Frequency adaptive pulse noise filter system and adaptive adjustment method

Abstract

The invention discloses a frequency self-adaptive pulse noise filter system and a self-adaptive adjustment method, and relates to the field of filter self-adaptive adjustment, the frequency self-adaptive pulse noise filter system detects and identifies EMI (Electro-Magnetic Interference) frequency in real time by utilizing the super-sensitivity of a quantum entanglement state, and dynamically suppresses interference of specific frequency through a self-adaptive filter adjustment module. The response speed and the adaptability of the system are improved, and accurate suppression of EMI can be realized on the microscopic level based on the quantum mechanics principle, so that the stability and the precision of the quantum calculation and measurement technology are remarkably improved.

Description

Technical Field

[0001] The invention relates to the field of filter adaptive adjustment, in particular to a frequency adaptive pulse noise filter system and an adaptive adjustment method. Background Art

[0002] In modern electronic systems, electromagnetic compatibility (EMC) is a critical area that ensures that electronic devices can work properly in an electromagnetic environment without affecting other devices. Existing technologies usually use two methods, passive and active, to achieve electromagnetic compatibility. Passive methods include the use of shielding materials, filters, grounding and wiring techniques to reduce the generation and propagation of electromagnetic interference (EMI). For example, shielding technology uses metal housings or coatings to block the influence of external electromagnetic fields on sensitive circuits. Filters are installed on power lines and signal lines to filter out interference signals within a specific frequency range.

[0003] Active methods involve using complex algorithms and adaptive techniques to dynamically adjust system parameters to adapt to the changing electromagnetic environment. For example, some high-end communication equipment uses adaptive filters and smart antenna technology to dynamically adjust its operating frequency and transmission power according to changes in the signal environment. In addition, technologies such as digital signal processing (DSP) and field programmable gate array (FPGA) are also widely used to monitor and suppress EMI in real time.

[0004] In the field of quantum computing, as the manipulation technology of quantum bits becomes increasingly mature, the development of quantum algorithms and quantum communication protocols has also made significant progress. Quantum computers use the principles of quantum superposition and entanglement to demonstrate computing capabilities that surpass traditional computers. However, quantum systems are extremely sensitive to the external environment, especially to electromagnetic interference. In order to protect quantum information from being destroyed, quantum computing devices usually need to operate in a highly controlled environment, including the operation of superconducting quantum bits at extremely low temperatures and the high vacuum environment in ion trap quantum computers.

[0005] Although existing technologies have made certain achievements in electromagnetic compatibility, they still have significant defects when facing EMI problems in quantum computing and precision measurement technology. First, traditional EMC methods mainly target the interference of macroscopic electronic devices, while quantum devices are much more sensitive to EMI than traditional devices, which requires higher standards of EMI suppression technology. Second, the response speed and adaptability of existing technologies are usually not enough to cope with rapidly changing electromagnetic environments. Especially in the process of quantum computing, tiny EMI can cause decoherence of quantum states, thereby causing calculation errors. Summary of the invention

[0006] The present invention aims at the defects of the prior art and proposes a frequency adaptive impulse noise filter system and an adaptive adjustment method. The interference of a specific frequency is dynamically suppressed by an adaptive filter adjustment module.

[0007] Among them, a frequency adaptive impulse noise filter system includes:

[0008] The quantum state change detection module is used to generate the entangled state of quantum bit pairs for detecting electromagnetic changes, measure the changes in the quantum bit state, and identify the frequency components of EMI;

[0009] Adaptive frequency tracking module, which uses Kalman filter to combine historical and real-time data to estimate the dynamic changes of EMI frequency and track the changes of EMI frequency in real time;

[0010] An adaptive filter adjustment module is used to dynamically adjust the filter parameters to match the current EMI frequency based on the prediction information provided by the adaptive frequency tracking module;

[0011] A quantum control signal generation module, used to convert the predicted EMI frequency into a control signal, and drive the adaptive filter adjustment module according to the control signal;

[0012] The electromagnetic field neutralization module is used to generate an electromagnetic field opposite to the detected EMI to neutralize the electromagnetic interference.

