the current recursive level;

[0139] β is the adjustment factor used to control the change in the intensity of the interference source ΔP n response speed.

[0140] Updated frequency f n+1 and interference source strength P n+1 The value of is used as the input parameter of the electric field distribution function, which can be further used to adjust the position of the test equipment and the signal receiving angle, where the recursively calculated f n+1 Affects the distribution of electric field in space, Pn+1 This directly affects the strength of the electric field, and the recursively updated data can be used to determine the optimal position and receiving angle in the current environment.

[0141] S2. Update the result f based on recursive feedback n+1 and P n+1 Dynamically adjust the environment weight w env,adj , in order to optimize the placement of the test equipment and the signal reception angle, and further adjust the interference source strength in combination with the temperature, humidity and electric field strength in the environment;

[0142] Further preferably, the environmental weight is dynamically adjusted based on the recursive feedback control result, the placement of the test equipment and the signal reception angle are optimized, and the interference source strength is corrected to ensure that the equipment can continue to be tested efficiently under new environmental conditions.

[0143] Specifically, in the environmental adaptive adjustment step, the initial environmental weight is first defined, and then adjusted based on the initial placement of the test equipment and the current environmental parameters (such as electric field distribution, temperature, etc.) to obtain the adjusted environmental weight. The calculation formula is as follows:

[0144]

[0145] Among them, w env,adj is the adjusted environmental weight;

[0146] represents the initial environment weight, λ·tan -1 (H) is the correction part, which mainly considers the impact of humidity on electromagnetic compatibility testing;

[0147] The integration volume V is the physical space region where the test equipment is located;

[0148] E f (x,y,z) is the result of recursive feedback f n+1 and P n+1 The affected electric field distribution function adjusts the distribution of the electric field at different spatial locations, thereby affecting the placement of the device (x, y, z); d(x, y, z) is the distance from the device location (x, y, z) to the interference source;

[0149] (x0, y0, z0) is the initial placement of the device;

[0150] T and H are the current temperature and humidity respectively;

[0151] σ is the standard deviation of the device location distribution, which is used to indicate the fluctuation range of the device placement;

[0152] λ is the humidity correction coefficient, which adjusts the effect of humidity on weight adjustment.

[0153] Furthermore, the adjusted environmental weight optimizes the device location through the relationship between the distribution of electric field strength and the device placement.

[0154] In the space (x, y, z), according to the weight w env,adj , the device will be placed in the area with the strongest electric field strength (i.e. where the weight is the largest), while avoiding excessive interference or unsuitable test conditions.

[0155] By adjusting the electric field distribution and the placement of the device, we ensure that the device is tested in the optimal electromagnetic environment. By correcting the position fluctuation range σ, the system can dynamically adjust the device position in different environments to improve test accuracy.

[0156] After determining the device placement, you can use experience to determine the optimal reception angle. Angle adjustment is closely related to electric field strength, temperature, and humidity. For example, in certain environmental conditions, electric field propagation can be significantly affected by temperature and humidity, so optimizing the signal reception angle must comprehensively consider these factors.

[0157] For each device, the optimized reception angle can be achieved by adjusting the frequency and interference strength, allowing the device to maximize signal reception efficiency without excessive interference.

[0158] The adjusted environmental weight will be used to correct the interference source strength and directly passed to the interference strength adjustment formula in the next step.

[0159] After obtaining the adjusted weights, the interference source strength can be further adjusted to ensure that the device can maintain efficient testing under new environmental conditions. Specifically, after the recursive feedback update, the environmental weights are adjusted and the placement and signal reception angle of the test equipment are optimized, the interference source strength is adjusted again. The adjustment formula is as follows:

[0160]

[0161] Among them, P adj is the corrected interference source strength, which is based on the adjusted environment weight w env,adj and the frequency f after recursive feedback update n+1 to make corrections;

[0162] Ω is the physical space range or test area where the electromagnetic compatibility test is performed;

[0163] E(t) is the electric field intensity, i.e., the dynamic change of the electric field during the test;

[0164] θ is the adjustment coefficient of the signal reception angle, which affects the device's ability to receive signals;

[0165] is the standard deviation of the fluctuation range of the device position, which is used to represent the fluctuation in the interference source strength adjustment;

[0166] φ is the frequency adjustment factor, which is used to correct the coupling between the interference source strength and frequency.

