A testing device for electromagnetic shielding materials

Abstract

The application relates to the technical field of electromagnetic shielding test devices, and discloses a test device for electromagnetic shielding materials. The device comprises a signal emission module, a signal receiving module, a parameter calibration module and a shielding effectiveness calculation module. The signal emission module outputs electromagnetic signals of different frequencies from multiple signal sources, and forms a set of to-be-tested signals after pre-processing and amplitude adjustment; the signal receiving module collects residual signals passing through the shielding material and converts the residual signals into analyzable signals; the parameter calibration module extracts signal parameters to construct an electromagnetic signal parameter matrix, constructs a transmission correlation atlas through a channel correlation graph and a key signal parameter correlation degree; the shielding effectiveness calculation module combines signal channel entropy and the correlation atlas to calculate a shielding effectiveness core parameter sequence, and finally inputs the effectiveness detection model of a convolutional neural network model to generate a test report. The device can comprehensively process multiple-frequency signals, deeply analyze signal parameter correlation, accurately calculate shielding effectiveness, and is suitable for electromagnetic shielding material performance testing.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electromagnetic shielding test devices, in particular to a test device for electromagnetic shielding materials. BACKGROUND

[0002] Under the background of rapid development of modern electronic technology, the electromagnetic environment is becoming increasingly complex, and the problem of electromagnetic interference is becoming more and more prominent. As an important means to solve electromagnetic interference and ensure the normal operation of electronic equipment, the accuracy and reliability of the performance test of electromagnetic shielding materials are crucial.

[0003] The existing electromagnetic shielding material test device has many deficiencies in actual application. The processing of electromagnetic signals by traditional test devices is relatively single, and most of them can only process electromagnetic signals of a single frequency or a limited frequency range, which is difficult to meet the test requirements of the complex electromagnetic environment faced by current diversified electronic equipment. For example, when facing actual scenes containing electromagnetic signals of multiple frequencies, the traditional device cannot comprehensively and accurately simulate the real electromagnetic interference situation, resulting in insufficient comprehensive evaluation of the performance of electromagnetic shielding materials.

[0004] The existing test device lacks in-depth analysis of the correlation between electromagnetic signal parameters in the signal analysis process. Only some basic parameters of the signal are simply extracted and calculated, without considering the mutual influence and correlation between multiple signals such as incident signals, reflected signals, transmitted signals, interference signals and background noise signals. This makes it impossible to fully utilize the correlation information between signals when calculating the shielding effectiveness, resulting in low accuracy and reliability of the calculation results.

[0005] The traditional test device also has defects in the calculation method of shielding effectiveness. It often uses a relatively simple calculation model without fully considering the complex physical processes that occur when electromagnetic signals pass through shielding materials, such as signal reflection, transmission, absorption, and the influence of various interference and noise. Moreover, the signal correlation between different channels is not effectively analyzed and utilized, making the calculated shielding effectiveness core parameters unable to accurately reflect the actual shielding performance of electromagnetic shielding materials.

[0006] The existing test device also has deficiencies in the processing and application of test results. The generation of test reports lacks systematicness and comprehensiveness, and cannot provide detailed and accurate reference for the research and application of electromagnetic shielding materials. When facing electromagnetic shielding materials of different types and purposes, the traditional test device cannot conduct targeted testing and analysis according to their characteristics, resulting in poor applicability of the test results. SUMMARY

[0007] The purpose of the present application is to provide a test device for electromagnetic shielding materials to solve the problems raised in the background.

[0008] To achieve the above object, the application provides a testing device for electromagnetic shielding material, which comprises:

[0009] a signal transmitting module, which is used for outputting electromagnetic signals of different frequencies from multiple signal sources, and obtaining to-be-tested electromagnetic signals by signal conditioning on the electromagnetic signals;

[0010] a signal receiving module, which is used for collecting residual electromagnetic signals after the to-be-tested electromagnetic signals pass through the electromagnetic shielding material, and obtaining analyzable electromagnetic signals by signal conversion on the residual electromagnetic signals;

[0011] a parameter calibration module, which is used for parameter extraction on the analyzable electromagnetic signals, obtaining an electromagnetic signal parameter matrix, determining a channel correlation graph of each channel in the electromagnetic signal parameter matrix, and constructing an electromagnetic signal transmission correlation graph by the channel correlation graphs of the channels;

[0012] a shielding effectiveness calculation module, which is used for extracting signal parameter vectors of the channels in the electromagnetic signal parameter matrix, determining signal channel entropies of the channels according to the corresponding signal parameter vectors, and calculating a shielding effectiveness core parameter sequence based on all the signal channel entropies and the electromagnetic signal transmission correlation graph.

[0013] Preferably, the electromagnetic signals involved in the testing of the electromagnetic shielding material include incident signals, reflected signals, transmitted signals, interference signals and background noise signals.

[0014] Preferably, the signal conditioning on the electromagnetic signals to obtain the to-be-tested electromagnetic signals specifically comprises:

[0015] preprocessing on the electromagnetic signals to obtain preprocessed electromagnetic signals;

[0016] amplitude adjustment on the preprocessed electromagnetic signals to obtain the to-be-tested electromagnetic signals of each frequency;

[0017] construction of a to-be-tested electromagnetic signal set by the to-be-tested electromagnetic signals of all the frequencies.

[0018] Preferably, the parameter extraction on the analyzable electromagnetic signals to obtain the electromagnetic signal parameter matrix specifically comprises:

[0019] parameter extraction on electromagnetic signals of each channel in the analyzable electromagnetic signals to obtain signal parameter vectors of the channels;

[0020] construction of the electromagnetic signal parameter matrix according to the signal parameter vectors of all the channels.

