A power distribution electromagnetic shielding method and shielding system

Abstract

The application relates to an electromagnetic shielding method and shielding system for power distribution, and belongs to the technical field of electromagnetic shielding. The method comprises the following steps: establishing a shielding model corresponding to a shielding chamber according to volume data of the shielding chamber, simulating and positioning electromagnetic wave conditions in the shielding chamber in the shielding model, selecting key detection points, constructing a phase difference matrix, dividing three reinforced areas, establishing a reinforced effect feedback closed loop, quantifying time domain characteristics of pulses, distinguishing shielding requirements of different waveforms in the same frequency band, positioning a leakage path based on a waveguide equation, and dividing a core leakage area and an auxiliary protection area. The application provides an electromagnetic shielding method and shielding system for power distribution, significantly improves dynamic adaptability of electromagnetic shielding and detection capability of transient electromagnetic pulses, realizes multi-dimensional risk quantification and differentiated reinforcement strategies. Meanwhile, intelligent materials and a dynamic optimization mechanism are adopted, material utilization and protection effects are improved, and a reinforced effect feedback closed loop is formed.

Description

Technical Field

[0001] This invention relates to an electromagnetic shielding method and shielding system for power distribution, belonging to the field of electromagnetic shielding technology. Background Technology

[0002] Electromagnetic shielding technology is crucial in the power distribution field. Its core objective is to isolate external electromagnetic interference and ensure the stable operation of electronic and electrical equipment within the shielded room. Shielded rooms, as a typical facility for achieving electromagnetic shielding, block the propagation path of electromagnetic waves through physical structures and are widely used in scenarios such as power control and communication base stations.

[0003] However, existing magnetic shielding technologies have significant shortcomings in terms of dynamic adaptability, accurate assessment of leakage risk, and differentiated hardening strategies, making it difficult to meet the protection requirements in complex electromagnetic environments. Current detection technologies lack sufficient accuracy in capturing transient electromagnetic pulses, relying solely on single field strength detection without integrating time-domain characteristic parameters such as pulse width and rise time. This makes it impossible to accurately assess leakage risks in "high-frequency + fast-changing" composite scenarios. For example, narrow pulse signals in the 5G millimeter-wave band can easily form efficient coupling through gaps. For electromagnetic waves in the same frequency band but with different time-domain characteristics, existing technologies have not established a correlation mechanism between waveform characteristics and shielding requirements. For instance, narrow pulse and fast-rise-edge signals carry richer high-frequency components and have a higher leakage risk, but traditional methods only classify risk levels by frequency band, resulting in a "one-size-fits-all" protection strategy. This may fail in high-risk scenarios or waste resources in low-risk scenarios. Existing leakage detection relies on single-point or sparse array sampling, lacking collaborative analysis of field strength, phase, and standing wave distribution in the three-dimensional space of the shielded room, making it difficult to accurately locate waveguide leakage paths (such as gaps and joints) and standing wave antinodes (field strength peak areas). Meanwhile, the risk assessment did not incorporate structural characteristics such as joint density and material electromagnetic parameters, resulting in a blurred division between the core leakage area and the auxiliary protection area, and a lack of spatial targeting in reinforcement measures. Summary of the Invention

[0004] This invention provides an electromagnetic shielding method and shielding system for power distribution, which solves the problems of limitations of static protection mode, insufficient transient electromagnetic pulse detection capability, lack of protection against waveform differences in the same frequency band, and crude leakage path location and risk assessment in the prior art.

[0005] This invention provides an electromagnetic shielding method and system for power distribution, which includes establishing a shielding model corresponding to the shielding room based on the volume data of the shielding room, arranging a 16-channel synchronous sampling electromagnetic wave detection array in the shielding model to simulate and locate the electromagnetic wave situation in the shielding room, using a density clustering algorithm to identify abnormal areas, selecting key detection points, constructing a phase difference matrix to perform a fast Fourier transform on the time-domain phase data to convert it into a frequency-domain distribution, extracting the phase periodic change characteristics at a specific frequency, calculating the standing wave ratio to establish a frequency-distance-attenuation three-dimensional surface model, dividing the reinforcement area into three levels, calculating the deviation between the actual attenuation value and the expected value, and establishing a reinforcement effect feedback closed loop. Pulse parameters are acquired by a 16-channel detection array and a time-domain waveform factor is constructed to quantify the time-domain characteristics of the pulse, distinguish the shielding requirements of different waveforms within the same frequency band, and combine the pulse waveform characteristics with frequency band risks. An electromagnetic risk heat map is generated by calculating the modified impact index, standing wave ratio, and leakage path location based on waveguide equations. High-risk areas of electromagnetic leakage are identified, and the core leakage area and auxiliary protection area are divided by calculating joint density and comprehensive risk score.

[0006] Preferably, a coordinate system is established with one corner of the shielded room as the origin. Based on the three-dimensional rectangular coordinate system, a three-dimensional shielding model corresponding to the shielded room is established in proportion. A 16-channel synchronous sampling electromagnetic wave detection array is arranged, and a signal generation link for transmitting standard electromagnetic waves is built.

[0007] For the 16-channel synchronous sampling electromagnetic wave detection array data, a sliding window denoising method is used to calculate the median of 5 adjacent sampling points, replace outliers with the median, remove noise interference, normalize all field strength data according to frequency band, and mark core points.

[0008] Starting from the core point, merge density-connected points into the same cluster, calculate the average field strength of each cluster, mark the abnormal clusters, select key detection points within the cluster, calculate the phase difference between each detection point, and construct the phase difference matrix.

[0009] Calculate the phase difference between each key detection point, construct a phase difference matrix, and combine the three-dimensional coordinates of the detection points to map the detection point pairs that meet the node and antinode conditions into space. Mark the node and antinode regions of the standing wave, classify the standing wave mode using a clustering algorithm, calculate the phase difference of each segment, locate the complete leakage path through the phase accumulation effect, and mark the confirmed waveguide leakage path in the three-dimensional model of the shielded room.

[0010] The time-domain characteristics of the quantified pulse are used to distinguish the shielding requirements of different waveforms within the same frequency band, set the basic weight of the frequency band, preset the basic risk level according to the electromagnetic wave frequency band, and integrate the basic weight of the frequency band with the time-domain waveform factor.

[0011] The shielded room space is subdivided into a grid, and parameters such as joint density and comprehensive risk score are calculated to divide the core leakage zone and auxiliary protection zone. The reflection phase is adjusted in real time using an adjustable phase metasurface, the synthetic field strength is optimized through a three-dimensional electromagnetic coupling model, and the detection data of each unit group is synchronized through a GPS-disciplined clock source. The scene parameters, optimal reinforcement parameters and weighting coefficients of each leakage event are recorded.