[0167] By combining environmental parameters such as electric field strength E(t), temperature T, and humidity H, the intensity of the interference source is dynamically adjusted to adapt it to the actual test environment, avoiding excessive or insufficient interference.

[0168] S3, device frequency f after update based on recursive feedback n+1 and the adjusted interference source strength P adj Classify the test data during the equipment testing process, and according to the classified data D class (t) and the interference source strength P after adjustment of each device adj (k) Schedule the working time of multiple devices to ensure that multiple devices can complete the test without interfering with each other.

[0169] Further preferably, the device data is analyzed through classification to schedule the working hours of multiple devices to avoid mutual interference.

[0170] Specifically, the adjusted interference intensity will be used in real-time data classification and analysis. Through machine learning algorithms, high-dimensional analysis of the data during the test process can be performed to identify potential electromagnetic compatibility issues. The data classification formula is as follows:

[0171]

[0172] Among them, D class (t) is the classified data, which is based on P adj and f n+1 Classification results of data collected during the test;

[0173] X k (t) is the test data of the kth device at time t;

[0174] T k is the impact of ambient temperature on the kth device (obtained by taking the time-weighted average of the temperature data, i.e., the weighted average of the temperature data of each device at different collection points at different times);

[0175] M is the number of devices;

[0176] γ k is the classification adjustment coefficient;

[0177] ΔE k is the change in electric field intensity emitted by the kth test device.

[0178] Classification result D class (t) reveals the electromagnetic compatibility performance of each device, especially whether there is potential electromagnetic interference between different devices, which will be directly transmitted to the multi-device collaborative work module for test time scheduling between devices.

[0179] In specific implementation, X k X(t) represents the raw test data for the kth device at time t, reflecting the device's electromagnetic behavior in the current test environment. For example, for device 1, X1(t) contains data related to the device's electric field strength at a specific moment, the temperature and humidity around the device, and other environmental factors. Assume that at time t, the device's electric field strength is 100 V / m, the temperature is 25°C, and the humidity is 60%.

[0180] D class (t) represents the result of classifying the raw data based on the machine learning algorithm, which classifies the electromagnetic compatibility status of each device into different levels or categories, such as "qualified", "potential interference risk" or "needs correction". class The output result of (t) is: If the electric field strength of device 1 is too high and under certain temperature and humidity conditions, this device may generate electromagnetic interference and thus be classified as a potential electromagnetic compatibility problem.

[0181] Classification result feedback: The final classification results can help testers identify which devices may cause interference under specific environmental conditions and which devices can work normally in the current environment.

[0182] For example, if the X1(t) data of the first device contains high electric field strength and interference source strength, and is classified by the machine learning model, the result is D class (t) = 1, it means that the device may generate electromagnetic interference at this moment and needs further inspection and correction; if the result is D class If (t) = 0, it means that the device will not cause significant interference under the current conditions and meets the electromagnetic compatibility requirements.

[0183] It can be understood that formula (6) is a simplified machine learning algorithm. The machine learning model first collects the real-time test data X from each device. k (t) extracts features, which include parameters such as electric field strength, frequency, and temperature during the test. In this formula, the focus of feature extraction is the change in electric field strength ΔE k , frequency f n+1 , temperature T k and interference source strength P adj The hyperbolic tangent function tanh and the exponential function in the formula The input data is nonlinearly mapped, which enables the model to better handle the complex relationship between the changes in electric field intensity and the interference intensity and environmental parameters. The tanh function adjusts the ratio of interference intensity to frequency to ensure that the classification response is within a reasonable range. γ in k The influence of electric field change on classification is controlled. k , the machine learning model is able to flexibly adjust its response to changes in electric field strength, especially in environments with strong interference or noise. k It is an important indicator in electromagnetic compatibility analysis, reflecting the degree of interference of the equipment in the electromagnetic environment.

[0184] The application of machine learning algorithms enables:

[0185] Supervised learning: The model is trained based on historical data, enabling the model to automatically classify and predict based on features (such as electric field strength, electromagnetic frequency, ambient temperature, etc.).

[0186] Dynamic update: Since the electromagnetic environment and device status are constantly changing, the model uses a recursive update method to update inputs such as frequency and interference source strength in real time to ensure that the model can continuously adapt to new environments and electromagnetic changes.