[0021] Preferably, the determination of the channel correlation graph of each channel in the electromagnetic signal parameter matrix specifically comprises:

[0022] selecting one channel from all channels of the electromagnetic signal parameter matrix, and obtaining a signal parameter vector of the selected channel;

[0023] determining parameter correlation degrees between each signal parameter in the signal parameter vector of the selected channel;

[0024] constructing a channel correlation graph of the selected channel according to the parameter correlation degrees between each signal parameter, and further obtaining a channel correlation graph of each channel in the electromagnetic signal parameter matrix.

[0025] Preferably, constructing the electromagnetic signal transmission correlation graph through the channel correlation graphs of each channel specifically comprises:

[0026] determining key signal parameters of each channel, and further determining parameter correlation degrees between each key signal parameter;

[0027] connecting the channel correlation graphs of each channel according to the parameter correlation degrees between each key signal parameter, and further obtaining the electromagnetic signal transmission correlation graph.

[0028] Preferably, determining the signal channel entropy of each channel according to the corresponding signal parameter vector specifically comprises:

[0029] obtaining a calibration factor of each channel;

[0030] for the signal parameter vector of each channel, obtaining a weight corresponding to each signal parameter in the signal parameter vector;

[0031] determining the signal channel entropy of the channel corresponding to the signal parameter vector through the weight corresponding to each signal parameter and the corresponding calibration factor, and further obtaining the signal channel entropy of each channel.

[0032] Preferably, calculating the shielding effectiveness core parameter sequence based on all the signal channel entropies and the electromagnetic signal transmission correlation graph specifically comprises:

[0033] for each signal parameter in the electromagnetic signal parameter matrix, determining the signal channel entropy of the channel in which the signal parameter is located;

[0034] extracting all parameter correlation degrees corresponding to the signal parameter in the electromagnetic signal transmission correlation graph;

[0035] determining the shielding effectiveness core entropy of the signal parameter through the signal channel entropy of the channel in which the signal parameter is located and the corresponding all parameter correlation degrees, and further obtaining the shielding effectiveness core entropy of each signal parameter in the electromagnetic signal parameter matrix;

[0036] calculating all shielding effectiveness core parameters according to the shielding effectiveness core entropies of each signal parameter;

[0037] The shielding effectiveness core parameter sequence is constructed according to all the shielding effectiveness core parameters.

[0038] Preferably, the shielding effectiveness test of the electromagnetic shielding material according to the shielding effectiveness core parameter sequence is that the shielding effectiveness core parameter sequence is input into the effectiveness detection model for detection, and then a shielding effectiveness test report of the electromagnetic shielding material is obtained.

[0039] Preferably, the effectiveness detection model is a convolutional neural network model.

[0040] Compared with the prior art, the present application has the following beneficial effects:

[0041] The test device for electromagnetic shielding material provided by the present application has many significant advantages. The test device is provided with a signal transmitting module, which can output electromagnetic signals of different frequencies from multiple signal sources and perform signal conditioning on these electromagnetic signals. The electromagnetic signals are preprocessed and then amplitude-adjusted to obtain electromagnetic signals of each frequency to be tested, and finally a set of electromagnetic signals to be tested is constructed. Such a design enables the device to process electromagnetic signals of multiple frequencies, more comprehensively simulates complex electromagnetic environments, and meets the testing needs of electromagnetic shielding materials in different scenarios.

[0042] The signal receiving module can collect the remaining electromagnetic signals after passing through the electromagnetic shielding material and perform signal conversion to obtain analyzable electromagnetic signals. This process ensures that the device can accurately obtain the electromagnetic signals after the action of the shielding material, providing a reliable data basis for subsequent parameter analysis and shielding effectiveness calculation.

[0043] The parameter calibration module is very critical. It first extracts the parameters of the analyzable electromagnetic signals to obtain the signal parameter vectors of each channel, and then constructs an electromagnetic signal parameter matrix. Then, the channels are selected in the matrix, the parameter correlation degrees of each signal parameter in the signal parameter vectors of the channels are determined, the channel correlation graphs are constructed, the key signal parameters of each channel and the parameter correlation degrees between them are determined, the channel correlation graphs of each channel are connected, and the electromagnetic signal transmission correlation graph is constructed. In this way, the module deeply analyzes the correlation between the electromagnetic signal parameters, fully considers the mutual influence between the incident, reflected, transmitted, interference and background noise and other signals, and makes the analysis of the electromagnetic signals more comprehensive and in-depth.

[0044] The workflow of the shielding effectiveness calculation module is also very advantageous. It first acquires the calibration factor of each channel, determines the weight of each signal parameter in the signal parameter vector, and then determines the signal channel entropy of each channel. Then for each signal parameter in the electromagnetic signal parameter matrix, determine the signal channel entropy of the channel it is in, extract all parameter correlation degrees in the electromagnetic signal transmission correlation graph, determine the shielding effectiveness core entropy of the signal parameter through these two, and then calculate all shielding effectiveness core parameters according to the shielding effectiveness core entropy of each signal parameter, and finally construct the shielding effectiveness core parameter sequence. This calculation method makes full use of the signal channel entropy and the electromagnetic signal transmission correlation graph, and fully considers various complex factors of electromagnetic signals in the process of passing through shielding materials, so that the calculated shielding effectiveness core parameters can more accurately reflect the actual shielding performance of electromagnetic shielding materials.