[0013] Furthermore, the adaptive frequency tracking module specifically includes:

[0014] A data acquisition unit, used to collect data on changes in the state of quantum bits;

[0015] A frequency analysis unit is used to perform Fourier transform on the collected data, convert the time domain signal into the frequency domain through Fourier transform, and identify the interference frequency;

[0016] A Kalman filter implementation unit, used for processing the output of the frequency analysis unit through a Kalman filter algorithm and performing real-time estimation of the EMI frequency;

[0017] The prediction and trend analysis unit is used to predict the changing trend of EMI frequency based on historical data and real-time estimated values ​​of EMI frequency.

[0018] Furthermore, the adaptive filter adjustment module specifically includes:

[0019] A frequency response analysis unit is used to analyze the frequency response of the current filter, compare it with the output of the adaptive frequency tracking module, and adjust the parameters;

[0020] A parameter adjustment decision unit is used to make a decision on the adjustment direction and amplitude of the filter parameters according to the result of the frequency response analysis unit;

[0021] The tunable element control unit is used to receive instructions from the parameter adjustment decision unit and control the tunable element to adjust the center frequency and bandwidth of the filter in real time.

[0022] Furthermore, the adaptive filter adjustment module also includes a closed-loop feedback calibration unit, which is used to monitor the actual effect of the filter adjustment through a closed-loop feedback mechanism and perform calibration optimization.

[0023] Furthermore, in the frequency response analysis unit, the parameter adjustment process is to dynamically adjust the filter parameters through the filter transfer function according to the predicted EMI frequency, which is specifically expressed as follows:

[0024]

[0025] Wherein, H(f) is the transfer function of the filter, which is used to represent the gain of the filter for the signal of frequency f, ω0 represents the center angular frequency of the filter, in radians per second, ω represents the angular frequency of the input signal, in radians per second, Q is the quality factor, which represents the selectivity of the filter, that is, the ability of the filter to select frequencies near the center frequency, and j is an imaginary unit, which represents the imaginary part in the transfer function and is used to describe the influence of the filter on the signal phase.

[0026] Furthermore, a frequency adaptive pulse noise filter adaptive adjustment method is proposed, which is implemented based on the frequency adaptive pulse noise filter system described in any one of the above items, and includes the following steps:

[0027] S1. Generate an entangled state of a qubit pair for detecting electromagnetic changes, measure the change in the qubit state, and identify the frequency component of EMI;

[0028] S2. Use Kalman filter to combine historical and real-time data to estimate the dynamic changes of EMI frequency and track the changes of EMI frequency in real time;

[0029] S3. Dynamically adjust the filter parameters to match the current EMI frequency based on the prediction information provided by the adaptive frequency tracking module;

[0030] S4. Convert the predicted EMI frequency into a control signal, and drive the adaptive filter to adjust according to the control signal;

[0031] S5. Generate an electromagnetic field opposite to the detected EMI to neutralize the electromagnetic interference.

[0032] Furthermore, the step S2 specifically includes the following sub-steps:

[0033] S201. Collecting quantum bit state change data;

[0034] S202. Perform Fourier transform on the collected data, convert the time domain signal into the frequency domain through Fourier transform, and identify the interference frequency;

[0035] S203. Process the output of the frequency analysis unit through the Kalman filter algorithm and estimate the EMI frequency in real time; S204. Predict the change trend of the EMI frequency based on historical data and the real-time estimated value of the EMI frequency.

[0036] Furthermore, the step S3 specifically includes the following sub-steps:

[0037] S301. Analyze the frequency response of the current filter and compare it with the output of the adaptive frequency tracking module to adjust the parameters;

[0038] S302. Based on the results of the frequency response analysis, make decisions on the adjustment direction and amplitude of the filter parameters;

[0039] S303. Receive instructions from the parameter adjustment decision unit, and control the tunable element to adjust the center frequency and bandwidth of the filter in real time.

[0040] Furthermore, after step S303, step S304 is also included: monitoring the actual effect of the filter after adjustment through a closed-loop feedback mechanism, and performing calibration optimization.

[0041] Furthermore, in step S301, the parameter adjustment process is to dynamically adjust the filter parameters through the filter transfer function according to the predicted EMI frequency, which is specifically expressed as follows:

[0042]

[0043] Wherein, H(f) is the transfer function of the filter, which is used to represent the gain of the filter for the signal of frequency f, ω0 represents the center angular frequency of the filter, in radians per second, ω represents the angular frequency of the input signal, in radians per second, Q is the quality factor, which represents the selectivity of the filter, that is, the ability of the filter to select frequencies near the center frequency, and j is an imaginary unit, which represents the imaginary part in the transfer function and is used to describe the influence of the filter on the signal phase.

