Electromagnetic interference shielding and signal enhancement system

Abstract

A self-adaptive electromagnetic interference shielding and signal enhancement system belongs to the field of electronics and communication and comprises a signal feature analysis module, a dynamic shielding design module, a signal enhancement module, an intelligent adjustment module and a feedback adjustment module. According to the invention, the shielding effect and the signal enhancement strategy can be dynamically adjusted according to the change of the real-time electromagnetic environment. The intensity, the frequency and the position of an interference signal are monitored in real time through spectrum analysis and a multi-mode sensing technology. An intelligent material or a tunable structure is used to dynamically adjust electromagnetic parameters of a shielding material, and an efficient shielding effect is achieved. Various types of electromagnetic interferences, including high-frequency, low-frequency and transient interferences, can be effectively suppressed. Through a multi-sensor fusion technology, types and features of interference sources are accurately identified, and targeted shielding is realized. In a complex electromagnetic environment, a plurality of interference sources can be processed at the same time, and signal distortion or loss is avoided.

Description

Technical Field

[0001] The present invention belongs to the field of electronic and communication technologies, and more specifically, particularly relates to an electromagnetic interference shielding and signal enhancement system. Background Art

[0002] With the rapid development of electronic devices and wireless communication technologies, the electromagnetic environment has become increasingly complex. Electromagnetic interference (EMI) has become one of the main problems affecting the performance of electronic devices and the quality of communication. Electromagnetic interference may come from natural sources (such as lightning) or human sources (such as wireless devices, high-voltage power lines, industrial equipment, etc.), and these interferences will reduce the signal quality and even cause communication interruptions or equipment failures.

[0003] Traditional electromagnetic shielding materials and methods are usually static, and their shielding effects are fixed during design and manufacturing and cannot be dynamically adjusted according to environmental changes. When the intensity or frequency of the interference source changes, static shielding materials may not be able to effectively suppress the interference. In a complex electromagnetic environment, a single shielding strategy is difficult to cope with the combined effects of multiple interference sources. Traditional signal enhancement algorithms (such as fixed filters) usually work based on preset parameters and cannot be dynamically adjusted according to real-time environmental changes. When the frequency or intensity of the interference signal changes, the fixed filter may not be able to effectively separate the target signal and the interference signal. In a dynamic environment, the signal enhancement effect is unstable and may cause signal distortion or loss. Existing systems usually lack the ability to accurately sense and locate interference sources, making it difficult to achieve targeted shielding and signal enhancement. It is impossible to accurately identify the location, intensity, and spectral characteristics of the interference source, resulting in insufficient targeting of shielding and enhancement strategies. In a multi-interference source environment, it is difficult to distinguish between the main interference and the secondary interference, and the resource allocation is unreasonable. Summary of the Invention

[0004] In view of the above or existing problems of the adaptive electromagnetic interference shielding and signal enhancement system, the present invention is proposed.

[0005] To solve the above technical problems, the present invention provides the following technical solutions:

[0006] An embodiment of the present invention provides an adaptive electromagnetic interference shielding and signal enhancement system, including: a signal feature analysis module, configured to detect electromagnetic interference signals and target signals in the system in real time through spectral analysis methods, and extract frequency domain features using digital signal processing techniques;

[0007] a dynamic shielding design module, configured to design dynamically adjustable shielding materials according to the spectral analysis results and automatically adjust the shielding effect;

[0008] a signal enhancement module, configured to enhance the signal by using adaptive filtering techniques, and in the process of signal enhancement, adjust the parameters of the filter in real time in combination with a feedback mechanism;

[0009] An intelligent adjustment module, which is used to intelligently adjust the shielding effect and signal enhancement strategy according to real-time environmental changes, combine multi-modal perception technologies, realize the linkage between sensors and algorithms, and automatically adjust the shielding intensity and signal gain according to the position and intensity of the interference source;

[0010] A feedback adjustment module, which is used to continuously monitor the intensity of electromagnetic interference, dynamically adjust the shielding strategy and the parameters of the enhancement algorithm based on the feedback signal, introduce the adaptive control theory, quickly respond to the changes of interference signals, and avoid signal loss.

[0011] As a preferred embodiment of the adaptive electromagnetic interference shielding and signal enhancement system of the present invention, wherein: the real-time detection of electromagnetic interference signals and target signals in the system by the spectrum analysis method includes:

[0012] Perform Fourier transform on the signal to convert the time-domain signal into a frequency-domain signal. The expression of FFT is:

[0013]

[0014] Wherein, S(f) is the representation of s(t) in the frequency domain, where the amplitude represents the intensity of the signal at this frequency component, the phase represents the phase information of this frequency component, s(t) is the original time-domain signal, representing the form of the signal changing with time, e -j2πft is the complex exponential function, f is the frequency, t is the time, and j is the imaginary unit;

[0015] After being processed by FFT, the signal is represented as the sum of different frequency components, and each frequency component corresponds to an amplitude and a phase.