[0045] Finally, the shielding effectiveness core parameter sequence is input into the effectiveness detection model as a convolutional neural network model for detection, and the shielding effectiveness test report of the electromagnetic shielding material can be obtained. This way uses advanced neural network models to process and analyze test data, improves the accuracy and reliability of test results, and provides detailed and accurate reference for the research and application of electromagnetic shielding materials. The test device works collaboratively through various modules, from signal transmission, reception, parameter calibration to shielding effectiveness calculation and test report generation, forming a complete and systematic test process, and comprehensively improving the accuracy, reliability and comprehensiveness of the shielding effectiveness test of electromagnetic shielding materials. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 A working principle diagram of a test device for electromagnetic shielding materials according to the present application;

[0047] Figure 2 A flowchart of signal conditioning;

[0048] Figure 3 A flowchart of channel correlation graph construction;

[0049] Figure 4 A flowchart of signal channel entropy calculation;

[0050] Figure 5 A flowchart of shielding effectiveness core parameter sequence calculation. DETAILED DESCRIPTION

[0051] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of the present application.

[0052] Please refer to Figure 1-Figure 5 The present application provides a kind of for electromagnetic shielding material test device, the device includes: signal transmitting module, signal receiving module, parameter calibration module and shielding effectiveness calculation module.Specific implementation steps are as follows:

[0053] Signal transmitting module exports electromagnetic signal of different frequency from multiple signal sources, pre-processes electromagnetic signal, obtains pre-processed electromagnetic signal, adjusts amplitude to pre-processed electromagnetic signal, and then obtains each frequency electromagnetic signal to be tested, and constructs electromagnetic signal to be tested set by all frequency electromagnetic signal to be tested.

[0054] Signal receiving module collects the residual electromagnetic signal after electromagnetic signal to be tested passes through electromagnetic shielding material, signal conversion is carried out to residual electromagnetic signal, and obtainable electromagnetic signal is obtained.

[0055] Parameter calibration module extracts parameters from electromagnetic signal, extracts parameters from electromagnetic signal in each channel of electromagnetic signal, and then obtains signal parameter vector of each channel, constructs electromagnetic signal parameter matrix according to signal parameter vector of all channels, determines channel correlation diagram of each channel in electromagnetic signal parameter matrix, selects a channel in all channels of electromagnetic signal parameter matrix, obtains signal parameter vector of selected channel, determines parameter correlation degree between each signal parameter in signal parameter vector of selected channel, constructs channel correlation diagram of selected channel according to parameter correlation degree between each signal parameter, and then obtains channel correlation diagram of each channel in electromagnetic signal parameter matrix, constructs electromagnetic signal transmission correlation atlas by channel correlation diagram of each channel, determines key signal parameter of each channel, and then determines parameter correlation degree between each key signal parameter, connects channel correlation diagram of each channel according to parameter correlation degree between each key signal parameter, and then obtains electromagnetic signal transmission correlation atlas.

[0056] The shielding effectiveness calculation module extracts the signal parameter vectors of each channel in the electromagnetic signal parameter matrix, obtains the calibration factor of each channel, obtains the weight corresponding to each signal parameter in the signal parameter vector for the signal parameter vector of each channel, determines the signal channel entropy of the channel corresponding to the signal parameter vector through the weight corresponding to each signal parameter and the corresponding calibration factor, and further obtains the signal channel entropy of each channel. Based on all the signal channel entropies and the electromagnetic signal transmission correlation graph, the shielding effectiveness core parameter sequence is calculated. For each signal parameter in the electromagnetic signal parameter matrix, the signal channel entropy of the channel where the signal parameter is located is determined, all parameter correlation degrees corresponding to the signal parameter are extracted in the electromagnetic signal transmission correlation graph, and the shielding effectiveness core entropy of the signal parameter is determined through the signal channel entropy of the channel where the signal parameter is located and the corresponding all parameter correlation degrees. Further, the shielding effectiveness core entropy of each signal parameter in the electromagnetic signal parameter matrix is obtained. According to the shielding effectiveness core entropy of each signal parameter, all shielding effectiveness core parameters are calculated. According to all the shielding effectiveness core parameters, the shielding effectiveness core parameter sequence is constructed. The shielding effectiveness core parameter sequence is input into the effectiveness detection model for detection, and further the shielding effectiveness test report of the electromagnetic shielding material is obtained.

[0057] In the test of the electromagnetic shielding material, the electromagnetic signals involved include incident signals, reflected signals, transmitted signals, interference signals and background noise signals. Among them, the incident signal is the original electromagnetic signal output by the signal emission module from multiple signal sources, and its frequency range is set according to the test requirements. It is used to directly irradiate the electromagnetic shielding material and is the starting signal of the entire test process. The reflected signal is the signal generated when the incident signal encounters the electromagnetic shielding material due to the reflection of the material to the electromagnetic signal. This signal will return along the incident direction, and its intensity and characteristics are closely related to factors such as the surface characteristics and material of the shielding material. The transmitted signal is the remaining signal after the incident signal passes through the electromagnetic shielding material. It carries the attenuation information of the electromagnetic signal of the shielding material and is one of the key signals for evaluating the shielding effectiveness. The interference signal mainly comes from other electronic devices or electromagnetic radiation sources in the test environment, and its frequency and intensity are uncertain, which will interfere with the test results to a certain extent. The background noise signal is the weak electromagnetic signal always existing in the test environment, which belongs to part of the environmental background radiation.

[0058] During the test, the electromagnetic signal output by the signal transmitting module contains the above-mentioned various signals, and these signals participate in the test in different ways. The signal transmitting module first performs signal conditioning on the output electromagnetic signal to obtain a set of electromagnetic signals to be tested, which contains incident signals of different frequencies and may also contain some interference signals and background noise signals. When the electromagnetic signals to be tested act on the electromagnetic shielding material, part of the incident signals is reflected by the material to form reflected signals, and the other part passes through the material to form transmitted signals, while the interference signals and background noise signals may bypass the material or directly pass through the material together with the transmitted signals to be collected by the signal receiving module.

[0059] The function of the signal receiving module is to collect the remaining electromagnetic signals after passing through the electromagnetic shielding material, which mainly includes transmitted signals, part of reflected signals (which may reach the receiving module through other paths), and interference signals and background noise signals in the environment. The receiving module converts these remaining electromagnetic signals into digital signals from analog signals for subsequent analysis and processing to obtain analyzable electromagnetic signals.