[0187] Adaptive control: By introducing multiple parameters such as temperature, humidity, frequency, and electric field strength, the model has adaptive capabilities and can automatically adjust the classification criteria according to different environmental conditions.

[0188] The multi-device collaborative work module ensures that multiple devices can complete the test without interfering with each other based on the data classification results and the interference source strength of each device. The collaborative scheduling formula is as follows:

[0189]

[0190] Among them, T sched It is the device scheduling time window, which indicates the working period of each device and is scheduled based on the interference source strength and frequency of each device;

[0191] P adj (k) is the interference source strength after adjustment of the kth device;

[0192] is the scheduling adjustment factor, which adjusts the scheduling time of the kth device to avoid interference;

[0193] T k and H k are the ambient temperature and humidity of the kth device respectively.

[0194] Based on formula (7), the working time periods of multiple devices can be allocated and scheduled according to the interference source strength and frequency of each device, ensuring that there will be no mutual interference when multiple devices work simultaneously under different temperature and humidity environments, and that they can efficiently and collaboratively complete the test under different environmental conditions.

[0195] Specifically, the scheduling time window is allocated by comprehensively considering the adjusted interference strength of each device, environmental parameters (such as temperature and humidity), and the electromagnetic compatibility classification results between devices. The scheduling time for each device must not only avoid mutual interference between different devices, but also ensure that the devices can work together efficiently under different environmental conditions. For example, devices with higher frequencies may require longer operating times, while devices with lower interference source strength may be assigned shorter test periods. Through these intelligent scheduling methods, the mutual influence between devices during the test process is minimized, while improving test efficiency and accuracy.

[0196] Embodiment 2 of the present invention provides an electromagnetic compatibility automated detection and optimization system, including:

[0197] The recursive feedback update module is used to measure the initial interference source strength and monitor the electromagnetic environment in real time. It calculates the initial frequency of the electromagnetic compatibility automated testing equipment and recursively updates the equipment frequency and interference source strength based on changes in temperature, humidity, and electric field strength in the environment.

[0198] Interference source strength adjustment module, which is used to dynamically adjust the environment weight based on the device frequency and interference source strength updated by recursive feedback, optimize the placement of the test equipment and the signal reception angle according to the adjusted environment weight, and further adjust the interference source strength;

[0199] The multi-device collaborative detection module is used to classify the test data during the device testing process based on the recursive feedback updated device frequency and the adjusted interference source strength. The working time periods of multiple devices are scheduled according to the classified data and the adjusted interference source strength of each device to ensure that multiple devices can complete the test without interfering with each other.

[0200] Embodiment 3 of the present invention provides a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0201] Embodiment 4 of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0202] Compared with the prior art, the beneficial effects of the present invention include at least:

[0203] 1. When calculating the initial frequency, the present invention combines the maximum frequency of the device and the initial interference source strength, and utilizes the distribution of sine and cosine functions to ensure that the frequency distribution is extensive and adaptable to a variety of test scenarios. At the same time, the correction of frequency by temperature and humidity has environmental adaptive characteristics. The environmental correction factor α is introduced to adjust the initial frequency by utilizing the influence of environmental temperature and humidity. By adjusting α, it can automatically adapt to the influence of the external environment on the electromagnetic compatibility test, thereby improving the test accuracy. This calculation method is highly flexible and can dynamically calculate the initial frequency and interference source strength based on the maximum frequency of the device, the interference source strength and the external environmental conditions, thereby improving the adaptability of the system; at the same time, it has strong adaptability and is corrected by environmental factors (such as temperature and humidity), ensuring the accuracy of the test process and the stability of the equipment under different environments.

[0204] 2. The present invention uses a multi-layer recursive and feedback mechanism to recursively feedback and update the frequency and interference source strength of the device according to the changes in temperature, humidity and electric field strength in the environment. It can dynamically adjust the frequency and interference source strength of the device in an adaptive manner to the environment, and can automatically adjust the operating parameters of the device according to real-time data, which can reduce manual intervention, improve test efficiency, and ensure the accuracy and stability of the test process.

[0205] The present invention combines the time derivative when recursively feedback updating the frequency of the device Dynamically adjust the frequency to cope with frequency changes, and not only consider the frequency change, but also the change in the intensity of the interference source, using the modification factor Smoothly respond to changes in interference source strength, making frequency adjustment more sensitive.