[0016] As a preferred embodiment of the adaptive electromagnetic interference shielding and signal enhancement system of the present invention, wherein: the real-time detection of electromagnetic interference signals and target signals in the system by the spectrum analysis method further includes:

[0017] Use SVM to classify the signals, identify harmful interference signals and useful signals from them, and set the training set as:

[0018]

[0019] Wherein, x i is the feature vector of the i-th signal sample, and y i is the label of this sample;

[0020] Maximize the interval between categories through training to find an optimal hyperplane:

[0021]

[0022] where \(w\) is the normal vector of the hyperplane, \(b\) is the bias term of the hyperplane, and \(\xi\) i is the slack variable, \(C\) is the penalty parameter that controls the penalty degree of the slack variable;

[0023] After training the model, for a new signal sample \(x\), its classification result is judged by the following discriminant function:

[0024] \(y = sign(w\) T \(x + b)\)

[0025] If \(y = +1\), the signal is classified as a useful signal; if \(y = -1\), the signal is classified as an interference signal.

[0026] As a preferred solution of the adaptive electromagnetic interference shielding and signal enhancement system described in the present invention, wherein: the extraction of frequency-domain features using digital signal processing technology includes:

[0027] Converting the time-domain signal into a frequency-domain signal through FFT, and extracting frequency-domain feature indicators from the frequency-domain signal, including spectral amplitude, spectral flatness, spectral center, spectral width, and spectral power density.

[0028] As a preferred solution of the adaptive electromagnetic interference shielding and signal enhancement system described in the present invention, wherein: designing a dynamically adjustable shielding material according to the spectral analysis results to automatically adjust the shielding effect, including:

[0029] The conductivity and permeability of the shielding material are adaptively adjusted according to the frequency and intensity of the interference signal. Using adjustable conductive materials to ensure the maximization of the shielding effect. When combating high-frequency interference, the adjustment of the material is achieved through an external electric field or temperature change. The shielding effect is expressed by the following formula:

[0030]

[0031] where \(Z\) screen is the shielding impedance, \(\sigma\) mat is the conductivity of the material, \(\omega\) is the angular frequency of the signal, and \(\mu\) mat is the permeability of the material.

[0032] As a preferred solution of the adaptive electromagnetic interference shielding and signal enhancement system described in the present invention, wherein: enhancing the signal by using adaptive filtering technology, including:

[0033] Using the LMS algorithm to adjust its coefficients to minimize the error between the input signal and the desired signal. Setting the initial filter coefficients, calculating the output of the current filter, calculating the error between the filter output and the desired signal, and adjusting the coefficients of the filter according to the error. The update rule is:

[0034] \(w\) n+1= w n + μ·e n ·x n

[0035] where w n is the filter coefficient, μ is the step factor, e n is the error, and x n is the input signal;

[0036] The input signal and the desired signal are input into the adaptive filter, the error between the current output and the desired signal is calculated, and the filter coefficient is dynamically updated according to the error, and feedback is performed according to the LMS algorithm to continuously adjust the filter coefficient.

[0037] As a preferred solution of the adaptive electromagnetic interference shielding and signal enhancement system described in the present invention, wherein: during the signal enhancement process, the parameters of the filter are adjusted in real time in combination with the feedback mechanism, including:

[0038] The filter processes the input signal and generates an output signal:

[0039]

[0040] where y(n) is the output of the filter, x(n - i) is the delayed sample of the input signal, w i (n) is the filter coefficient, and M is the order of the filter;

[0041] Calculate the error between the filter output and the desired signal:

[0042] e(n) = d(n) - y(n)

[0043] where e(n) is the error signal, d(n) is the desired signal, and y(n) is the filter output signal.

[0044] As a preferred solution of the adaptive electromagnetic interference shielding and signal enhancement system described in the present invention, wherein: according to the real-time environmental changes, the shielding effect and the signal enhancement strategy are intelligently adjusted, including:

[0045] The bandpass filter allows the frequency band of the target signal to pass through, suppresses the interference signals in other frequency bands, dynamically adjusts the filter coefficient according to the error signal fed back in real time, enhances the target signal and removes the interference;

[0046] According to the quality of the signal and the intensity of the interference source, the conductivity or magnetic permeability of the shielding material is dynamically adjusted; according to the relative positions of the signal source and the interference source, the shielding position and shape are dynamically adjusted; according to the real-time spectrum analysis result, the shielding ability of the shielding material for a specific frequency band is adjusted, and in a multi-band interference environment, the influence of the interference is reduced by local shielding.