[0060] When processing the analyzable electromagnetic signals, the parameter calibration module needs to extract parameters of different types of signals. For incident signals, their frequency, amplitude, phase, and other parameters need to be extracted; for reflected signals, these parameters also need to be extracted to analyze the reflection characteristics; the parameter extraction of transmitted signals is directly related to the evaluation of the attenuation performance of the shielding material; and the parameter extraction of interference signals and background noise signals is used for subsequent noise elimination and interference analysis. The parameter calibration module extracts parameters of electromagnetic signals in each channel of the analyzable electromagnetic signals. Each channel may correspond to different signal types or test points, and signal parameter vectors of each channel are obtained by extraction, and an electromagnetic signal parameter matrix is constructed based on the signal parameter vectors of all channels.

[0061] After constructing the electromagnetic signal parameter matrix, the channel correlation graph of each channel in the matrix needs to be determined. Taking a certain channel as an example, the signal parameter vector of the channel is obtained, which contains the parameters of incident signals, reflected signals, transmitted signals, interference signals, and background noise signals. Then the parameter correlation degrees between these parameters are analyzed, such as the correlation degree between the frequency of the incident signal and the amplitude of the transmitted signal, the correlation degree between the phase of the reflected signal and the frequency of the interference signal, etc. By calculating these correlation degrees, the channel correlation graph of the channel is constructed, in which the nodes represent the signal parameters and the edges represent the correlation degrees between the parameters, thereby intuitively showing the mutual relationship between different signal parameters in the channel.

[0062] When calculating the shielding effectiveness core parameter sequence, the shielding effectiveness calculation module needs to analyze the parameters of these different types of signals. First, the signal parameter vectors of each channel are extracted from the electromagnetic signal parameter matrix. For each channel, its calibration factor is obtained. This calibration factor is used to correct the system error or environmental influence during the test process. At the same time, the weight corresponding to each signal parameter in the signal parameter vector is determined. The weight setting is determined according to the importance of different signal parameters to the shielding effectiveness evaluation. For example, the parameter weight of the transmission signal may be relatively high, while the parameter weight of the background noise signal may be relatively low. The signal channel entropy of the channel is calculated based on the weight and calibration factor corresponding to each signal parameter, and then the signal channel entropy of all channels is obtained.

[0063] Next, the shielding effectiveness core parameter sequence is calculated based on the entropy of all signal channels and the electromagnetic signal transmission correlation map. In the electromagnetic signal transmission correlation map, it is necessary to consider the correlation between various signal parameters between different channels, such as the correlation between the transmission signal parameters of different channels, and the transmission relationship between the incident signal parameters and the reflected signal parameters in different channels. For each signal parameter in the electromagnetic signal parameter matrix, the signal channel entropy of the channel in which it is located is determined, and the correlation of all parameters corresponding to the signal parameter is extracted from the transmission correlation map. The shielding effectiveness core entropy of the signal parameter is determined based on the signal channel entropy and the parameter correlation, and then the shielding effectiveness core entropy of all signal parameters is obtained. Finally, the shielding effectiveness core parameters are calculated based on these core entropies and constructed into a sequence.

[0064] The core shielding effectiveness parameter sequence is input into the effectiveness testing model for testing. Based on the input parameter sequence and the characteristics and correlations of various signal parameters, the model comprehensively evaluates the shielding effectiveness of the electromagnetic shielding material and ultimately generates a test report. Throughout this process, the parameter characteristics of the incident signal, reflected signal, transmitted signal, interference signal, and background noise signal, as well as their mutual correlations, directly influence the shielding effectiveness calculation and evaluation results. Therefore, these signals must be comprehensively collected, processed, and analyzed to ensure the accuracy and reliability of the test results.

[0065] Example 2: The signal transmission module performs signal conditioning on the electromagnetic signal to obtain the electromagnetic signal to be tested. This process includes multiple steps such as preprocessing, amplitude adjustment, and construction of a signal set. First, the electromagnetic signal is output by multiple signal sources. These signals may have varying degrees of noise, distortion, or parameters that do not meet the test requirements, so they need to be preprocessed first. Preprocessing operations include filtering, amplification, etc. The purpose of filtering is to remove interference components carried in the electromagnetic signal, such as stray electromagnetic radiation in the external environment or harmonics generated by the signal source itself. By setting a suitable filter cutoff frequency, the signal in the required frequency band can be retained and the noise outside the frequency band can be filtered out. The amplification operation is aimed at the case of weak signal strength, and the amplitude of the electromagnetic signal is increased to a certain level for subsequent processing and transmission to avoid distortion or acquisition errors caused by too weak a signal.

[0066] Although the preprocessed electromagnetic signal has had some interference removed and its intensity adjusted, its amplitude may not yet meet the test requirements. In this case, the preprocessed electromagnetic signal needs to be amplitude adjusted, and this adjustment process is determined based on the specific test requirements. Different electromagnetic shielding materials may require testing at different signal intensities to fully evaluate their shielding effectiveness. For example, certain high-shielding-effectiveness materials may require a stronger incident signal to test their performance in a strong electromagnetic environment; while general materials may be tested with a standard intensity signal. Amplitude adjustment can be achieved using an attenuator or amplifier to precisely control the amplitude of the electromagnetic signal to meet the test requirements at each frequency point, thereby obtaining the electromagnetic signal to be tested at each frequency.