[0206] When recursively updating the interference source strength of the device, the present invention considers the change in electric field strength ΔE n and ambient temperature and humidity difference |T n -H n | Dynamically adjust the intensity of the interference source to accurately reflect the actual environmental impact, through the change of the electric field intensity (ΔE n ) square term strengthens the effect of electric field changes on the interference source intensity regulation, ensuring that the fluctuation of electromagnetic interference can have an effective impact on the interference source intensity.

[0207] The present invention adjusts η in each recursive process. f ,η p , γ p , κ p , β controls the adjustment range of frequency and interference source strength and the influence of environmental factors, thereby optimizing the adjustment pace of frequency and interference source strength.

[0208] The present invention can ensure that the frequency and interference source strength can be adjusted in real time with time changes, environmental changes and electric field feedback, avoiding the instability of the equipment under fixed frequency and interference source strength. By comprehensively considering the influence of changes in ambient temperature and humidity and electric field strength, the equipment can always maintain the optimal frequency and interference source strength under complex environmental conditions.

[0209] The present invention combines the feedback of ambient temperature and humidity, frequency and time variations, interference source strength, and electric field strength. The comprehensive adjustment of multiple factors can ensure real-time optimization of device frequency and interference sources. It achieves efficient response and avoids over-response or lag through the smooth response of the sigmoid function to the interference source strength, thus ensuring the high efficiency of recursive adjustment.

[0210] 3. Through environmental adaptive adjustment, the present invention can optimize the placement of the device and the signal reception angle according to factors such as electric field distribution and ambient temperature and humidity, ensuring that the device can operate effectively in different environments.

[0211] The present invention is to distribute the electric field E f The spatial integration of (x, y, z) and the temperature correction for the electric field (via 1 / (T+1)) dynamically adjust the environmental weights, accurately reflecting the interaction between the environment and the device. The influence of the position distribution standard deviation (σ) and the device placement on the electric field distribution ensures the optimization of the device placement during testing. This method is highly adaptable to environmental conditions, enabling real-time adjustment of environmental weights and optimizing device placement to improve the effectiveness of electromagnetic compatibility testing. It also integrates environmental factors, leveraging the impact of temperature and humidity on environmental weights, allowing device placement to be optimized even in complex environments, ensuring test accuracy.

[0212] 4. This invention further dynamically adjusts the interference source strength by comprehensively considering factors such as electric field strength, temperature and humidity, and frequency adjustment to ensure its adaptability to the actual environment. Effective coupling between the interference source strength and the receiving angle and frequency is achieved through the θ and φ adjustment factors. This approach has strong environmental adaptability and can accurately adjust the interference source strength under different environmental temperature and humidity conditions to avoid excessive or weak interference. By adjusting multiple dimensions such as the receiving angle, humidity, and frequency, the interference source strength adjustment is ensured to meet actual test requirements, avoiding the impact of environmental changes on the test.

[0213] 5. The present invention performs high-dimensional data classification analysis on the test data during the equipment testing process based on the recursive feedback updated device frequency and the adjusted interference source strength, which can quickly identify electromagnetic compatibility problems, provide data support for equipment optimization, and improve the intelligence level of the test.

[0214] 6. The present invention schedules the working time periods of multiple devices according to the classified data and the interference source intensity adjusted by each device, which can efficiently schedule the working time of multiple devices, ensure that there is no mutual interference between the devices, and improve the testing efficiency of multiple devices working simultaneously.

[0215] The present disclosure may be a system, method and / or computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0216] A computer-readable storage medium can be a tangible device that can hold and store instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination thereof. As used herein, a computer-readable storage medium is not to be construed as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through an electrical wire.

[0217] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in the computer-readable storage medium in each computing / processing device.