[0044] The beneficial effects of the invention are:

[0045] The present invention utilizes the ultra-sensitivity of quantum entangled states to detect and identify EMI frequencies in real time, and dynamically suppresses interference of specific frequencies through an adaptive filter adjustment module, which not only improves the response speed and adaptability of the system, but also, because it is based on the principles of quantum mechanics, can achieve precise suppression of EMI at the microscopic level, thereby significantly improving the stability and accuracy of quantum computing and measurement technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A method flow chart of a frequency adaptive impulse noise filter adaptive adjustment method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following.

[0048] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is further described in detail in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0049] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative work are within the scope of protection of the present invention. It should be noted that relational terms such as the terms "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0050] Moreover, the terms "comprises", "includes" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a list of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or apparatus. In the absence of more restrictions, an element defined by the phrase "comprises a ..." does not exclude the presence of additional identical elements in the process, method, article or apparatus that includes the element.

[0051] The features and performance of the present invention are further described in detail below in conjunction with the embodiments.

[0052] Among them, a frequency adaptive impulse noise filter system includes:

[0053] The quantum state change detection module is used to generate the entangled state of quantum bit pairs for detecting electromagnetic changes, measure the changes in the quantum bit state, and identify the frequency components of EMI;

[0054] Adaptive frequency tracking module, which uses Kalman filter to combine historical and real-time data to estimate the dynamic changes of EMI frequency and track the changes of EMI frequency in real time;

[0055] An adaptive filter adjustment module is used to dynamically adjust the filter parameters to match the current EMI frequency based on the prediction information provided by the adaptive frequency tracking module;

[0056] A quantum control signal generation module, used to convert the predicted EMI frequency into a control signal, and drive the adaptive filter adjustment module according to the control signal;

[0057] The electromagnetic field neutralization module is used to generate an electromagnetic field opposite to the detected EMI to neutralize the electromagnetic interference.

[0058] Specifically, in the quantum state change detection module, the entangled state of multiple quantum bit pairs is generated to detect electromagnetic changes in the environment. The implementation process is as follows: through quantum gate operation, Hadamard gate or CNOT gate is used to prepare multiple pairs of Bell state entangled quantum bits, and the entanglement metric is F=(Tr(ρ AB ρ ideal )) 2 quantized, the F represents the entanglement fidelity, which is used to measure the closeness between the actual entangled state and the ideal entangled state, the Tr represents the trace function, which is used to express the expectation, and the ρ AB represents the density matrix of the actual two-qubit state, which is used to describe the state of the quantum system. ideal The density matrix representing the ideal maximum entangled state represents the best entangled state that can be achieved in theory. Furthermore, by measuring the state change of the quantum bit, the EMI frequency is identified using quantum state tomography or quantum Fourier transform, where the quantum Fourier transform is specifically expressed as: Among them, the represents the Fourier transform operation, which is used to convert the time domain signal into the frequency domain, and the Δ<σ z > represents the change in the expected value of the Pauli-Z operator of the quantum bit, the e -2πift It represents the exponential term, the complex exponential function in Fourier transform, which is used to convert the time domain signal into the frequency domain, and f represents the frequency.

[0059] Furthermore, the quantum control signal generation, specifically, converts the predicted EMI frequency into a corresponding control voltage or digital instruction for adjusting the filter parameters, and its feedback process is expressed as: V feedback (t) = V control (t)-k feedbac error(t), where V feedback (t) represents the feedback control voltage or signal at time t, which is used to adjust the system to compensate for the error, and the V control (t) represents the original control signal at time t, the k feedbac represents feedback gain, a proportional constant used to determine the influence of the error signal on the adjustment amplitude of the control signal, and error(t) represents the error signal at time t, which represents the difference between the expected output and the actual output.

[0060] Furthermore, the adaptive frequency tracking module specifically includes:

[0061] A data acquisition unit, used to collect data on changes in the state of quantum bits;

[0062] A frequency analysis unit is used to perform Fourier transform on the collected data, convert the time domain signal into the frequency domain through Fourier transform, and identify the interference frequency;

[0063] A Kalman filter implementation unit, used for processing the output of the frequency analysis unit through a Kalman filter algorithm and performing real-time estimation of the EMI frequency;

[0064] The prediction and trend analysis unit is used to predict the changing trend of EMI frequency based on historical data and real-time estimated values ​​of EMI frequency.