[0067] After obtaining the electromagnetic signals to be tested at each frequency, these signals need to be integrated to construct a test signal set. This set contains conditioned electromagnetic signals at different frequencies, which will serve as incident signals for subsequent electromagnetic shielding material testing. When constructing the signal set, it is necessary to ensure that the signals of different frequencies do not interfere with each other and can act on the electromagnetic shielding material in a predetermined sequence or simultaneously. For example, the electromagnetic signals to be tested at different frequencies can be combined using a multiplexer to form a comprehensive signal source, allowing the shielding performance of the material to be tested at multiple frequencies simultaneously.

[0068] Assume that the signal transmission module outputs electromagnetic signals at 100 MHz, 500 MHz, and 1 GHz from three signal sources, respectively. These raw signals may contain low-frequency noise below 200 MHz and high-frequency noise above 1.5 GHz. Bandpass filters are used for preprocessing, retaining the frequency band from 100 MHz to 1 GHz and filtering out noise in other frequency bands. The 100 MHz signal amplitude is 10 mV, the 500 MHz signal amplitude is 5 mV, and the 1 GHz signal amplitude is 8 mV. The test requires that the amplitudes of all three frequencies be 10 mV. Therefore, the 500 MHz signal amplitude is boosted to 10 mV through an amplifier, while the 1 GHz signal amplitude remains unchanged (or fine-tuned based on actual conditions). The 100 MHz signal amplitude is also unchanged. After amplitude adjustment, the three electromagnetic signals under test are generated, each with an amplitude of 10 mV and at frequencies of 100 MHz, 500 MHz, and 1 GHz. Finally, these three signals are combined to form a test electromagnetic signal set, which can be output through a single signal output port for irradiating electromagnetic shielding materials.

[0069] Throughout the entire signal conditioning process, every step requires precise control and calibration. The filter parameters in the preprocessing stage must be designed based on the required frequency range for testing to ensure effective noise filtering without affecting the desired signal. During amplitude adjustment, high-precision attenuators and amplifiers are required, along with real-time monitoring using instruments such as oscilloscopes to ensure the accuracy of the adjusted signal amplitude. When constructing the electromagnetic signal set to be tested, it is necessary to consider signal transmission delay and phase consistency to avoid inaccurate test results due to errors in the signal combination process.

[0070] Furthermore, the signal transmission module must possess a certain degree of flexibility to accommodate diverse testing requirements. For example, when testing the shielding effectiveness of electromagnetic shielding materials across a wide frequency range, the frequency range of the signal source can be expanded, and the preprocessing and amplitude adjustment parameters can be adjusted accordingly to construct a test electromagnetic signal set encompassing a wider frequency range. When testing the shielding performance of a material at a specific frequency point, the signal parameters at that frequency point can be adjusted to meet the test requirements.

[0071] Example 3: The parameter calibration module extracts parameters from the analyzable electromagnetic signal to obtain an electromagnetic signal parameter matrix. This process involves processing electromagnetic signals of multiple channels one by one and systematically integrating the parameters.

[0072] The residual electromagnetic signals collected by the signal receiving module form analyzable electromagnetic signals after signal conversion. These signals usually contain multiple channels, each corresponding to a different test position, signal type, or transmission path. For example, multiple receiving antennas can be set in the test device, located at different positions of the electromagnetic shielding material, to collect transmission signals at different angles, or different channels can be used to receive reference signals of reflected signals, incident signals, etc.

[0073] For each channel in the analyzable electromagnetic signal, the parameter calibration module needs to perform independent parameter extraction operations. The electromagnetic signal of each channel is a waveform that changes over time, which contains rich signal parameters such as frequency, amplitude, phase, time domain characteristic parameters (such as rise time, pulse width), frequency domain characteristic parameters (such as power spectral density), etc. The parameter extraction process needs to select appropriate methods according to the characteristics of the signal, for example, for continuous sinusoidal signals, the main parameters to be extracted are frequency and amplitude; for pulse signals, parameters such as pulse width and repetition frequency need to be extracted.

[0074] Taking the electromagnetic signal of a certain channel as an example, suppose that the channel receives a transmission signal that passes through the electromagnetic shielding material, and the waveform of the signal is a composite signal containing multiple frequency components. The parameter calibration module first digitizes the signal and converts the analog signal into a discrete digital signal sequence. Then, through digital signal processing algorithms, the sampled data is analyzed, for example, using Fast Fourier Transform (FFT) to convert the time domain signal to the frequency domain, thereby extracting the amplitude and phase information of each frequency component. At the same time, the amplitude variation range, average power, and other parameters of the signal in the time domain are analyzed. These operations need to accurately control the sampling rate and sampling time length to ensure that the extracted parameters can accurately reflect the true characteristics of the signal.

[0075] After completing the parameter extraction of a single channel, the signal parameter vector of the channel is obtained. The signal parameter vector is an ordered array containing all the extracted parameters of the channel, and the order of its elements is arranged according to the type and importance of the parameters. For example, the first element of the vector is the center frequency, the second element is the amplitude, the third element is the phase, and the subsequent elements are other characteristic parameters. The length of the signal parameter vector of each channel may vary due to the complexity of the signal and the number of extracted parameters, but the format consistency of all channel parameter vectors under the same test scenario needs to be maintained to facilitate the subsequent construction of the matrix.

[0076] Once the signal parameter vectors for all channels have been extracted, the parameter calibration module combines these vectors by channel order to construct an electromagnetic signal parameter matrix. Each row of the matrix corresponds to a signal parameter vector for a channel, and each column corresponds to a specific parameter type. For example, the first column of the matrix is ​​the center frequency of all channels, the second column is the amplitude of all channels, and so on. This matrix structure intuitively displays the distribution and differences in different parameters across channels, providing a structured data foundation for subsequent channel correlation diagram construction and shielding effectiveness calculations.