[0047] As a preferred embodiment of the adaptive electromagnetic interference shielding and signal enhancement system of the present invention, it includes: integrating multi-modal sensing technologies to achieve the linkage between sensors and algorithms, and automatically adjusting the shielding intensity and signal gain according to the position and intensity of the interference source, including:

[0048] Fuse data from different sensors, use deep learning algorithms to identify the position, intensity, and type of the interference source, and determine the spatial position of the interference source by combining the time difference, phase difference, or intensity difference of multi-sensor data with the triangulation algorithm;

[0049] When the interference source approaches the target signal, increase the shielding intensity and optimize the signal gain. When the interference source moves away from the target signal, reduce the shielding intensity to save energy consumption;

[0050] Automatically adjust the electromagnetic parameters of the shielding material according to the intensity of the interference source to achieve the best shielding effect; through intelligent materials or electromagnetic shielding arrays, dynamically adjust the bandwidth, center frequency, and gain parameters of the filter according to the position and intensity of the interference source to ensure the clarity and integrity of the target signal.

[0051] As a preferred embodiment of the adaptive electromagnetic interference shielding and signal enhancement system of the present invention, it includes: continuously monitoring the intensity of electromagnetic interference, dynamically adjusting the parameters of the shielding strategy and enhancement algorithm based on the feedback signal, introducing the adaptive control theory, quickly responding to the changes in the interference signal, and avoiding signal loss, including:

[0052] Quantify the intensity of the monitored electromagnetic interference signal into specific values, set the interference intensity threshold, and trigger the dynamic adjustment mechanism when the monitored interference intensity exceeds the threshold;

[0053] During the shielding and signal enhancement process, collect the quality indicators of the target signal in real time, compare the quality indicators of the target signal with the preset optimization objectives, generate a feedback signal, and adjust the electromagnetic parameters or shielding structure of the shielding material according to the feedback signal;

[0054] Apply fuzzy logic to the adjustment of the shielding strategy and signal enhancement algorithm, and dynamically adjust the shielding intensity and signal gain according to the fuzzy level of the interference intensity; use a PID controller to adjust the shielding and enhancement parameters in real time according to the feedback signal.

[0055] The beneficial effects of the present invention are as follows: The present invention can dynamically adjust the shielding effect and signal enhancement strategy according to the changes in the real-time electromagnetic environment. Through spectrum analysis and multi-modal perception technology, the intensity, frequency, and position of interference signals are monitored in real time. Intelligent materials or tunable structures are used to dynamically adjust the electromagnetic parameters of the shielding material to achieve an efficient shielding effect. It can effectively suppress various types of electromagnetic interference, including high-frequency, low-frequency, and transient interference. Through multi-sensor fusion technology, the types and characteristics of interference sources are accurately identified to achieve targeted shielding. In a complex electromagnetic environment, it can handle multiple interference sources simultaneously to avoid signal distortion or loss. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0057] Figure 1 It is a schematic structural diagram of an adaptive electromagnetic interference shielding and signal enhancement system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0058] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention will be described in detail below with reference to the drawings of the specification.

[0059] Many specific details are set forth in the following description in order to provide a thorough understanding of the present invention. However, the present invention may be implemented in other ways different from those described herein. Those skilled in the art can make similar extensions without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0060] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation manner of the present invention. The appearances of "in one embodiment" in different places in this specification do not all refer to the same embodiment, nor are they separate or alternative embodiments that exclude each other with other embodiments.

[0061] Embodiment

[0062] S1: Real-time detect the electromagnetic interference signals and target signals in the system through spectrum analysis methods, and use digital signal processing technology to extract frequency-domain features.

[0063] Preferably, perform a Fourier transform on the signal to convert the time-domain signal into a frequency-domain signal. The expression of FFT is:

[0064]

[0065] Among them, S(f) is the representation of s(t) in the frequency domain, where the amplitude represents the intensity of the signal at that frequency component, and the phase represents the phase information of that frequency component. s(t) is the original time-domain signal, representing the form of the signal changing with time, and e -j2πft is the complex exponential function, f is the frequency, t is the time, and j is the imaginary unit;

[0066] After being processed by FFT, the signal is represented as the sum of different frequency components, and each frequency component corresponds to an amplitude and a phase.