[0012] Three types of heterogeneous attenuation nodes are deployed in the core leakage area and auxiliary protection area of ​​the three-dimensional model of the shielded room. Through the standing wave interference effect, the attenuation increases exponentially with the number of nodes, so that the reflection phase difference between adjacent nodes in the ring topology is fixed at 180°, forming a standing wave node.

[0013] The field strength, phase, and pulse parameters of each node region are collected in real time by a 16-channel detection array. The connection order of the nodes in the ring topology is adjusted. The phase difference matrix and PID algorithm are used to fix the reflection phase difference of adjacent nodes to 180°. A gradient prediction model and a long short-term memory network (LSTM) are constructed. The differential is calculated in real time and the future threat index trend is predicted. The preset topology configuration is automatically selected according to the interference type to form a new ring topology.

[0014] An electromagnetic shielding system for power distribution includes a modeling and positioning module, a data acquisition and signal generation module, a data processing and algorithm module, a shielding reinforcement and dynamic control module, and an intelligent optimization and feedback module. The modeling and positioning module establishes a three-dimensional rectangular coordinate system with the corner of the shielding room as the origin, generates a shielding model on a proportional scale, locates key positions of the shielding room structure, and performs fine spatial discretization. The data acquisition and signal generation module uses a 16-channel synchronous sampling electromagnetic wave detection array to acquire field strength and phase in real time, generate standard test signals and transient pulses, and simulate the real electromagnetic environment. The data processing and algorithm module is used to clean up the raw data, unify the data format, use a sliding window to remove noise, and eliminate outliers. The shielding reinforcement and dynamic control module implements differentiated reinforcement according to risk level, suppresses leakage and standing wave, dynamically adjusts the shielding structure, and enhances multipath interference attenuation; The intelligent optimization and feedback module iteratively optimizes risk assessment parameters using historical data, verifies the hardening effect, drives system self-optimization, and synchronizes timestamps with unit group numbers to track the spatiotemporal distribution of leakage events. The beneficial effects of this invention are: This invention provides an electromagnetic shielding method and system for power distribution. By combining dynamic impact assessment, phase interference analysis, and asymmetric hardening algorithms, it upgrades electromagnetic shielding technology from a "static protection" model to a new paradigm of "dynamic control." This allows the electromagnetic shielding system to adjust its shielding strategy in real time according to changes in the electromagnetic environment, more effectively suppressing electromagnetic interference and improving electromagnetic compatibility. An intelligent optimization and feedback module iteratively optimizes risk assessment parameters using historical data, verifies the hardening effect, and drives system self-optimization. Employing a 16-channel synchronous sampling electromagnetic wave detection array, combined with a dynamic impact assessment algorithm, it can accurately capture transient electromagnetic pulses, solving the problem of insufficient sensitivity in rising edge pulse detection in existing technologies. Through a newly added pulse parameter sensor, it synchronously collects pulse width and rise time, constructs a time-domain waveform factor, quantifies the time-domain characteristics of the pulse, and thus distinguishes the shielding requirements of different waveforms within the same frequency band, improving the accuracy of electromagnetic leakage risk identification. The magnetic wave detection array enables collaborative analysis of field strength, phase, and standing wave distribution in the three-dimensional space of the shielded room, accurately locating waveguide leakage paths (such as gaps and joints) and standing wave antinodes. Combining frequency, time, and spatial dimensions, a five-dimensional comprehensive weight is formed to achieve multi-dimensional risk quantification, making the division of reinforced areas more accurate and scientific. Based on the risk assessment results, the shielded room is divided into three levels: high-risk (Level 1), medium-risk (Level 2), and low-risk (Level 3), and different reinforcement measures are taken. This ensures both protection effectiveness and avoids resource waste. The GPS-disciplined clock source ensures the synchronization of detection data in each unit group, records the scene parameters, optimal reinforcement parameters, and weight coefficients of each leakage event, forming a closed loop of reinforcement effect feedback, enabling the system to learn and optimize itself. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the electromagnetic shielding method and shielding system for power distribution according to the present invention.

[0016] Figure 2 This is a schematic diagram of the structure of an electromagnetic shielding method and shielding system for power distribution according to the present invention. Detailed Implementation

[0017] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0018] Example 1: This invention provides an electromagnetic shielding method for power distribution, which includes acquiring the volume data of a shielded room, establishing a three-dimensional rectangular coordinate system based on the volume data of the shielded room, establishing a shielding model corresponding to the shielded room in proportion to the three-dimensional rectangular coordinate system, marking the locations where electromagnetic wave experiments need to be conducted in the shielding model, and recording the marked points as simulation points. Perpendicular lines are drawn from the simulation points to the six faces of the shielding model, and the intersection of the shortest perpendicular line with a face is recorded as a face point. Perpendicular lines are drawn from the electromagnetic simulation points to the twelve edges of the shielding model, and the intersection of the shortest perpendicular line with an edge is recorded as an edge point. The electromagnetic simulation points are connected to the eight vertices of the shielding model, and the vertex corresponding to the shortest connection line is recorded as a corner point. A 16-channel synchronous sampling electromagnetic wave detection array is uniformly arranged at the corresponding face points, edge points, and corner points within the shielding room to conduct a standard electromagnetic wave experiment. A signal generation link is established, the carrier frequency is scanned in 1% increments, each frequency point is maintained for 60 seconds, the antenna polarization is alternating between vertical and horizontal, and the field strength values ​​of the 16 channels are recorded synchronously to generate a frequency domain field strength distribution map. A dual exponential pulse source was constructed, with the following pulse parameters: rise time tr: 1ns; pulse width tw: 50ns (half-width at half maximum); peak voltage: 6kV. A transverse electromagnetic wave chamber was used to inject the pulses. A GPS-disciplined clock source was employed to ensure that the multi-channel sampling time deviation was ≤1ns. A sliding window denoising method was used: for each sensor data point, the median of the five adjacent sampling points was calculated to replace outliers. All field strength data were normalized to the [0,1] interval according to frequency bands. Specifically:

[0019] in: Minimum field strength in the current frequency band; : Maximum field strength in the current frequency band; If there are ≥MinPts points in the ε neighborhood of a certain point, mark it as the core point. Starting from the core point, merge the densely connected points into the same cluster. Calculate the average field strength of each cluster. If it exceeds 3 times the global average, mark it as an abnormal region, i.e., an abnormal cluster. For the abnormal cluster, select the average coordinates of all points in the cluster and the two points in the cluster that are farthest from the centroid as key detection points. Establish a three-dimensional electromagnetic field distribution model. Initially divide the shielded room into 1m³ cubes and perform octree spatial segmentation. Predict the field strength of unmeasured locations based on the data of neighboring detection points. Randomly select 10% of the detection points that are not used for modeling and calculate the prediction error. If the error is >2dB, refine the mesh of the region and re-interpolate. Construct the phase difference matrix, specifically:

[0020] in: : The instantaneous phase of the i-th detection point; : The instantaneous phase of the j-th detection point; N: Total number of detection points; If the phase difference Then the two points are located in the same half-wavelength region of the standing wave, and there exists a point of maximum field strength (antinode) in between; if the phase difference between the two points is... If the two points are located in different half-wavelength regions of the standing wave, there is a minimum field strength point (node) in between. Perform a Fast Fourier Transform (FFT) to convert the time-domain phase data into a frequency-domain distribution, extract the periodic phase variation characteristics at a specific frequency, and calculate the Standing Wave Ratio (SWR). Specifically:

[0021] in: : Reflection coefficient; By combining the three-dimensional coordinates of the detection points, the detection points that meet the conditions of nodes and bulla points are mapped into space, and the node regions (field strength troughs) and bulla point regions (field strength peaks) of the standing wave are marked. Based on the spatial distribution and characteristic frequency of nodes and bulla points, a clustering algorithm is used to classify the standing wave patterns, and for each type of standing wave pattern, its corresponding high-risk area is marked. Calculate the impact index for each detection point, specifically:

[0022] in: Peak field strength; : Rate of change of electric field strength; Distance to the interference source is obtained through 3D model localization; Leakage paths are analyzed using waveguide equations, where the leakage paths are structures such as gaps, holes, or joints within the shielded room. Specifically:

[0023] in: Maximum gap size; : Permeability; Dielectric constant; By associating the geometric parameters of the waveguide structure with the three-dimensional coordinates of the detection point, a spatial position mapping relationship is established. Starting from the potential interference source outside the shielding room, the phase change is tracked along the equivalent path of the waveguide. For complex structures, the phase difference of each segment is calculated in segments. The complete leakage path is located through the phase accumulation effect. The confirmed waveguide leakage path is marked in the three-dimensional model of the shielding room. Establish a three-dimensional surface model of frequency-distance-attenuation, and select detection points in the three-dimensional space of the shielded room to define three orthogonal directions with each point as the center: X-axis (length direction), Y-axis (width direction), and Z-axis (height direction). For each detection point, electromagnetic wave attenuation data were collected under different conditions. Specifically, the frequency range was 0.1-40GHz (in 0.1GHz increments, covering 5G millimeter wave and traditional communication frequency bands); the distance range was the distance d from the detection point to the shielding wall; and the polarization direction was vertical polarization, horizontal polarization, and circular polarization. For each direction (X / Y / Z) and polarization state, calculate the attenuation in decibels. For a single polarization direction, calculate the omnidirectional average attenuation at each frequency f and distance d, and convert the attenuation in decibels to a linear attenuation factor. For the target direction (e.g., X-axis) and polarization direction (e.g., vertical polarization), calculate the anisotropy correction coefficient. Specifically:

[0024] The comprehensive weighting calculation is as follows:

[0025] in: , , These are adaptive weighting coefficients; The reinforcement zones are divided into three levels based on weight W: Level 1 is high-risk. (For example, standing wave antinodes and waveguide leakage inlets) are reinforced using a three-stage method: Base layer: applying conductive adhesive to fill gaps and enhance conductivity continuity; Middle layer: laying a high-density copper mesh to suppress high-frequency leakage; Top layer: attaching absorbing material to eliminate standing wave field strength peaks; Secondary medium-risk: (e.g., ordinary seams, non-critical waveguide structures), base layer: conductive adhesive, intermediate layer: low-density copper mesh balancing cost and high-frequency attenuation; Level 3 low risk: (For example, in the central area of ​​a complete shielding plate) basic reinforcement is applied with only conductive adhesive to ensure basic conductivity continuity; in: This represents the maximum weight of all detection points in the current experiment. After reinforcement, field strength data at each point is collected in real time using a 16-channel detection array. The deviation between the actual attenuation value and the expected value is calculated to establish a feedback loop for the reinforcement effect. Historical reinforcement data is collected, and the weighting coefficients are optimized using the Q-learning algorithm. , , The weighting coefficients are automatically updated after every 5 experiments.