[0077] In practice, the accuracy of parameter extraction is affected by a variety of factors, requiring appropriate calibration and error control. For example, quantization errors during the sampling process can lead to deviations in parameter extraction, necessitating the selection of an analog-to-digital converter (ADC) with sufficient accuracy and the incorporation of error compensation steps into the parameter extraction algorithm. Furthermore, environmental noise and interfering signals can be mixed into the analyzable electromagnetic signal, affecting the accuracy of parameter extraction. Therefore, additional filtering may be required before parameter extraction, or algorithms may be employed to identify and remove noise components during the parameter extraction process.

[0078] For example, consider a test scenario with four channels: channel 1 receives the transmitted signal, channel 2 receives the reflected signal, channel 3 receives the incident reference signal, and channel 4 receives the ambient noise signal. Parameter extraction for channel 1's transmitted signal reveals a center frequency of 500 MHz, an amplitude of 20 dBμV, a phase of 30 degrees, and a bandwidth of 10 MHz, resulting in a signal parameter vector of [500 MHz, 20 dBμV, 30 degrees, 10 MHz]. Similarly, the parameter vector for channel 2's reflected signal might be [500 MHz, 15 dBμV, 180 degrees, 8 MHz], the parameter vector for channel 3's incident reference signal might be [500 MHz, 30 dBμV, 0 degrees, 5 MHz], and the parameter vector for channel 4's ambient noise might be [450-550 MHz, 5 dBμV, -45 degrees, 100 MHz]. These vectors are arranged in sequence to construct an electromagnetic signal parameter matrix with 4 rows and 4 columns, where the first column is the center frequency of each channel, the second column is the amplitude, the third column is the phase, and the fourth column is the bandwidth.

[0079] Constructing the electromagnetic signal parameter matrix requires not only accurate extraction of the parameters for each channel but also consideration of the physical meaning and unit consistency of the parameters. For example, amplitude parameters for all channels must be standardized in dBμV or V, and frequency parameters must be standardized in MHz or Hz to avoid calculation errors caused by inconsistent units. Furthermore, for some nonlinear or time-varying signals, time-frequency analysis methods (such as wavelet transforms) may be required to extract the time-varying parameters. In this case, the signal parameter vector may contain parameters with more dimensions, and the number of matrix columns will increase accordingly.

[0080] Embodiment 4: determining the channel correlation graph of each channel in the electromagnetic signal parameter matrix, which requires selecting a channel from the matrix and analyzing the correlation between its signal parameters, the specific implementation is as follows:

[0081] Select a channel from all channels in the electromagnetic signal parameter matrix, which is constructed by the parameter calibration module and contains signal parameter vectors of multiple channels. Assuming that there are N channels in the matrix, after selecting the i-th channel (i = 1, 2, …, N), the signal parameter vector of the channel is obtained The vector contains multiple parameters of the electromagnetic signal of the channel, such as frequency, amplitude, phase, etc. Assuming that there are M parameters in the vector, it can be represented as where represents the j-th signal parameter of the i-th channel.

[0082] Determine the parameter correlation between each signal parameter in the signal parameter vector of the selected channel. The parameter correlation is used to measure the correlation between two parameters, and Pearson correlation coefficient is used here. For signal parameters and , the calculation formula of Pearson correlation coefficient is:

[0083] ,

[0084] where P is the number of samples, and are the values of the j-th and k-th signal parameters of the i-th channel in the n-th sample, and are the sample means of the j-th and k-th signal parameters of the i-th channel. The formula calculates the ratio of the product of the covariance and the standard deviation between the parameters, and obtains a correlation coefficient between -1 and 1. The larger the absolute value of the number, the stronger the linear correlation between the two parameters.

[0085] Take the signal parameter vector of the i-th channel as an example, where is the frequency parameter, is the amplitude parameter, is the phase parameter. When calculating the correlation coefficient of and , the values of the two parameters in multiple samples need to be obtained and substituted into the above formula for calculation. Assuming that 100 sets of data of and are obtained through 100 samplings, first calculate their sample means and , then calculate the covariance of the numerator part and the product of the standard deviation of the denominator part, and finally obtain the correlation coefficient , similarly we can calculate and Correlation coefficient and and Correlation coefficient .

[0086] After obtaining the parameter correlation between each signal parameter, the channel correlation graph of the selected channel is constructed based on these correlations. The channel correlation graph uses the signal parameters as nodes and the correlation between the parameters as edges. The weight of the edge is the absolute value of the corresponding correlation coefficient, and the direction is determined by the correlation relationship (if it is linearly correlated, it is an undirected edge). For example, in the channel containing the three parameters of frequency, amplitude, and phase, the constructed channel correlation graph has three nodes, namely 、 、 , the nodes are connected by edges, and the weight of the edge is the absolute value of the corresponding correlation coefficient. ,but and The edge weight between them is 0.8, indicating that there is a strong positive correlation between the two parameters; if , the edge weight is 0.5, indicating that there is a moderate negative correlation between frequency and phase.

[0087] Following the above steps, each channel in the electromagnetic signal parameter matrix is ​​processed sequentially: first, a channel is selected, its signal parameter vector is obtained, the correlation between the parameters in the vector is calculated, and then a channel correlation graph is constructed based on the correlation. Finally, a channel correlation graph is obtained for each channel in the matrix. Assuming that there are five channels in the matrix and the signal parameter vector of each channel contains four parameters, six pairs of correlations (C(4,2)=6) between the four parameters need to be calculated for each channel. Then, a corresponding channel correlation graph is constructed, each containing four nodes and six weighted edges.

[0088] In actual operation, the calculation of parameter correlation needs to pay attention to the rationality of the number of samples. Too few samples will lead to inaccurate correlation calculation results. It is generally recommended that the number of samples P is not less than 30. At the same time, for non-normally distributed signal parameters, it may be necessary to use non-parametric methods such as the Spearman rank correlation coefficient to calculate the correlation, but in this embodiment, the Pearson correlation coefficient is used as an example for illustration. In addition, when constructing the channel correlation diagram, a correlation threshold value, such as 0.3, can be set. When the absolute value of the correlation is less than the threshold, it is considered that the correlation between the parameters is weak, and the corresponding edge is not drawn in the diagram to simplify the diagram and highlight the main correlation relationship.