[0067] Preferably, SVM is used to classify the signal to identify harmful interference signals and useful signals. The training set is set as:

[0068]

[0069] Among them, x i is the feature vector of the i-th signal sample, and y i is the label of this sample;

[0070] By training to maximize the margin between classes, an optimal hyperplane is found:

[0071]

[0072] Among them, w is the normal vector of the hyperplane, b is the bias term of the hyperplane, ξ i is the slack variable, and C is the penalty parameter, which controls the penalty degree of the slack variable;

[0073] After training the model, for a new signal sample x, its classification result is judged by the following discriminant function:

[0074] y = sign(w T x + b)

[0075] If y = +1, the signal is classified as a useful signal; if y = -1, the signal is classified as an interference signal.

[0076] Furthermore, assume that the time-domain signal s(t)s(t)s(t) is a composite signal composed of two sine waves with different frequencies:

[0077] s(t) = sin(2π50t) + 0.5sin(2π150t)s

[0078] Among them, the first term is a sine wave with a frequency of 50 Hz, and the second term is a sine wave with a frequency of 150 Hz. We discretize the signal s(t), set the sampling frequency to 1000 Hz, and the sampling time to 1 second, that is, the number of sampling points N = 1000.

[0079] The spectrum X(k) after FFT processing will display the frequency components contained in the signal. By calculating the amplitude and phase of each frequency component, the main frequency components in the signal can be identified.

[0080] Obvious peaks will appear at frequencies 50Hz, 50Hz and 150Hz, indicating the intensity of these two frequency components in the signal. At these two frequency points, the system can also provide the corresponding phase information, indicating the time offset of each frequency component relative to other components.

[0081] Furthermore, assume that the training set contains the following samples, each with a feature vector and a label (+1 represents a useful signal, -1 represents an interference signal):

[0082] Signal number Feature vector xi Label yi 1 [0.5,0.8,0.3] +1 2 [1.0,1.2,0.5] -1 3 [0.6,0.9,0.4] +1 4 [1.1,0.7,0.6] -1

[0083] Train the above training set with an SVM model and select an appropriate penalty parameter C for optimization. The training process will generate an optimal hyperplane to separate useful signals and interference signals.

[0084] Assume that there is now a new signal sample x = [0.8, 1.0, 0.4], and we input it into the trained SVM model for classification:

[0085] Calculate the discriminant function value: f(x) = w T x + bf(x);

[0086] Judge the category of the signal according to the sign of f(x)f(x)f(x):

[0087] If f(x) ≥ 0, the signal is classified as a useful signal; if f(x) < 0, the signal is classified as an interference signal.

[0088] S2: According to the spectrum analysis results, design a dynamically adjustable shielding material to automatically adjust the shielding effect.

[0089] Preferably, the conductivity and permeability of the shielding material are adaptively adjusted according to the frequency and intensity of the interference signal,

[0090] Use an adjustable conductive material to ensure the maximization of the shielding effect. When combating high-frequency interference, the material is adjusted through an external electric field or temperature change, and the shielding effect is expressed by the following formula:

[0091]

[0092] Among them, Z screen is the shielding impedance, σ mat is the conductivity of the material, ω is the angular frequency of the signal, μ matis the magnetic permeability of the material.

[0093] Furthermore, materials such as conductive polymers or liquid metals are used. For example, temperature-responsive polymer materials are used. When the temperature increases, the conductivity of the material enhances, thereby improving the shielding effect of low-frequency signals. Ferrite materials with relatively high magnetic permeability are selected, and their magnetic permeability is adjustable under the action of an external magnetic field. The magnetic permeability is controlled by electromagnetic regulation means (such as the magnetic field generated by current induction) so that the material can adaptively adjust when facing signals of different frequencies.

[0094] The adjustable conductivity material and the magnetic material are configured according to a specific hierarchical structure to form a composite material layer. The materials of each layer can be adjusted by temperature, electric field or external magnetic field according to interference signals of different frequencies, so as to achieve adaptive shielding. For example, low-frequency signals can be shielded by a material layer with high conductivity, while high-frequency signals are shielded by a material layer with relatively high magnetic permeability.

[0095] To achieve adaptive adjustment, it is necessary to monitor the frequency and intensity of the interference signal in real time and adjust the conductivity and magnetic permeability of the material through a feedback mechanism. For example: use a spectrum analysis instrument to detect the frequency and intensity of the interference signal in the environment in real time, and use the feedback mechanism to automatically adjust the conductivity and magnetic permeability of the material. For example, if a signal with a higher frequency is detected, the conductivity or magnetic permeability of the material is increased through temperature regulation or external electric field control to enhance the shielding effect of the high-frequency signal.