[0065] Specifically, the Kalman filter algorithm predicts the change of EMI frequency based on historical data, which is specifically expressed as:

[0066]

[0067] Among them, the representation, the representation, the representation, the representation, the representation, the representation, the representation.

[0068] Furthermore, the adaptive filter adjustment module specifically includes:

[0069] A frequency response analysis unit is used to analyze the frequency response of the current filter, compare it with the output of the adaptive frequency tracking module, and adjust the parameters;

[0070] A parameter adjustment decision unit is used to make a decision on the adjustment direction and amplitude of the filter parameters according to the result of the frequency response analysis unit;

[0071] The tunable element control unit is used to receive instructions from the parameter adjustment decision unit and control the tunable element to adjust the center frequency and bandwidth of the filter in real time.

[0072] Furthermore, the adaptive filter adjustment module also includes a closed-loop feedback calibration unit, which is used to monitor the actual effect of the filter adjustment through a closed-loop feedback mechanism and perform calibration optimization.

[0073] Furthermore, in the frequency response analysis unit, the parameter adjustment process is to dynamically adjust the filter parameters through the filter transfer function according to the predicted EMI frequency, which is specifically expressed as follows:

[0074]

[0075] Wherein, H(f) is the transfer function of the filter, which is used to represent the gain of the filter for the signal of frequency f, ω0 represents the center angular frequency of the filter, in radians per second, ω represents the angular frequency of the input signal, in radians per second, Q is the quality factor, which represents the selectivity of the filter, that is, the ability of the filter to select frequencies near the center frequency, and j is an imaginary unit, which represents the imaginary part in the transfer function and is used to describe the influence of the filter on the signal phase.

[0076] Furthermore, the quantum control signal generation module specifically includes:

[0077] A frequency prediction interface unit, used to receive the output of the adaptive frequency tracking module, i.e. the predicted EMI frequency, and convert the frequency data into a format required for control signal generation;

[0078] A control signal processor unit is used to design and generate corresponding control signals according to the predicted EMI frequency. Specifically, an algorithm is used to convert the frequency information into a voltage or current signal to drive the filter adjustment module;

[0079] A signal optimization and amplification unit, used to optimize and amplify the generated control signal to ensure that the signal has sufficient strength and stability to drive the adaptive filter adjustment module;

[0080] The signal transmission interface unit is used to transmit the optimized and amplified control signal to the adaptive filter adjustment module to ensure that the signal is not disturbed during the transmission process.

[0081] Furthermore, the electromagnetic field neutralization module specifically includes:

[0082] EMI detection and analysis unit, used to detect electromagnetic interference in the environment and analyze its characteristics, such as frequency and amplitude;

[0083] a neutralization signal generator unit for generating an opposite electromagnetic field signal according to the detected EMI characteristics;

[0084] The electromagnetic field transmitter unit is used to receive the output of the neutralization signal generator unit and convert it into an actual electromagnetic field to generate electromagnetic waves opposite to the EMI to neutralize the interference.

[0085] Furthermore, a frequency adaptive pulse noise filter adaptive adjustment method is proposed, such as Figure 1 The method is implemented based on the frequency adaptive pulse noise filter system described in any one of the above items, and comprises the following steps:

[0086] S1. Generate an entangled state of a qubit pair for detecting electromagnetic changes, measure the change in the qubit state, and identify the frequency component of EMI;

[0087] S2. Use Kalman filter to combine historical and real-time data to estimate the dynamic changes of EMI frequency and track the changes of EMI frequency in real time;

[0088] S3. Dynamically adjust the filter parameters to match the current EMI frequency based on the prediction information provided by the adaptive frequency tracking module;

[0089] S4. Convert the predicted EMI frequency into a control signal, and drive the adaptive filter to adjust according to the control signal;

[0090] S5. Generate an electromagnetic field opposite to the detected EMI to neutralize the electromagnetic interference.