[0089] The channel correlation diagram can intuitively show the mutual relationship between the signal parameters in the channel, and provide a basis for subsequent construction of the electromagnetic signal transmission correlation diagram. For example, by observing the correlation diagram of a certain channel, if it is found that the correlation degree between the frequency parameter and the amplitude parameter is high, it means that the frequency change of the electromagnetic signal in this channel has a significant impact on the amplitude, and the correlation of these two parameters needs to be focused on when analyzing the shielding effectiveness. The comparison of the channel correlation diagrams of different channels can reflect the parameter correlation differences of the electromagnetic signal under different test positions or types, and provide multi-angle data support for comprehensive evaluation of the performance of electromagnetic shielding materials.

[0090] In the construction of the electromagnetic signal transmission correlation diagram through the channel correlation diagrams of each channel, the key signal parameters need to be determined first, and then the correlation degree is determined, and then the channel correlation diagrams are connected. Taking an electromagnetic signal parameter matrix containing three channels as an example, channel 1 corresponds to the transmission signal, and its signal parameter vector contains frequency, amplitude, and phase; channel 2 corresponds to the reflection signal, and the parameter vector contains frequency, amplitude, and reflection coefficient; channel 3 corresponds to the incident reference signal, and the parameter vector contains frequency, amplitude, and power.

[0091] The key signal parameters of each channel are determined. For the transmission signal of channel 1, frequency and amplitude are the key parameters affecting the shielding effectiveness, because electromagnetic signals of different frequencies attenuate differently when passing through the shielding material, and the change of amplitude directly reflects the attenuation ability of the shielding material; in the reflection signal of channel 2, the reflection coefficient and the amplitude are the key parameters, the reflection coefficient reflects the reflection ability of the material to the electromagnetic signal, and the amplitude is related to the intensity of the reflected signal; in the incident reference signal of channel 3, the frequency and the power are the key parameters, the frequency is used to match the parameters of other channels, and the power is used as the reference value of the incident signal.

[0092] The parameter correlation degree between each key signal parameter is determined. The correlation degree between the frequency of channel 1 and the reflection coefficient of channel 2 is calculated, and the relationship between the transmission signal frequency and the reflection coefficient is analyzed, such as whether the reflection coefficient changes when the transmission signal frequency changes; the correlation degree between the amplitude of channel 1 and the power of channel 3 is calculated, and the relationship between the transmission signal amplitude and the incident power is understood, and whether the attenuation of the shielding material is related to the incident power is determined; the correlation degree between the amplitude of channel 2 and the frequency of channel 3 is calculated, and whether the amplitude of the reflected signal changes with the change of the frequency of the incident signal is viewed.

[0093] Suppose the frequency of channel 1 is f1, the amplitude is A1; the reflection coefficient of channel 2 is R2, the amplitude is A2; the frequency of channel 3 is f3, the power is P3. When calculating the correlation degree of f1 and R2, the values of f1 and R2 in multiple samples are obtained, and the correlation degree is determined by analyzing the change trend of the two. If R2 generally increases when f1 increases, it means that the two are positively correlated; if R2 decreases when f1 increases, it means that the two are negatively correlated. Similarly, the correlation degree of A1 and P3 is calculated. If A1 also increases when P3 increases, and the increase amplitude has a certain rule, it means that the correlation degree of the two is high.

[0094] According to the parameter correlation degree between each key signal parameter, the channel correlation graphs of each channel are connected. In the channel correlation graph of channel 1, the key parameters f1 and A1 are connected by an edge, and the weight of the edge is the correlation degree of the two; in the channel correlation graph of channel 2, the key parameters R2 and A2 are connected by an edge; in the channel correlation graph of channel 3, the key parameters f3 and P3 are connected by an edge. Then, f1 of channel 1 and R2 of channel 2 are connected by an edge, and the weight of the edge is the correlation degree of f1 and R2; A1 of channel 1 and P3 of channel 3 are connected by an edge, and the weight of the edge is the correlation degree of A1 and P3; A2 of channel 2 and f3 of channel 3 are connected by an edge, and the weight of the edge is the correlation degree of A2 and f3, thereby forming an overall electromagnetic signal transmission correlation graph.

[0095] In this graph, the nodes include f1, A1, R2, A2, f3, P3, and the edges represent the correlation between the key parameters. For example, the edge between f1 and R2 represents the correlation between the transmission signal frequency and the reflection coefficient, and the edge between A1 and P3 represents the correlation between the transmission signal amplitude and the incident power. Through this graph, the mutual influence between different channel key parameters can be directly observed, such as how the change of incident power P3 affects the transmission signal through A1, or how the change of transmission signal frequency f1 affects the reflection coefficient R2.

[0096] For another example, when the electromagnetic shielding material has different shielding effects on electromagnetic signals of different frequencies, the correlation degree of f1 and R2 in the graph may be high, indicating that the frequency change will significantly affect the reflection coefficient and then affect the shielding effectiveness. If the correlation degree of A1 and P3 is low, it means that the transmission signal amplitude is less affected by the incident power, and the attenuation characteristics of the shielding material may be relatively stable and do not change significantly with the incident power.

[0097] After constructing the electromagnetic signal transmission correlation map, the shielding effectiveness calculation module calculates the shielding effectiveness core parameter sequence based on all signal channel entropies and the map. For each signal parameter in the electromagnetic signal parameter matrix, the signal channel entropy of the channel in which it resides is determined, and the correlation degree of all parameters corresponding to the signal parameter in the map is extracted. The shielding effectiveness core entropy of the signal parameter is determined based on the signal channel entropy and parameter correlation degree, and then the shielding effectiveness core entropy of all signal parameters is obtained. Based on these core entropies, the shielding effectiveness core parameters are calculated and constructed into a sequence.