[0096] Furthermore, when an interference signal with a frequency of 3000 Hz is detected, the system needs to enhance the conductivity of the shielding material to block this high-frequency signal. Assume that the conductivity of the material under the reference condition is σbase = 1.5×10 7 . According to the feedback of the control system, temperature and external electric field regulation may lead to an increase in conductivity, and the formula is as follows:

[0097] σmat(T) = 1.5×10 7 ·(1 + 0.03×T)

[0098] Assume that the external temperature is adjusted to 30 °C (i.e., T = 30), then the conductivity becomes:

[0099] σmat(30) = 1.5×10 7 ·(1 + 0.03×30) = 1.5×10 7 ·1.9 = 2.85×10 7 S / m

[0100] When the system detects low-frequency interference, it will enhance the magnetic permeability according to magnetic field regulation. Assume that the base magnetic permeability is μ base = 1.2×10 -3H / m. By applying an external magnetic field, the magnetic permeability can be adjusted to:

[0101] μ mat = 1.2×10 -3 ·(1 + 0.05×H)

[0102] μmat(50) = 1.2×10 -3 ·(1 + 0.05×50) = 4.2×10 -3 H / m

[0103] In this way, the system can dynamically increase the magnetic permeability to counteract low-frequency interference.

[0104] S3: By using adaptive filtering technology, enhance the signal. During the signal enhancement process, combine a feedback mechanism to adjust the parameters of the filter in real time.

[0105] Preferably, use the LMS algorithm to adjust its coefficients to minimize the error between the input signal and the desired signal. Set the initial filter coefficients, calculate the output of the current filter, calculate the error between the filter output and the desired signal, and adjust the filter coefficients according to the error. The update rule is:

[0106] w n+1 = w n + μ·e n ·x n

[0107] where, w n is the filter coefficient, μ is the step size factor, e n is the error, x n is the input signal;

[0108] Input the input signal and the desired signal into the adaptive filter, calculate the error between the current output and the desired signal, and dynamically update the filter coefficients according to the error. According to the feedback of the LMS algorithm, continuously adjust the filter coefficients.

[0109] Preferably, the filter processes the input signal and generates an output signal:

[0110]

[0111] where, y(n) is the output of the filter, x(n - i) are the delayed samples of the input signal, w i (n) are the filter coefficients, and M is the order of the filter;

[0112] Calculate the error between the filter output and the desired signal:

[0113] e(n) = d(n) - y(n), where e(n) is the error signal, d(n) is the desired signal, and y(n) is the filter output signal.

[0114] Furthermore, there is a speech signal x(n) which contains noise. The goal is to recover the clear speech signal d(n) from this noisy signal through an adaptive filter.

[0115] Set the filter order MMM (for example, 10), initialize the filter coefficients wi(0) = 0, that is, all coefficients are initially zero. Set the step size factor μ, which determines the rate of coefficient update (for example, choose a small value, such as μ = 0.01). The input signal x(n) is the signal with noise. The desired signal d(n) is the clean speech signal, that is, the ideal signal without noise.

[0116] Use the delayed samples x(n - i) of the input signal and the filter coefficients wi(n) to calculate the filter output y(n):

[0117] y(n) = w0(n)·x(n) + w1(n)·x(n - 1) + … + w M-1 (n)·x(n - M + 1)

[0118] Calculate the error e(n) between the filter output y(n) and the desired signal d(n):

[0119] e(n) = d(n) - y(n)

[0120] Use the LMS algorithm to update the filter coefficients wi(n):

[0121] wi(n + 1) = wi(n) + μ·e(n)·x(n - i)

[0122] This step will adjust the filter coefficients according to the error feedback to make them more adaptable to the characteristics of the input signal. Repeat the above steps until the error e(n) converges and the filter coefficients are stable. At this time, the filter output y(n) should be close to the desired signal d(n), that is, the speech signal after removing noise.

[0123] S4: According to the real-time environmental changes, intelligently adjust the shielding effect and signal enhancement strategy, combine multi-modal perception technology, realize the linkage between the sensor and the algorithm, and automatically adjust the shielding intensity and signal gain according to the position and intensity of the interference source.

[0124] Preferably, allow the frequency band of the target signal to pass through the band-pass filter, suppress the interference signals in other frequency bands, dynamically adjust the filter coefficients according to the error signal of the real-time feedback, enhance the target signal and remove the interference;

[0125] Dynamically adjust the conductivity or magnetic permeability of the shielding material according to the signal quality and interference source intensity; dynamically adjust the shielding position and shape according to the relative positions of the signal source and the interference source; adjust the shielding ability of the shielding material for specific frequency bands according to the real-time spectrum analysis results, and reduce the influence of interference through local shielding in a multi-band interference environment.