[0026] In practical use, the length, width, and height of the shielded room are measured to determine its volume. A coordinate system is established with one corner of the shielded room as the origin, and the length, width, and height directions as the X, Y, and Z axes, respectively. Based on the three-dimensional rectangular coordinate system, a three-dimensional shielding model corresponding to the shielded room is built to scale. In the shielding model, the locations where electromagnetic wave experiments will be conducted are marked, and these marked points are recorded as simulation points. Perpendicular lines are drawn from each simulation point to each of the six faces of the shielding model, and the intersection of the shortest perpendicular line with a face is recorded as a face point. Perpendicular lines are drawn from each simulation point to each of the twelve edges of the shielding model, and the intersection of the shortest perpendicular line with an edge is recorded as an edge point. Each simulation point is connected to each of the eight vertices of the shielding model, and the vertex corresponding to the shortest connection line is recorded as a corner point. A 16-channel synchronous sampling electromagnetic wave detection array is evenly arranged at the actual locations corresponding to the face points, edge points, and corner points determined in the model within the shielded room, establishing a signal generation link for transmitting standard electromagnetic waves. The frequency was scanned in 1% increments to cover the relevant frequency bands. Each frequency point was maintained for 60 seconds. The antenna polarization was alternating between vertical and horizontal. During the experiment, a 16-channel synchronous sampling electromagnetic wave detection array was used to synchronously record the field strength values ​​of each channel, generating a frequency domain field strength distribution map. The pulse parameters were set as follows: rise time tr = 1 ns, pulse width tw = 50 ns (half-width at half maximum), and peak voltage = 6 kV. A transverse electromagnetic wave chamber was used to inject the pulse, and a GPS-disciplined clock source was used to ensure that the sampling time deviation of the multi-channel was ≤1 ns, thus ensuring the time consistency of data acquisition for each channel. For the data acquired by each sensor, a sliding window denoising method was used to calculate the median of 5 adjacent sampling points. The median was used to replace outliers to remove noise interference. All field strength data were normalized according to frequency bands. A density clustering algorithm was used to mark points with ≥MinPts points in their ε-neighborhood as core points. Starting from the core points, density-connected points were merged into the same cluster. The average field strength of each cluster is calculated. If it exceeds three times the global average, the cluster is marked as an anomalous region (abnormal cluster). For abnormal clusters, the average coordinates of all points within the cluster are selected as the centroid, and the two points farthest from the centroid are selected as key detection points. The shielded room is initially divided into 1m³ cubes using an octree spatial partitioning method. Based on data from neighboring detection points, the field strength at unmeasured locations is predicted. 10% of the detection points not used for modeling are randomly selected, and the prediction error is calculated. If the error is >2dB, the mesh of that area is refined and re-interpolated to improve prediction accuracy. The phase difference between each detection point is calculated, and a phase difference matrix is ​​constructed. If the phase difference... Then the two points are located in the same half-wavelength region of the standing wave, and there exists a point of maximum field strength (antinode) in between; if the phase difference between the two points is... If two points are located in different half-wavelength regions of the standing wave, with a minimum field strength point (node) in between, a fast Fourier transform is performed on the time-domain phase data to convert it into a frequency-domain distribution. The periodic phase variation characteristics at a specific frequency are extracted, the standing wave ratio is calculated, and the detection points that meet the node and antinode conditions are mapped into space, marking the node region (field strength trough) and antinode region (field strength peak) of the standing wave. A clustering algorithm is used to classify the standing wave modes, and for each type of standing wave mode, its corresponding high-risk region is marked. For each detection point, the impulse index is calculated to assess the impact of transient electromagnetic pulses. Waveguide equations are used to analyze the leakage paths of gaps, holes, or joints in the shielded room. By associating the geometric parameters of the waveguide structure with the three-dimensional coordinates of the detection points, a spatial position mapping relationship is established. Starting from the potential interference source outside the shielded room, the phase change is tracked along the equivalent path of the waveguide. For complex structures, the phase difference of each segment is calculated segment by segment. The complete leakage path is located through the phase accumulation effect. In the three-dimensional model of the shielded room, the confirmed waveguide leakage path is marked. Detection points are selected in the three-dimensional space of the shielded room, and three orthogonal directions are defined with each point as the center: X-axis (length direction), Y-axis (width direction), and Z-axis (height direction). Electromagnetic wave attenuation data are collected under different conditions. For each direction (X / Y / Z) and polarization state, the attenuation decibel value is calculated and converted into a linear attenuation factor. For a single polarization direction, the omnidirectional average attenuation value at each frequency f and distance d is calculated. For the target direction (such as the X-axis) and polarization direction (such as vertical polarization), the anisotropy correction coefficient is calculated. The comprehensive weight of each detection point is calculated, and three-level reinforcement zones are divided. The first-level high-risk zone adopts three-level reinforcement. Conductive adhesive is applied to the base layer to fill gaps and enhance conductivity continuity; a high-density copper mesh is laid in the middle layer to suppress high-frequency leakage; and absorbing material is pasted on the surface layer to eliminate peak standing wave intensity. In the secondary medium-risk area, conductive adhesive is used on the base layer, and a low-density copper mesh is laid in the middle layer to balance cost and high-frequency attenuation. In the tertiary low-risk area, basic reinforcement is adopted, with only conductive adhesive applied to ensure basic conductivity continuity. After reinforcement, field strength data at each point is collected in real time through a 16-channel detection array. The deviation between the actual attenuation value and the expected value is calculated to establish a feedback loop for reinforcement effect. Historical reinforcement data is collected, and the weight coefficients are optimized using the Q-learning algorithm. After every 5 experiments, the weight coefficients are automatically updated to continuously improve the reinforcement effect and system performance.

[0027] Compared with existing technologies, by establishing a three-dimensional rectangular coordinate system and a scaled shielding model, the electromagnetic wave situation inside the shielding room can be accurately simulated and located. The arrangement of a 16-channel synchronous sampling electromagnetic wave detection array can comprehensively and synchronously record the field strength values ​​inside the shielding room, generating a frequency domain field strength distribution map, improving detection accuracy and efficiency. The detection dimension is expanded from single intensity to a four-dimensional fusion of intensity, phase, time domain, and spectrum, significantly improving standing wave positioning accuracy. This helps to more accurately identify and solve electromagnetic interference problems. The use of density clustering algorithms to identify anomalous regions (anomalous clusters) and selecting key detection points for these clusters helps to accurately identify and address weak points in electromagnetic wave shielding. Based on the impulse index and standing wave of the detection points... This approach allows for further delineation of high-risk areas and the implementation of corresponding reinforcement measures to improve shielding effectiveness. Using an octree spatial segmentation method and neighboring detection point data to predict the field strength at unmeasured locations improves prediction accuracy and reduces experimental costs. By establishing a feedback loop for reinforcement effects, collecting historical reinforcement data, and optimizing weighting coefficients, the reinforcement scheme can be continuously optimized, improving system performance. This upgrades electromagnetic shielding technology to a "dynamic control" paradigm, enabling real-time adjustments to the shielding strategy based on changes in the electromagnetic environment, thereby more effectively suppressing electromagnetic interference and improving electromagnetic compatibility. The dynamic impulse assessment algorithm accurately captures transient electromagnetic pulses, addressing the insufficient sensitivity issue in rising-edge pulse detection in existing technologies. This contributes to improving the response speed and accuracy of electromagnetic shielding systems to transient electromagnetic pulses.

[0028] Example 2: In the above examples, by combining dynamic impact assessment, phase interference analysis and asymmetric hardening algorithm, electromagnetic shielding technology is upgraded from "static protection" to a new paradigm of "dynamic control". However, by using only a fixed frequency band weighting factor F, it is impossible to distinguish electromagnetic waves with different time domain characteristics within the same frequency band, resulting in inaccurate protection strategies. The embodiments of this application are optimized based on the above embodiments.

[0029] In this embodiment, a pulse parameter sensor is added to the 16-channel detection array. The pulse width (PW) and rise time (RT) are extracted from the pulse source parameters, where PW is the full width at half maximum (FWHM) pulse width and RT is the rise time of 10%–90% of the amplitude. A time-domain waveform factor is constructed based on the pulse width and rise time, specifically:

[0030] Narrow pulses (smaller PW) and short rise times (smaller RT) correspond to higher high-frequency components, exacerbating the risk of electromagnetic leakage. TWF is inversely proportional to PW and RT, enhancing the sensitivity to narrow pulses and fast rise time waveforms. The basic weight F is set according to the electromagnetic wave frequency band: traditional communication frequency band F=1.0; 5G millimeter wave frequency band F=1.5; ultra-high frequency band F=2.0; Multiply the frequency band base weights by the time-domain waveform factor to form the joint weights. Specifically:

[0031] Among them, high-frequency bands (such as millimeter waves) can simultaneously have narrow pulse wave (PW) and short response time (RT) (such as 5G data transmission pulse). This will significantly increase the accuracy of identifying high-risk scenarios that combine "high frequency and rapid changes"; The joint weighting will be introduced into the revised shock index, specifically as follows:

[0032] A pulse parameter sensor was added to the 16-channel detection array to simultaneously acquire pulse wave (PW) and pulse retrieval (RT); the corrected impulse index was calculated in real time for each detection point.