[0091] Furthermore, the step S2 specifically includes the following sub-steps:

[0092] S201. Collecting quantum bit state change data;

[0093] S202. Perform Fourier transform on the collected data, convert the time domain signal into the frequency domain through Fourier transform, and identify the interference frequency;

[0094] S203. Process the output of the frequency analysis unit through the Kalman filter algorithm and estimate the EMI frequency in real time; S204. Predict the change trend of the EMI frequency based on historical data and the real-time estimated value of the EMI frequency.

[0095] Furthermore, the step S3 specifically includes the following sub-steps:

[0096] S301. Analyze the frequency response of the current filter and compare it with the output of the adaptive frequency tracking module to adjust the parameters;

[0097] S302. Based on the results of the frequency response analysis, make decisions on the adjustment direction and amplitude of the filter parameters;

[0098] S303. Receive instructions from the parameter adjustment decision unit, and control the tunable element to adjust the center frequency and bandwidth of the filter in real time.

[0099] Furthermore, after step S303, step S304 is also included: monitoring the actual effect of the filter after adjustment through a closed-loop feedback mechanism, and performing calibration optimization.

[0100] Furthermore, in step S301, the parameter adjustment process is to dynamically adjust the filter parameters through the filter transfer function according to the predicted EMI frequency, which is specifically expressed as follows:

[0101]

[0102] Wherein, H(f) is the transfer function of the filter, which is used to represent the gain of the filter for the signal of frequency f, ω0 represents the center angular frequency of the filter, in radians per second, ω represents the angular frequency of the input signal, in radians per second, Q is the quality factor, which represents the selectivity of the filter, that is, the ability of the filter to select frequencies near the center frequency, and j is an imaginary unit, which represents the imaginary part in the transfer function and is used to describe the influence of the filter on the signal phase.

[0103] Furthermore, the step S4 specifically includes the following sub-steps:

[0104] S401. Receive the output of the adaptive frequency tracking module and convert the frequency data into the format required for generating the control signal;

[0105] S402. According to the predicted EMI frequency, design and generate corresponding control signals, specifically, use an algorithm to convert frequency information into a voltage or current signal to drive the filter adjustment module;

[0106] S403. Optimize and amplify the generated control signal to drive the adaptive filter adjustment module;

[0107] S405. Transmit the optimized and amplified control signal to the adaptive filter adjustment module.

[0108] Furthermore, the step S5 specifically includes the following sub-steps:

[0109] S501. Detect electromagnetic interference in the environment and analyze its characteristics, wherein the analysis parameters include frequency and amplitude;

[0110] S502. Generate an opposite electromagnetic field signal according to the detected EMI characteristics;

[0111] S503. Receive the output of the neutralization signal generator unit and convert it into an actual electromagnetic field to generate electromagnetic waves opposite to EMI to neutralize the interference.

[0112] The above is only a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art shall not deviate from the spirit and scope of the present invention, and shall be within the scope of protection of the claims attached to the present invention.

Claims

1. A frequency adaptive impulse noise filter system, characterized in that: include: The quantum state change detection module is used to generate the entangled state of quantum bit pairs for detecting electromagnetic changes, measure the changes in the quantum bit state, and identify the frequency components of EMI; Adaptive frequency tracking module, which uses Kalman filter to combine historical and real-time data to estimate the dynamic changes of EMI frequency and track the changes of EMI frequency in real time; An adaptive filter adjustment module is used to dynamically adjust the filter parameters to match the current EMI frequency based on the prediction information provided by the adaptive frequency tracking module; A quantum control signal generation module, used to convert the predicted EMI frequency into a control signal, and drive the adaptive filter adjustment module according to the control signal; The electromagnetic field neutralization module is used to generate an electromagnetic field opposite to the detected EMI to neutralize the electromagnetic interference.

2. A frequency adaptive impulse noise filter system as claimed in claim 1, characterized in that: The adaptive frequency tracking module specifically includes: A data acquisition unit, used to collect data on changes in the state of quantum bits; A frequency analysis unit is used to perform Fourier transform on the collected data, convert the time domain signal into the frequency domain through Fourier transform, and identify the interference frequency; A Kalman filter implementation unit, used for processing the output of the frequency analysis unit through a Kalman filter algorithm and performing real-time estimation of the EMI frequency; The prediction and trend analysis unit is used to predict the changing trend of EMI frequency based on historical data and real-time estimated values ​​of EMI frequency.