[0126] Preferably, fuse the data from different sensors, use deep learning algorithms to identify the position, intensity, and type of the interference source, and determine the spatial position of the interference source through the time difference, phase difference, or intensity difference of multi-sensor data, combined with the triangulation algorithm;

[0127] When the interference source approaches the target signal, increase the shielding intensity and optimize the signal gain; when the interference source moves away from the target signal, reduce the shielding intensity to save energy consumption;

[0128] Automatically adjust the electromagnetic parameters of the shielding material according to the intensity of the interference source to achieve the best shielding effect; through intelligent materials or electromagnetic shielding arrays, dynamically adjust the bandwidth, center frequency, and gain parameters of the filter according to the position and intensity of the interference source to ensure the clarity and integrity of the target signal.

[0129] Furthermore, determine the spatial position of the interference source using the triangulation algorithm based on multi-sensor data. Assume we have N sensors (e.g., 3 receiving antennas) with known positions, and each sensor can receive the signal from the interference source. The core idea of the triangulation algorithm is to estimate the spatial coordinates of the interference source through the signal time difference, phase difference, or signal intensity difference between different sensors.

[0130] Assume the signal received by sensor i is Si(t), where i = 1, 2, …, N;

[0131] By comparing the received signals of different sensors, calculate their time difference or phase difference Δt ij = t j - t i where, t i and t j are the times when sensors i and j receive the signals respectively. Based on the known sensor positions and time difference, locate the position P = (x, y, z) of the interference source through geometric calculation.

[0132] Furthermore, adjust the conductivity (σ mat ) and magnetic permeability (μ mat ) of the shielding material according to the intensities of different interference sources. The relationship between the conductivity σ mat and frequency f is:

[0133]

[0134] where, σbase is the reference conductivity of the shielding material, ασ is the adjustment coefficient of the conductivity, A i is the interference intensity at the current frequency, A max is the maximum interference intensity;

[0135] The magnetic permeability μ mat and the relationship with the frequency f:

[0136]

[0137] wherein, μ base is the reference magnetic permeability of the shielding material, α μ is the adjustment coefficient of the magnetic permeability;

[0138] Assume the reference conductivity σ base = 1.5×10 7 S / m; the reference magnetic permeability μ base = 1.2×10 -3 H / m, the adjustment coefficient α σ = 0.1, α μ = 0.05; for the frequency 5000Hz and the intensity 25dB:

[0139] σ mat = 1.65×10 7 S / m; μ mat = 1.26×10 -3 H / m. Through the above calculations, the conductivity and magnetic permeability of the shielding material have been dynamically adjusted according to the interference source intensity.

[0140] S5: Continuously monitor the intensity of electromagnetic interference, dynamically adjust the shielding strategy and the parameters of the enhancement algorithm based on the feedback signal, introduce the adaptive control theory, quickly respond to the change of the interference signal, and avoid signal loss.

[0141] Preferably, quantify the intensity of the monitored electromagnetic interference signal into specific values, set the interference intensity threshold, and trigger the dynamic adjustment mechanism when the monitored interference intensity exceeds the threshold;

[0142] During the shielding and signal enhancement process, collect the quality indicators of the target signal in real time, compare the quality indicators of the target signal with the preset optimization target to generate a feedback signal, and adjust the electromagnetic parameters or shielding structure of the shielding material according to the feedback signal; apply fuzzy logic to the adjustment of the shielding strategy and the signal enhancement algorithm, and dynamically adjust the shielding intensity and signal gain according to the fuzzy level of the interference intensity; use a PID controller to adjust the shielding and enhancement parameters in real time according to the feedback signal.

[0143] Furthermore, the system first monitors the electromagnetic interference signals in the environment in real time through various sensors (such as receiving antennas, electromagnetic wave detectors). These sensors provide data such as the intensity, spectrum, and phase of the interference signals, and the system quantifies the intensity of the interference signals based on this data.

[0144] Through spectrum analysis and signal intensity calculation, the intensity of the interference signal is quantified into specific values:

[0145]

[0146] where P interference is the power of the interference signal, and P ref is the reference power.

[0147] Set an interference intensity threshold I threshold , and when the monitored interference intensity exceeds this threshold, trigger the dynamic adjustment mechanism. For example, set the threshold I threshold =-70dBm. When I interference >I threshold , the system starts adaptive adjustment.