[0033] Impact on the index after the addition and correction of the comprehensive weight W This forms a four-dimensional comprehensive weight, specifically:

[0034] in: : This is the impact index weighting coefficient (this is the impact index weighting coefficient).

[0035] By quantizing the pulse time-domain characteristics through TWF, the shielding requirements of different waveforms within the same frequency band are distinguished. The dynamic weight F' couples the frequency band and time domain, amplifying the risk of narrow pulse width and fast rise edge characteristics of high-frequency bands such as millimeter waves, and adapting to the physical characteristics of "high frequency easy leakage".

[0036] In use, by utilizing the newly added pulse parameter sensor in the 16-channel detection array, the pulse width at half maximum (PW) and the rise time (RT) of the pulse signal (10%–90% amplitude) are simultaneously acquired. The sensor works synchronously with the 16-channel electromagnetic wave detection array to ensure that the PW and RT data are time-aligned with data such as field strength and phase. A time-domain waveform factor (TWF) is constructed. The smaller the PW (narrow pulse) and the smaller the RT (fast rise time), the larger the TWF value, which characterizes the richer high-frequency components and the higher the electromagnetic leakage risk. A basic weight for each frequency band is set, and a basic risk level is preset according to the electromagnetic wave frequency band. The basic weight of the frequency band is then fused with the time-domain waveform factor. The domain waveform factor introduces joint weights into the impact index formula in Example 1. For each detection point, the corrected impact index is dynamically calculated based on the real-time acquired PW, RT, and field strength data. Through TWF and F', the pulse waveform characteristics (PW / RT) are combined with the frequency band risk (F) to solve the problem of inaccurate protection strategies for different waveforms within the same frequency band. Based on the three-dimensional weights in Example 1, a new corrected impact index is added to form a five-dimensional weight, realizing multi-dimensional risk quantification of "frequency domain + time domain + space". The reinforcement area division follows the three-level reinforcement strategy, but the weight calculation incorporates the newly added corrected impact index.

[0037] Compared to existing designs, this new paradigm upgrades electromagnetic shielding from "static protection" to "dynamic control" by combining dynamic impact assessment, phase interferometry analysis, and asymmetric hardening algorithms. This makes electromagnetic shielding more flexible and efficient, adaptable to electromagnetic interference under different environments and conditions. A pulse parameter sensor has been added to the 16-channel detection array, enabling simultaneous acquisition of the pulse width at half maximum (PW) and rise time (RT) of the pulse signal from 10% to 90%, and constructing a time-domain waveform factor (TWF) based on these parameters. TWF quantifies the time-domain characteristics of the pulse, distinguishing the shielding requirements of different waveforms within the same frequency band, thereby improving the accuracy of electromagnetic leakage risk identification. The frequency band base weight is multiplied by the time-domain waveform factor to form a joint weight (F'), which is then introduced into the corrected impact index. Each detection point can dynamically calculate the corrected impact index based on real-time acquired PW, RT, and field strength data. By combining TWF and F' with pulse waveform characteristics (PW / RT) and frequency band risk (F), the problem of inaccurate protection strategies for different waveforms within the same frequency band is solved. Meanwhile, a modified impact index was added on the basis of the three-dimensional weight to form a five-dimensional weight, realizing multi-dimensional risk quantification of "frequency domain + time domain + space", making the division of reinforcement areas more accurate and scientific.

[0038] Example 3: In the above examples, the pulse waveform characteristics (PW / RT) and frequency band risk (F) are combined through TWF and F', which solves the problem of inaccurate protection strategies for different waveforms in the same frequency band. However, it cannot suppress waveguide leakage and cavity resonance. The embodiments of this application are optimized based on the above examples.

[0039] In this embodiment, a 16-channel detection array is used to synchronously acquire the field strength E and phase at each detection point. Calculate the corrected impact index using pulse width PW and rise time RT. Electromagnetic risk heat maps for each region are generated by combining the standing wave ratio and leakage path location results based on waveguide equations. Calculate the total length of seams per unit volume to reflect the structural weakness of the shielded room, based on the waveguide cutoff frequency. Waveguide risk level is determined by the degree of overlap with the operating frequency range: High risk ( <10)GHz), medium risk ( =10-20GHz), low risk ( >20GHz); Using the corner of the shielded room as the origin, a cubic grid is divided along the X, Y, and Z axes at a resolution of 1 m³, covering the entire shielded room space to generate an initial grid set. An octree partitioning algorithm is then applied to the initial grid, dividing it into 8 equal sub-grids, until the resolution is refined to 0.25 m³, forming a refined grid set. The total length of the seams within each grid is then collected. Maximum gap size Material permeability Dielectric constant Field strength was acquired using a 16-channel detection array. Phase Pulse width Ascent time Simultaneously record the distance from the interference source

[0040] The integrity of the shielding structure within the mesh is reflected by calculating the joint density. Specifically:

[0041] in: : represents the mesh volume; The higher the seam density, the denser the waveguide leakage paths. The corrected impact index for a single detection point is calculated as follows: ,

[0042] in: : Basic weights for frequency bands (traditional communication frequency bands) Millimeter wave = 1.5, ultra-high frequency = 2.0); The grid mean is calculated as follows:

[0043] in: : This represents the number of detection points within the grid; The standing wave ratio (SWR) of a single detection point is calculated as follows:

[0044] in: : represents the reflection coefficient; Grid extrema: This reflects the extreme risk of the peak value of the standing wave field within the grid; The comprehensive risk score is calculated as follows:

[0045] in: : : The weights are 3:4:3; Using joint density and comprehensive risk score as two-dimensional feature space, a neighborhood radius is set. The minimum number of core points, MinPts, is 3. The mark satisfies The area with ≥MinPts high-risk grids in the neighborhood is the core leakage zone. One grid is extended outward from the core zone, and the adjacent area with a joint density ≥20cm / m³ is included as the auxiliary protection zone, forming a unit group structure of 1 core + 3-5 auxiliary. The unit group structure is checked to see if it contains a complete leakage path. If there is a break, the adjacent grids are automatically merged based on the spatial connectivity of the 3D model until the path is closed. For each unit group, a three-dimensional electromagnetic coupling model is established, where the coupling strength matrix is ​​specifically:

[0046] in: : Indicates a region arrive The electromagnetic wave coupling efficiency; the larger the value, the stronger the coupling. Phase difference between the core area and auxiliary area within the formation By deploying an tunable phase metasurface in the auxiliary region, the reflection phase can be adjusted in real time to increase the combined field strength within the group. ; The field strength E and phase of each detection point within the unit group are simultaneously acquired using a 16-channel detection array. Pulse parameters (PW / RT) are updated every 1μs. Constructing a 3D protection matrix model: ,in For spatial coordinates, For frequency, To ensure time synchronization, a three-tiered reinforcement layer (conductive adhesive + high-density copper mesh + absorbing material) is deployed in the core area of ​​the unit group, and a two-tiered reinforcement layer (conductive adhesive + low-density copper mesh) is deployed in the auxiliary area, forming a cascaded structure of strong attenuation in the core and weak attenuation in the auxiliary area. A GPS-disciplined clock source ensures synchronization of detection data from each unit group. A timestamp is added to the data at each detection point, and time window matching is used to synchronize the field strength E and phase. The pulse parameters (PW / RT) are bound to the corresponding unit group number in real time, recording the scene parameters of each leakage event, the optimal reinforcement parameters, and saving the weight coefficients during training. , , The curve of change will automatically adjust the corresponding weight when a certain type of scenario occurs more than 5 times.

[0047] During use, the field strength E and phase of each detection point in the shielded room are simultaneously acquired using a 16-channel detection array. The pulse width PW and rise time RT are recorded, and the distance D from each point to the interference source is recorded. The waveguide cutoff frequency is calculated simultaneously. ,according to The waveguide risk level is determined by the overlap with the operating frequency. A cubic mesh is generated with the corner of the shielded room as the origin and a resolution of 1 m³. An initial mesh set is then generated by performing an octree partitioning algorithm on the initial mesh, successively dividing it into 8 equal sub-mesh sets until the resolution is refined to 0.25 m³, forming a refined mesh set. The structural parameters of each mesh are collected, including the total joint length. Maximum gap size Material permeability Dielectric constant The algorithm calculates grid seam density, single-detection-point corrected impact index, single-detection-point standing wave ratio (SWR), and grid extreme SWR. It integrates the risk score with seam density, average impact index, and extreme SWR, using seam density and the comprehensive risk score as two-dimensional features. A density clustering algorithm is employed to divide the core leakage zone into core and auxiliary protection zones. One grid is expanded outward from the core zone, incorporating neighboring areas as auxiliary protection zones, forming a "1 core + 3-5 auxiliary" unit group structure. Based on the spatial connectivity of the 3D model, adjacent grids are automatically merged to ensure leak path closure. A 3D electromagnetic coupling model of the unit group is established. Adjustable-phase metasurfaces deployed in the auxiliary zone are used to adjust the reflection phase in real time, ensuring a phase difference between the core and auxiliary zones. To achieve the synthetic field strength To suppress electromagnetic leakage, the detection data of each unit group is synchronized by using a GPS-disciplined clock source. A timestamp is added to each detection point and the unit group number is bound. The detection array updates the data every 1μs and feeds it back to the protection system in real time. The scene parameters, optimal hardening parameters and weighting coefficients of each leakage event are recorded.

[0048] Compared with existing technologies, the 16-channel detection array synchronously acquires field strength E and phase. Multiple parameters, such as pulse width (PW) and rise time (RT), enable a more comprehensive assessment of electromagnetic risks. By calculating the corrected impulse index, standing wave ratio (VSWR), and leakage path location based on waveguide equations, an electromagnetic risk heat map is generated, making risk assessment more intuitive and accurate. An octree segmentation algorithm is used to refine the shielded room space into a 0.25m³ grid, enabling more precise identification of high-risk areas for electromagnetic leakage. By calculating parameters such as joint density and comprehensive risk score, combined with a density clustering algorithm, the core leakage area and auxiliary protection area can be accurately delineated, providing a scientific basis for subsequent reinforcement measures. Adjustable... The phase metasurface adjusts the reflection phase in real time and optimizes the synthetic field strength through a three-dimensional electromagnetic coupling model to achieve intelligent suppression of electromagnetic leakage. A GPS-disciplined clock source ensures the synchronization of detection data in each unit group, and records the scene parameters, optimal hardening parameters, and weight coefficients of each leakage event, enabling the system to learn and optimize its protection strategy. A cascaded structure of "core strong attenuation - auxiliary weak attenuation" is used for hardening, which can more effectively reduce electromagnetic leakage and save hardening costs compared to existing designs. By intelligently identifying high-risk areas and prioritizing hardening, the efficiency of hardening is improved and unnecessary resource waste is reduced.

[0049] Example 4: In the above examples, the electromagnetic leakage was effectively reduced and the reinforcement cost was saved by using a cascaded structure of "core strong attenuation - auxiliary weak attenuation". However, the attenuation efficiency in the millimeter wave band and the dynamic scene are difficult to cope with transient strong interference. The embodiments of this application are based on the above embodiments and are optimized to a certain extent.

[0050] In this embodiment, three types of heterogeneous attenuation nodes are deployed in the core leakage area and auxiliary protection area of ​​the three-dimensional model of the shielded room: For the high-frequency millimeter wave band such as 28GHz, a graphene conductive film with a thickness of 5μm is deployed at the apex of the ring topology, covering an area of ​​50%, and its high conductivity is used to realize the surface reflection and skin effect loss of high-frequency electromagnetic waves. Ferrite magnetic sheets are deployed in areas with dense edges and seams, covering 33% of the area, and absorb low-frequency interference below 1GHz through magnetic loss. Plasma discharge units are embedded in the standing wave antinode region, covering an area of ​​17%, and respond to transient pulses such as EMP through ionized gas. Centered on the core leakage region, three adjacent graphene nodes, two ferrite nodes, and one plasma node are connected by conductive copper strips to form a hexagonal ring topology. Each node is equipped with an adjustable phaser to achieve multipath reflection of electromagnetic waves in the ring path, and the total attenuation is calculated. Specifically:

[0051] in: : The number of nodes in the ring; : Reflection coefficient of each node; Through the standing wave interference effect, the attenuation increases exponentially with the number of nodes. By synchronizing the phasers of each node with a GPS servo clock source, the reflection phase difference between adjacent nodes in the ring topology is fixed at 180°, thus forming a standing wave node. Real-time acquisition frequency of detection points Through waveguide cutoff frequency Determine the dominant leakage mode when >10GHz: Graphene nodes account for 60%, ferrite nodes decrease to 25%, and plasma nodes reach 15%, enhancing high-frequency reflection; when ≤1GHz ​​(low frequency band): Ferrite node ratio increased to 50%, graphene 30%, plasma 20%, enhanced magnetic loss; When a transient pulse with rise time RT < 5ns is detected: Plasma node ratio increased to 40%, graphene 40%, ferrite 20%, preferential response to fast pulses; Using the phase difference matrix For any two nodes in a ring topology Make a judgment, if If determined to be a valid interference pair, the phaser is adjusted using a PID algorithm to... Approaching 180° maximizes coverage of the standing wave node region; Calculate the joint density for each grid cell for SD > 30 cm / m³ and For high-risk meshes with a diameter >0.8, the graphene node density is increased by 20% (coverage area increases from 50% to 60%), the ferrite node density is reduced by 10%, and high-frequency leakage paths are prioritized for enhancement. For SD≤10cm / m³ and With a low-risk grid of ≤0.5, the proportion of plasma nodes is reduced to 10%, reducing redundant deployment and increasing material utilization from 60% to 85%. The 16-channel detection array acquires the field strength E and phase of each node region every 1μs. Pulse parameters (PW / RT) are used to calculate the actual attenuation, specifically A = measured value. ; If |A_measured - A_total| > 3dB, a self-optimization mechanism is triggered to adjust the reflection coefficients of graphene, ferrite, and plasma nodes, correct the node connection order in the ring topology, and automatically update the optimal ratio parameters after every 5 feedbacks. The current frequency band f, pulse width PW, and rise time RT are obtained using a 16-channel detection array, and the joint weight of the frequency band and time domain is calculated. Building a gradient prediction model The differential is calculated in real time through a sliding window (1 μs wide), triggering a dynamic reconstruction mechanism. A Long Short-Term Memory (LSTM) network is used to train the history. The sequence predicts the threat index trend over the next 5 μs, triggering reconstruction preparation in advance. It presets three typical topology configurations: high-frequency mode (6-node all-graphene ring connection, 180° phase difference, 82dB attenuation); low-frequency mode (3 ferrite + 2 graphene + 1 plasma ring connection, 150° phase difference, 65dB attenuation); and transient mode (4 plasma + 2 graphene ring connections, 180° phase difference, 5μs response time, 4x improved immunity). When a threat index trend is detected... If the corresponding threshold is exceeded or the LSTM predicts an increase in the threat level, a reconfiguration is immediately initiated, the existing ring topology links are cut off, a preset topology configuration is automatically selected according to the type of interference, a new ring topology is formed, the optimal parameters of each reconfiguration are recorded, and the FPGA configuration file is automatically updated after every 10 effective reconfigurations.

[0052] In use, the area with the most severe electromagnetic leakage in the 3D model of the shielded room is used as the core, and auxiliary protection zones are divided outwards. A 5μm thick graphene conductive film is deployed at the apex of the ring topology, with an initial coverage area of ​​50%. For high-frequency millimeter-wave bands such as 28GHz, high conductivity is used to achieve surface reflection and skin effect loss. Ferrite magnetic sheets are deployed at the edges and densely packed seams, with an initial coverage area of ​​33%, absorbing low-frequency interference below 1GHz through magnetic loss. Plasma discharge units are embedded in the standing wave antinode region, with an initial coverage area of ​​17%, using ionized gas to instantaneously respond to transient pulses such as EMP. Centered on the core leakage area, three adjacent graphene nodes, two ferrite nodes, and one plasma node are connected by conductive copper strips to form a hexagonal ring structure. Each node is equipped with an adjustable phaser. By connecting to a GPS clock source, the initial phase difference between reflections from adjacent nodes is fixed at 180°, forming standing wave nodes. A 16-channel detection array is used to collect parameters of each node region in real time with a period of 1μs. The actual attenuation and seam density of each grid are calculated. The phase difference matrix is ​​used to determine the phase difference between any two nodes. A PID algorithm is employed to adjust the phase difference to approach 180°, maximizing the coverage of the standing wave node region and enhancing multipath reflection attenuation. The measured attenuation is compared with the theoretical calculation in real time, automatically adjusting the reflection coefficients of graphene, ferrite, and plasma nodes, correcting the node connection order in the ring topology, and updating the optimal ratio parameters after every 5 feedback iterations. A gradient prediction model is constructed, and the differential is calculated in real time using a 1μs sliding window to detect the threat index change rate. A Long Short-Term Memory (LSTM) network is used to train the historical data. The sequence predicts the threat index trend over the next 5 μs, with three typical topologies preset. When the corresponding threshold is exceeded or the LSTM predicted threat level increases, the existing link is immediately cut off, a preset topology is automatically selected according to the interference type to form a new ring topology, the optimal parameters of each reconstruction are recorded, and the FPGA configuration file is automatically updated after every 10 effective reconstructions.

[0053] Compared to existing designs, this design utilizes a 5μm thick graphene conductive film with high conductivity to achieve surface reflection and skin effect loss of high-frequency electromagnetic waves, effectively reducing electromagnetic leakage. For low-frequency interference below 1GHz, ferrite magnetic sheets are deployed at edge points and densely packed seams to absorb interference using magnetic loss, improving low-frequency protection. Plasma discharge units are embedded in the standing wave antinode region, using ionized gas to instantaneously respond to transient pulses such as EMP, enhancing protection against strong transient interference. A 16-channel detection array collects the field strength, phase, and pulse parameters of each node region in real time, and automatically adjusts the reflection coefficients of graphene, ferrite, and plasma nodes and the connection order of nodes in the ring topology based on real-time data, achieving intelligent dynamic optimization. The difference matrix and PID algorithm fix the reflection phase difference between adjacent nodes to 180°, forming standing wave nodes, which enhances the multipath reflection attenuation effect. Based on real-time data and prediction models, the coverage area ratio of different nodes is automatically adjusted to optimize material utilization. The graphene node density is increased in high-risk grids, while the proportion of plasma nodes is reduced in low-risk grids, thereby improving material utilization and saving costs. By constructing a gradient prediction model and a long short-term memory network (LSTM), the differential is calculated in real time and the future threat index trend is predicted. When the corresponding threshold is exceeded or the LSTM predicts an increase in the threat level, the reconstruction mechanism is immediately activated. The preset topology configuration is automatically selected according to the interference type to form a new ring topology, which improves the system's response speed and anti-interference ability.