[0098] The shielding effectiveness core parameter sequence is input into the effectiveness detection model, which is a convolutional neural network model. The model comprehensively evaluates the shielding effectiveness of the electromagnetic shielding material based on the correlation between the parameters in the spectrum and the core parameter sequence, and generates a test report. For example, if the spectrum shows a strong correlation between the transmission signal frequency and the reflection coefficient, and the corresponding shielding effectiveness core entropy is high, it indicates that this set of parameters has a significant impact on shielding effectiveness, and the model will focus on this parameter in the evaluation.

[0099] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0100] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A testing device for electromagnetic shielding materials, characterized in that: The testing device comprises: A signal transmitting module is used to output electromagnetic signals of different frequencies from multiple signal sources, and perform signal conditioning on the electromagnetic signals to obtain electromagnetic signals to be tested; a signal receiving module, configured to collect the residual electromagnetic signal after the electromagnetic signal to be tested passes through the electromagnetic shielding material, and perform signal conversion on the residual electromagnetic signal to obtain an analyzable electromagnetic signal; a parameter calibration module, configured to extract parameters of the analyzable electromagnetic signal to obtain an electromagnetic signal parameter matrix, determine a channel correlation diagram for each channel in the electromagnetic signal parameter matrix, and construct an electromagnetic signal transmission correlation map based on the channel correlation diagrams of the respective channels; a shielding effectiveness calculation module, configured to extract a signal parameter vector of each channel from the electromagnetic signal parameter matrix, determine the signal channel entropy of each channel according to the corresponding signal parameter vector, and calculate a shielding effectiveness core parameter sequence based on all signal channel entropies and the electromagnetic signal transmission correlation map; Determining a channel association diagram for each channel in the electromagnetic signal parameter matrix specifically includes: Selecting a channel from all channels of the electromagnetic signal parameter matrix and obtaining a signal parameter vector of the selected channel; determining a parameter correlation between each signal parameter in a signal parameter vector of a selected channel; A channel correlation graph of the selected channel is constructed according to the parameter correlation between each signal parameter, thereby obtaining a channel correlation graph of each channel in the electromagnetic signal parameter matrix.

2. A testing device for electromagnetic shielding materials according to claim 1, characterized in that: The electromagnetic signals involved in the test of the electromagnetic shielding material include incident signals, reflected signals, transmitted signals, interference signals and background noise signals.

3. A testing device for electromagnetic shielding materials according to claim 1, characterized in that: Performing signal conditioning on the electromagnetic signal to obtain the electromagnetic signal to be tested specifically includes: Preprocessing the electromagnetic signal to obtain a preprocessed electromagnetic signal; Adjusting the amplitude of the pre-processed electromagnetic signal to obtain electromagnetic signals to be tested at various frequencies; The electromagnetic signal set to be tested is constructed by using the electromagnetic signals to be tested of all frequencies.

4. A testing device for electromagnetic shielding materials according to claim 1, characterized in that: Extracting parameters from the analyzable electromagnetic signal to obtain an electromagnetic signal parameter matrix specifically includes: Extracting parameters of the electromagnetic signal of each channel in the analyzable electromagnetic signal respectively, thereby obtaining a signal parameter vector of each channel; The electromagnetic signal parameter matrix is ​​constructed based on the signal parameter vectors of all channels.

5. The testing device for electromagnetic shielding materials according to claim 1, characterized in that: The electromagnetic signal transmission correlation map is constructed through the channel correlation diagram of each channel, specifically including: Determine the key signal parameters of each channel, and then determine the parameter correlation between each key signal parameter; The channel correlation diagrams of each channel are connected according to the parameter correlation between each key signal parameter, thereby obtaining the electromagnetic signal transmission correlation map.

6. A testing device for electromagnetic shielding materials according to claim 1, characterized in that: Determining the signal channel entropy of each channel according to the corresponding signal parameter vector specifically includes: Get the calibration factor for each channel; For the signal parameter vector of each channel, obtain the weight corresponding to each signal parameter in the signal parameter vector; The signal channel entropy of the channel corresponding to the signal parameter vector is determined by using the weight corresponding to each signal parameter and the corresponding calibration factor, thereby obtaining the signal channel entropy of each channel.

7. A testing device for electromagnetic shielding materials according to claim 1, characterized in that: The shielding effectiveness core parameter sequence calculated based on all signal channel entropies and the electromagnetic signal transmission correlation map specifically includes: For each signal parameter in the electromagnetic signal parameter matrix, determining the signal channel entropy of the channel where the signal parameter is located; Extracting all parameter correlation degrees corresponding to the signal parameters in the electromagnetic signal transmission correlation map; Determining the shielding effectiveness core entropy of the signal parameter by using the signal channel entropy of the channel where the signal parameter is located and the correlation degree of all corresponding parameters, and then obtaining the shielding effectiveness core entropy of each signal parameter in the electromagnetic signal parameter matrix; All shielding effectiveness core parameters are calculated based on the shielding effectiveness core entropy of each signal parameter; A shielding effectiveness core parameter sequence is constructed based on all shielding effectiveness core parameters.

8. The testing device for electromagnetic shielding materials according to claim 1, characterized in that: The shielding effectiveness test of the electromagnetic shielding material is performed according to the shielding effectiveness core parameter sequence, which is input into the effectiveness detection model for detection, thereby obtaining a shielding effectiveness test report of the electromagnetic shielding material.

9. A testing device for electromagnetic shielding materials according to claim 8, characterized in that: The performance detection model is a convolutional neural network model.

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