[0148] Furthermore, monitor the quality of the target Wi-Fi signal through the sensor. Assume the quality of the target signal is Starget = 90dB; the intensity of the monitored interference signal is Sinterference = 75dB;

[0149] Error calculation:

[0150] e(t)=Starget - Sinterference = 90dB - 75dB = 15dB

[0151] This error represents the gap between the quality of the target signal and the interference signal;

[0152] Assume the parameters of the PID controller are: Kp = 1, Ki = 0.5, Kd = 0.2; the output of the controller is calculated as follows:

[0153] P = Kp·e(t)=1·15 = 15, I = Ki·∫e(t)dt = 2.5, D = Kd·ddte(t)=0.2·0.1 = 0.02;

[0154] Total output:

[0155] u(t)=P + I + D = 15 + 2.5 + 0.02 = 17.52;

[0156] According to the output signal (17.52) of the PID controller, dynamically adjust the conductivity and permeability of the shielding material, as well as the bandwidth, center frequency, and gain parameters of the filter:

[0157] Set the bandwidth to an appropriate value according to the frequencies of the interference sources (such as 2000 Hz and 5000 Hz) to isolate these frequency bands;

[0158] Adjust the gain to about 17.52 dB to enhance the target signal;

[0159] According to the strength of the feedback signal, enhance the shielding ability against the interference frequency band by adjusting the conductivity and permeability of the material.

[0160] In the description of the present invention, it should be noted that the terms "first", "second", and "third" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0161] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0162] In several embodiments provided by the present invention, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some communication interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0163] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0164] In addition, the functional units in each embodiment of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0165] Finally, it should be noted that the above-described embodiments are only specific embodiments of the present invention, which are used to illustrate the technical solutions of the present invention rather than to limit it. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that any person skilled in the art within the technical scope disclosed by the present invention can still modify the technical solutions described in the foregoing embodiments, or can easily think of changes, or make equivalent replacements for some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

[0166] In addition, although the operations of the method of the present invention are described in a specific order in the drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step for execution, and / or one step may be decomposed into multiple steps for execution.

Claims

1. An adaptive electromagnetic interference shielding and signal enhancement system, characterized in that: include: The signal feature analysis module is used to detect the electromagnetic interference signal and target signal in the system in real time through the spectrum analysis method, and extract the frequency domain features using digital signal processing technology; Dynamic shielding design module, which is used to design dynamically adjusted shielding materials and automatically adjust the shielding effect according to the spectrum analysis results; The signal enhancement module is used to enhance the signal by using adaptive filtering technology. During the signal enhancement process, the filter parameters are adjusted in real time in combination with the feedback mechanism; Intelligent adjustment module, which is used to intelligently adjust the shielding effect and signal enhancement strategy according to real-time environmental changes. It combines multimodal sensing technology to realize the linkage between sensors and algorithms, and automatically adjusts the shielding strength and signal gain according to the location and strength of the interference source. The feedback adjustment module is used to continuously monitor the intensity of electromagnetic interference, dynamically adjust the parameters of the shielding strategy and enhancement algorithm based on the feedback signal, introduce adaptive control theory, quickly respond to changes in interference signals, and avoid signal loss.

2. The adaptive electromagnetic interference shielding and signal enhancement system according to claim 1, characterized in that: The method of detecting electromagnetic interference signals and target signals in the system in real time by spectrum analysis method comprises: Perform Fourier transform on the signal to convert the time domain signal into the frequency domain signal. The expression of FFT is: Among them, S(f) is the representation of s(t) in the frequency domain, where the amplitude represents the strength of the signal at the frequency component, the phase represents the phase information of the frequency component, s(t) is the original time domain signal, which represents the shape of the signal changing over time, and e -j2πft is a complex exponential function, f is the frequency, t is the time, and j is the imaginary unit; After FFT processing, the signal is represented as the sum of different frequency components, each frequency component corresponds to an amplitude and phase.

3. The adaptive electromagnetic interference shielding and signal enhancement system according to claim 1, characterized in that: The real-time detection of electromagnetic interference signals and target signals in the system by spectrum analysis method also includes: Use SVM to classify the signal and identify harmful interference signals and useful signals. Set the training set as: Among them, x i is the eigenvector of the ith signal sample, y i is the label of the sample; By training to maximize the interval between categories, an optimal hyperplane is found: Where w is the normal vector of the hyperplane, b is the bias term of the hyperplane, ξ i is the slack variable, C is the penalty parameter, which controls the degree of penalty for the slack variable; After the model is trained, for a new signal sample x, its classification result is judged by the following discriminant function: y=sign(w T x+b) If y=+1, the signal is classified as a useful signal; if y=-1, the signal is classified as an interference signal.

4. The adaptive electromagnetic interference shielding and signal enhancement system according to claim 1, characterized in that: The method of extracting frequency domain features using digital signal processing technology includes: The time domain signal is converted into a frequency domain signal through FFT, and the frequency domain characteristic indicators including spectrum amplitude, spectrum flatness, spectrum center, spectrum width and spectrum power density are extracted from the frequency domain signal.