[0054] Example 5: This invention provides an electromagnetic shielding system for power distribution, comprising a modeling and positioning module, a data acquisition and signal generation module, a data processing and algorithm module, a shielding reinforcement and dynamic control module, and an intelligent optimization and feedback module. The modeling and positioning module establishes a three-dimensional rectangular coordinate system with the corner of the shielded room as the origin, and generates a shielding model proportionally. Simulation points are marked, and face points, edge points, and apex points are determined through geometric operations to locate key structural positions of the shielded room. The system also performs refined spatial discretization, supporting high-precision analysis of local areas. Initially divided into 1m³ cubes, the system uses an octree algorithm to progressively subdivide to a resolution of 0.25m³. The structural parameters of each grid are associated. The data acquisition and signal generation module uses a 16-channel synchronous sampling electromagnetic wave detection array to acquire field strength and phase in real time; a new pulse parameter sensor is added to obtain pulse width and rise time; standard test signals and transient pulses are generated to simulate real electromagnetic environment; The data processing and algorithm module is used to purify the raw data, unify the data format, use sliding window noise reduction, and remove outliers; frequency band normalization maps the field strength to the [0,1] interval; fast Fourier transform (FFT) converts the time domain phase to the frequency domain distribution, extracts the phase periodicity features, identifies key features and abnormal areas of electromagnetic leakage, predicts the field strength of unmeasured areas, and quantifies the three-dimensional spatial risks. The shielding reinforcement and dynamic control module implements differentiated reinforcement according to risk level, suppresses leakage and standing wave, dynamically adjusts the shielding structure, and enhances multipath interference attenuation; The intelligent optimization and feedback module iteratively optimizes risk assessment parameters using historical data, verifies the reinforcement effect, drives system self-optimization, and synchronizes timestamps to unit group numbers to track the spatiotemporal distribution of leakage events.

[0055] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. An electromagnetic shielding method for power distribution, characterized in that: include: Based on the volume data of the shielded room, a shielding model corresponding to the shielded room is established. A 16-channel synchronous sampling electromagnetic wave detection array is arranged in the shielding model to generate a frequency domain field strength distribution map. A dual exponential pulse source was constructed to inject pulses, and a density clustering algorithm was used to identify abnormal regions. Key detection points were selected, and a three-dimensional electromagnetic field distribution model was established. Based on a three-dimensional electromagnetic field distribution model, a phase difference matrix is ​​constructed, and a fast Fourier transform is performed to convert the time-domain phase data into a frequency-domain distribution. The phase periodic change characteristics at a specific frequency are extracted, and the standing wave ratio is calculated. By combining three-dimensional coordinate annotation of the nodal and antinode regions of standing waves, standing wave patterns are classified and high-risk areas are marked. For high-risk areas, the impact index of each detection point is calculated, the leakage path is analyzed using waveguide equations, and the complete leakage path is located through phase accumulation effect; A three-dimensional surface model of frequency-distance-attenuation is established. Detection points are selected within the three-dimensional space of the shielded room. Three orthogonal directions are defined with each point as the center. For each direction and polarization state, the attenuation value in decibels is calculated. For a single polarization direction, calculate the omnidirectional average attenuation value at each frequency and distance, convert the attenuation decibel value into a linear attenuation factor, and calculate the anisotropy correction coefficient for the target direction and polarization direction. The calculation formula is: ; The overall weight is obtained by combining the impact index, phase difference, and anisotropy correction coefficient; Pulse parameters are acquired by a 16-channel detection array and a time-domain waveform factor is constructed. The frequency band base weight is multiplied by the time-domain waveform factor to form a joint weight. By introducing joint weights into the modified impact index, the modified impact index is calculated in real time for each detection point; the modified impact index is added to the comprehensive weight to form a four-dimensional comprehensive weight, and the three-level reinforcement areas are divided. The impact index at each detection point is calculated as follows: ； in: Peak field strength; : Rate of change of electric field strength; Distance from the interference source.

2. The electromagnetic shielding method for power distribution according to claim 1, characterized in that: Based on the volume data of the shielded room, a shielding model corresponding to the shielded room is established, including: establishing a coordinate system with one corner of the shielded room as the origin; establishing a three-dimensional shielding model corresponding to the shielded room according to the three-dimensional rectangular coordinate system and on the same scale; arranging a 16-channel synchronous sampling electromagnetic wave detection array; and building a signal generation link for transmitting standard electromagnetic waves.

3. The electromagnetic shielding method for power distribution according to claim 1, characterized in that: Key detection points were selected, including: for the 16-channel synchronous sampling electromagnetic wave detection array data, a sliding window denoising method was used to calculate the median of 5 adjacent sampling points, and the median was used to replace outliers to remove noise interference. All field strength data were normalized according to frequency bands, and core points were marked. Starting from the core points, points with density connections were merged into the same cluster, and the average field strength of each cluster was calculated. If it exceeded 3 times the global average, an abnormal cluster was marked. For the abnormal cluster, the average coordinates of all points in the cluster and the two points in the cluster farthest from the centroid were selected as key detection points.

4. The electromagnetic shielding method for power distribution according to claim 1, characterized in that: Calculate the phase difference between each key detection point, construct a phase difference matrix, and combine the three-dimensional coordinates of the detection points to map the detection point pairs that meet the node and antinode conditions into space, mark the node and antinode regions of the standing wave, classify the standing wave mode using a clustering algorithm, calculate the phase difference of each segment, and locate the complete leakage path through the phase accumulation effect.

5. An electromagnetic shielding method for power distribution, characterized in that: The shielded room space is refined into a grid to generate an initial grid set; The density of joints per unit volume is calculated as follows: ;in: For the mesh volume; Total length of seams within each grid; The corrected impact index for a single detection point is calculated as follows: , ； in: : This represents the basic weight of the frequency band; Distance from the interference source; Peak field strength; : Rate of change of electric field strength; Pulse width PW and rise time RT; The grid mean is calculated as follows: ;in: : This represents the number of detection points within the grid; The standing wave ratio (SWR) of a single detection point is calculated as follows: ;in: : represents the reflection coefficient; The grid extrema are: ; The comprehensive risk score is calculated based on joint density, grid mean, and grid extreme values. Using the joint density and comprehensive risk score as a two-dimensional feature space, a neighborhood radius is set to divide the core leakage area and the auxiliary protection area, forming a unit group structure; The unit group structure is checked to see if it contains a complete leakage path. If a break exists, adjacent meshes are automatically merged based on the spatial connectivity of the 3D model until the path is closed. A 3D electromagnetic coupling model is established for each unit group. The phase difference between the core area and the auxiliary area within the group is used to adjust the reflection phase in real time by deploying an adjustable phase metasurface in the auxiliary area, so that the combined field strength within the group is approximately 0. GPS-controlled clock sources ensure data synchronization across all units, recording scenario parameters, optimal hardening parameters, and weighting coefficients for each leakage event; a three-dimensional protection matrix model is constructed. ,in For spatial coordinates, For frequency, For time; A three-level reinforcement layer is deployed in the core area of ​​the unit group, and a two-level reinforcement layer is deployed in the auxiliary area, forming a cascade structure of strong attenuation in the core and weak attenuation in the auxiliary area.

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