3. A frequency adaptive impulse noise filter system as claimed in claim 1, characterized in that: The adaptive filter adjustment module specifically includes: A frequency response analysis unit is used to analyze the frequency response of the current filter, compare it with the output of the adaptive frequency tracking module, and adjust the parameters; A parameter adjustment decision unit is used to make a decision on the adjustment direction and amplitude of the filter parameters according to the result of the frequency response analysis unit; The tunable element control unit is used to receive instructions from the parameter adjustment decision unit and control the tunable element to adjust the center frequency and bandwidth of the filter in real time.

4. A frequency adaptive impulse noise filter system as claimed in claim 3, characterized in that: The adaptive filter adjustment module also includes a closed-loop feedback calibration unit, which is used to monitor the actual effect of the filter adjustment through a closed-loop feedback mechanism and perform calibration optimization.

5. A frequency adaptive impulse noise filter system as claimed in claim 3, characterized in that: In the frequency response analysis unit, the parameter adjustment process is to dynamically adjust the filter parameters through the filter transfer function according to the predicted EMI frequency, which is specifically expressed as follows: Wherein, H(f) is the transfer function of the filter, which is used to represent the gain of the filter for the signal of frequency f, ω0 represents the center angular frequency of the filter, in radians per second, ω represents the angular frequency of the input signal, in radians per second, Q is the quality factor, which represents the selectivity of the filter, that is, the ability of the filter to select frequencies near the center frequency, and j is an imaginary unit, which represents the imaginary part in the transfer function and is used to describe the influence of the filter on the signal phase.

6. A frequency adaptive pulse noise filter adaptive adjustment method, the method is implemented based on the frequency adaptive pulse noise filter system according to any one of claims 1 to 5, characterized in that: The following steps are involved: S1. Generate an entangled state of a qubit pair for detecting electromagnetic changes, measure the change in the qubit state, and identify the frequency component of EMI; S2. Use Kalman filter to combine historical and real-time data to estimate the dynamic changes of EMI frequency and track the changes of EMI frequency in real time; S3. Dynamically adjust the filter parameters to match the current EMI frequency based on the prediction information provided by the adaptive frequency tracking module; S4. Convert the predicted EMI frequency into a control signal, and drive the adaptive filter to adjust according to the control signal; S5. Generate an electromagnetic field opposite to the detected EMI to neutralize the electromagnetic interference.

7. A frequency adaptive impulse noise filter adaptive adjustment method as claimed in claim 6, characterized in that: The step S2 specifically includes the following sub-steps: S201. Collecting quantum bit state change data; S202. Perform Fourier transform on the collected data, convert the time domain signal into the frequency domain through Fourier transform, and identify the interference frequency; S203. Process the output of the frequency analysis unit through the Kalman filter algorithm and estimate the EMI frequency in real time; S204. Predict the change trend of the EMI frequency based on historical data and the real-time estimated value of the EMI frequency.

8. A frequency adaptive impulse noise filter adaptive adjustment method as claimed in claim 6, characterized in that: The step S3 specifically includes the following sub-steps: S301. Analyze the frequency response of the current filter and compare it with the output of the adaptive frequency tracking module to adjust the parameters; S302. Based on the results of the frequency response analysis, make decisions on the adjustment direction and amplitude of the filter parameters; S303. Receive instructions from the parameter adjustment decision unit, and control the tunable element to adjust the center frequency and bandwidth of the filter in real time.

9. A frequency adaptive impulse noise filter adaptive adjustment method as claimed in claim 7, characterized in that: After step S303, the method further includes step S304: monitoring the actual effect of the filter after adjustment through a closed-loop feedback mechanism, and performing calibration optimization.

10. The frequency adaptive impulse noise filter adaptive adjustment method according to claim 7, characterized in that: In step S301, the parameter adjustment process is to dynamically adjust the filter parameters through the filter transfer function according to the predicted EMI frequency, which is specifically expressed as follows: Wherein, H(f) is the transfer function of the filter, which is used to represent the gain of the filter for the signal of frequency f, ω0 represents the center angular frequency of the filter, in radians per second, ω represents the angular frequency of the input signal, in radians per second, Q is the quality factor, which represents the selectivity of the filter, that is, the ability of the filter to select frequencies near the center frequency, and j is an imaginary unit, which represents the imaginary part in the transfer function and is used to describe the influence of the filter on the signal phase.

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