5. The adaptive electromagnetic interference shielding and signal enhancement system according to claim 1, characterized in that: The method of designing a dynamically adjusted shielding material based on the spectrum analysis results to automatically adjust the shielding effect includes: The conductivity and magnetic permeability of the shielding material are adaptively adjusted according to the frequency and intensity of the interference signal. The use of adjustable conductive materials ensures the maximum shielding effect. When counteracting high-frequency interference, the material is adjusted through external electric fields or temperature changes. The shielding effect is expressed by the following formula: Among them, Z screen is the shield impedance, σ mat is the conductivity of the material, ω is the angular frequency of the signal, μ mat is the magnetic permeability of the material.

6. The adaptive electromagnetic interference shielding and signal enhancement system according to claim 1, characterized in that: The signal is enhanced by using adaptive filtering technology, including: Use the LMS algorithm to adjust its coefficients to minimize the error between the input signal and the expected signal, set the initial filter coefficients, calculate the output of the current filter, calculate the error between the filter output and the expected signal, and adjust the filter coefficients according to the error. The update rule is: w n+1 =w n +μ·e n ·x n Among them, w n is the filter coefficient, μ is the step size factor, e n is the error, x n is the input signal; The input signal and the expected signal are input into the adaptive filter, the error between the current output and the expected signal is calculated, and the filter coefficients are dynamically updated according to the error. The filter coefficients are continuously adjusted according to the feedback of the LMS algorithm.

7. The adaptive electromagnetic interference shielding and signal enhancement system according to claim 1, characterized in that: In the signal enhancement process, the parameters of the filter are adjusted in real time in combination with the feedback mechanism, including: A filter processes an input signal and generates an output signal: Where y(n) is the output of the filter, x(ni) is the delayed sample of the input signal, and w i (n) is the filter coefficient, M is the filter order; Calculate the error between the filter output and the desired signal: e(n)=d(n)-y(n) Where e(n) is the error signal, d(n) is the desired signal, and y(n) is the filter output signal.

8. The adaptive electromagnetic interference shielding and signal enhancement system according to claim 1, characterized in that: The intelligent adjustment of shielding effect and signal enhancement strategy according to real-time environmental changes includes: The bandpass filter allows the frequency band of the target signal to pass through, suppresses interference signals in other frequency bands, and dynamically adjusts the filter coefficients according to the real-time feedback error signal to enhance the target signal and remove interference; Dynamically adjust the conductivity or magnetic permeability of the shielding material according to the signal quality and the strength of the interference source; dynamically adjust the shielding position and shape according to the relative positions of the signal source and the interference source; adjust the shielding ability of the shielding material for a specific frequency band according to the real-time spectrum analysis results, and reduce the impact of interference through local shielding in a multi-band interference environment.

9. The adaptive electromagnetic interference shielding and signal enhancement system according to claim 1, characterized in that: The multimodal sensing technology is combined to realize the linkage between sensors and algorithms, and automatically adjust the shielding strength and signal gain according to the location and strength of the interference source, including: The data from different sensors are integrated, and the location, strength and type of the interference source are identified using a deep learning algorithm. The spatial location of the interference source is determined by combining the time difference, phase difference or strength difference of multi-sensor data with a triangulation positioning algorithm. When the interference source is close to the target signal, the shielding strength is increased and the signal gain is optimized. When the interference source is far away from the target signal, the shielding strength is reduced to save energy. According to the intensity of the interference source, the electromagnetic parameters of the shielding material are automatically adjusted to achieve the best shielding effect; through smart materials or electromagnetic shielding arrays, the bandwidth, center frequency and gain parameters of the filter are dynamically adjusted according to the location and intensity of the interference source to ensure the clarity and integrity of the target signal.

10. The adaptive electromagnetic interference shielding and signal enhancement system according to claim 1, characterized in that: The method of continuously monitoring the intensity of electromagnetic interference, dynamically adjusting the parameters of the shielding strategy and the enhancement algorithm based on the feedback signal, introducing the adaptive control theory, and quickly responding to the change of the interference signal to avoid signal loss includes: Quantify the monitored electromagnetic interference signal strength into a specific value, set the interference strength threshold, and trigger the dynamic adjustment mechanism when the monitored interference strength exceeds the threshold; During the shielding and signal enhancement process, the quality index of the target signal is collected in real time, the quality index of the target signal is compared with the preset optimization target, a feedback signal is generated, and the electromagnetic parameters of the shielding material or the shielding structure is adjusted according to the feedback signal; Fuzzy logic is applied to the adjustment of shielding strategy and signal enhancement algorithm. Shielding strength and signal gain are dynamically adjusted according to the fuzzy level of interference intensity. PID controller is used to adjust shielding and enhancement parameters in real time according to feedback signals.

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