[0218] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, and conventional procedural programming languages ​​such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., utilizing an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions. The electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0219] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. An electromagnetic compatibility automated detection optimization method, characterized in that: The method comprises: Measure the initial interference source strength and monitor the electromagnetic environment in real time to calculate the initial frequency of the electromagnetic compatibility automated testing equipment. Recursively update the equipment frequency and interference source strength based on changes in temperature, humidity, and electric field strength in the environment. The recursive feedback update formula for the frequency is as follows: （2） in, Recursively feedback the updated device frequency; is the device frequency of the current recursive level; is a recursive hierarchical index; is the learning rate of frequency; is the adjustment factor; is the change in the intensity of the interference source at the current recursive level; The recursive feedback update formula of the interference source strength is as follows: （3） in, is the interference source strength after recursive feedback update; is the interference source strength at the current recursive level; is a recursive hierarchical index; is the learning rate of the interference source strength; is the interference source intensity feedback responsivity coefficient; is the environmental adaptation coefficient of the interference source strength; is the change in electric field intensity; is the ambient temperature at the current recursive level; is the humidity of the current recursive level; The environment weight is dynamically adjusted based on the device frequency and interference source strength after recursive feedback update. The placement of the test equipment and the signal reception angle are optimized according to the dynamically adjusted environment weight, and the interference source strength is further adjusted. The further adjustment formula of the interference source strength is as follows: in, is the adjusted interference source strength; is based on adjusted environmental weights; It is the physical space range or test area where electromagnetic compatibility testing is carried out; is the electric field strength at time t; is the adjustment coefficient of the signal receiving angle; and They are the temperature and humidity in the current environment; is the standard deviation of the device position fluctuation range; is the frequency adjustment factor; is the device frequency after recursive feedback update; The test data during the device test process is classified based on the recursive feedback of the updated device frequency and the adjusted interference source strength. The working time of multiple devices is scheduled according to the classified data and the adjusted interference source strength of each device to ensure that multiple devices can complete the test without interfering with each other. The test data during the device test process is classified based on the recursive feedback updated device frequency and the adjusted interference source strength. The formula is as follows: in, is the data after classification at time t; is the test data of the kth device at time t during the test; is the adjusted interference source strength; is the device frequency after recursive feedback update; is the influence of ambient temperature on the kth device; is the number of devices; is the classification adjustment coefficient; is the change in electric field intensity emitted by the kth test device; The working time periods of multiple devices are scheduled based on the classified data and the interference source intensity adjusted by each device. The formula is as follows: in, is the working period of each device; is the interference source strength after adjustment of the kth device; is the data after classification at time t; is the scheduling adjustment factor; is the device frequency after recursive feedback update; and are the temperature and humidity of the environment of the kth device respectively.

2. The electromagnetic compatibility automated detection optimization method according to claim 1, characterized in that: The calculation formula of the initial frequency is: in, is the initial frequency of the device, which is the initial frequency of the electromagnetic interference emitted by the device during testing; is the initial interference source strength; is the number of sampling points; is the index of the sampling point; is the maximum test frequency of the device; and are the temperature and humidity of the environment respectively; is the environmental correction factor.

3. The electromagnetic compatibility automated detection optimization method according to claim 1, characterized in that: The environment weight is dynamically adjusted based on the device frequency and interference source strength after recursive feedback update. The formula is as follows: （4） in, is the adjusted environmental weight; is the integrated volume of the physical space region where the test equipment is located; is and The affected electric field distribution function; and is the device frequency and interference source strength after recursive feedback update; The initial placement of the device; and They are the temperature and humidity in the current environment; is the standard deviation of the device location distribution; is the humidity correction factor.

4. The electromagnetic compatibility automated detection optimization method according to claim 3, characterized in that: The electric field distribution function is: in, is the distance from the device location (x, y, z) to the interference source; t is the time.

5. An electromagnetic compatibility automated detection and optimization system, claiming the method according to any one of claims 1 to 4, characterized in that: The system comprises: The recursive feedback update module is used to measure the initial interference source strength and monitor the electromagnetic environment in real time. It calculates the initial frequency of the electromagnetic compatibility automated testing equipment and recursively updates the equipment frequency and interference source strength based on changes in temperature, humidity, and electric field strength in the environment. Interference source strength adjustment module, which is used to dynamically adjust the environment weight based on the device frequency and interference source strength updated by recursive feedback, optimize the placement of the test equipment and the signal reception angle according to the adjusted environment weight, and further adjust the interference source strength; The multi-device collaborative detection module is used to classify the test data during the device testing process based on the recursive feedback updated device frequency and the adjusted interference source strength. The working time periods of multiple devices are scheduled according to the classified data and the adjusted interference source strength of each device to ensure that multiple devices can complete the test without interfering with each other.

6. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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