43 results about "Spectral leakage" patented technology

The invention discloses a new energy broadband test analysis management and control method and system, and relates to the technical field of new energy detection and intelligent management and control, and the method comprises the following steps: obtaining a multi-window splicing frequency spectrum of a load switching edge, superposing phase lock consistency verification in a splicing frequency spectrum result, generating a frequency spectrum leakage suspicion chart, and carrying out the boundary constraint for energy track extraction; under the constraint of a spectrum leakage suspicion chart, an energy center track, a group delay curve and a phase derivative sequence are extracted, and a cross-frequency migration fingerprint is constructed and is used as a basic evidence for misjudgment traceability. By means of spectrum suspicion identification, feature fusion modeling, misjudgment traceability, label correction, energy reverse intervention and the like, accurate identification and closed-loop regulation and control of false operation caused by spectrum leakage are achieved, high identification accuracy, low misjudgment rate, high anti-interference performance and quick response capacity are achieved, and the operation stability and safety of a new energy field station are remarkably improved.

The invention discloses an anisotropic noise generation method based on local tensor integral field feature modulation, and is applied to the technical field of computer texture generation. The method comprises the following steps: step 1, constructing a global tensor field of spatial anisotropy intensity and direction; step 2, calculating local tensor integral features in a support domain based on the support domain of a Gabor noise kernel function, the local tensor integral features including principal direction features and anisotropic ratio features; step 3, calculating a curvature penalty factor based on the deviation between the local tensor integral feature and the center tensor of the seed point; step 4, based on the local tensor integral features, performing weighted correction on the frequency domain center frequency and Gaussian envelope parameters of the Gabor kernel function; and step 5, generating a final noise texture based on the corrected kernel function. The Gabor kernel function parameter is subjected to weighted correction through the local tensor integral feature and the curvature penalty factor, modulation of the kernel function direction under the high-curvature tensor field is achieved, spectrum leakage, texture fracture and artifacts caused by inconsistent direction changes in the kernel function can be reduced, and the robustness of the kernel function is improved. Therefore, the topological continuity and the simulation fidelity of the anisotropic noise texture at the complex structure are improved.

The invention provides an anti-noise interference frequency parameter estimation method for high-precision optical coherence ranging, which comprises the following steps: acquiring a spectral interference signal of an optical low-coherence interference system and a reference light spectral signal output only by a reference arm, and converting the spectral interference signal into interference signals with wave number space arranged at equal intervals, carrying out spectral density amplitude normalization to obtain a standard interference signal so as to eliminate interference of light source spectrum fluctuation and non-uniform sampling on frequency estimation; hanning window modulation is applied to a standard interference signal, spectrum leakage is suppressed, spectrum analysis is performed on the modulated signal, a peak value and an adjacent secondary peak value of a spectrum main lobe are extracted, a frequency correction amount is calculated based on a peak value and secondary peak value amplitude ratio relation derived by a Hanning window spectrum mode function, and an accurate frequency of the interference signal is obtained; and calculating the displacement of the object to be measured according to the product of the accurate frequency and the spectral resolution of the optical low-coherence interference system in combination with the refractive index of the light in the measurement medium.

The invention discloses a generative adversarial network image enhancement method combined with frequency domain information, relates to the technical field of computer vision, and solves the problems of spectrum leakage, ringing artifacts, splicing strips and structural dislocation easily caused by the existing frequency domain image enhancement method. The specific scheme is as follows: receiving a degraded image and extracting multi-scale features and boundary section features; the method comprises the following steps of: performing overlapping partitioning and periodic continuation expansion on the basis of features, performing spectral analysis on an expansion block to generate a parameterized window function and performing windowing, then obtaining a preliminary reconstructed image through complex field correction and overlapping perception mixed inverse transformation, and finally performing optimization reconstruction under a generative adversarial framework through a multi-scale wavelet decomposition and sub-band fusion decoder to obtain a reconstructed image. According to the method, the consistency of space geometric precision and texture details can be kept while artifacts and seams are inhibited, and the applicability and stability of image enhancement in a complex scene are improved.

The invention discloses a modal modeling method for a tendon-driven continuum robot. The method comprises the following steps: carrying out differential modeling on a configuration under a SE (3) Lie group-se (3) Lie algebra framework; the strain field is subjected to spectrum parameterization and is decomposed into active / passive orthogonal subspaces, and an inner product adopts energy weighted Hilbert measurement containing material and section parameters. The active mode is constructed by a linear continuous Jacobian of a tendon path; legendre polynomial expansion is adopted under the collinear layout, and complex Fourier harmonic expansion is adopted under the non-collinear layout; the passive mode is selected according to a spectrum slot position mutual exclusion principle so as to ensure that the passive mode is orthogonal to the active mode in energy and suppress spectrum leakage. Lie group integration and spectral integration are adopted for numerical value realization; newton-Rafson iteration is used in the quasi-static state, and generalized-alpha time integration or Newmark-beta integration is used in the dynamics. The method has high precision and robustness under nonlinear large deformation and multi-tendon coupling conditions, and is suitable for scenes such as software operation, minimally invasive intervention and precise detection.

The application provides a baseband radio frequency signal data feedback processing method based on vector modulation, which first receives a baseband signal data set transmitted by a target radio frequency link in a preset frequency band, which contains multiple signal frame original modulation parameters and corresponding radio frequency feedback signal waveforms, then calculates feedback error indicators composed of phase offset, amplitude distortion and spectral leakage factor according to the radio frequency feedback signal waveforms, quantizes the modulation error, analyzes the feedback signal waveforms in the time-frequency domain, extracts error feature vectors, inputs the pre-trained model for cross-frame correlation learning, generates a dynamic adjustment parameter sequence containing time sequence dependence, and finally constructs a closed-loop feedback control link based on the dynamic adjustment parameter sequence and the original modulation parameters, so as to realize accurate processing and optimized control of the baseband radio frequency signal and effectively improve the signal transmission performance.

The invention discloses a self-adaptive overlapped framing and variable window phase measurement method, device and system based on signal state perception, and belongs to the technical field of digital signal processing and phase measurement. Aiming at the technical problems that a fixed overlapping ratio and a single window function are adopted in an existing phase measurement method, resolution ratios of a time domain and a frequency domain cannot be considered under a time-varying signal, and frequency spectrum leakage and phase jump are easily introduced, the invention provides a joint self-adaptive preprocessing method. The method comprises the following steps: firstly, framing collected signals, and judging whether the signal state is a steady state or an unsteady state according to smoothness detection of absolute value sums of adjacent sampling points; according to the determined signal state, adaptively configuring an overlapping rate between adjacent data frames and window function type parameters, and then, before fast Fourier transform is carried out, introducing a window function coherent gain compensation mechanism to eliminate an amplitude reference error caused by window type switching; and finally calculating the phase difference based on the corrected spectrum result. According to the method, the overlapping framing and window function parameters are adaptively adjusted according to the signal state, the phase measurement continuity is ensured, the phase measurement precision and stability under the multi-frequency signal are improved, and the method has good real-time performance and engineering application value.

The embodiment of the present application discloses a spectrum analysis method, device and signal processing device, and the embodiment of the present application introduces a convolutional neural network to process discrete real part signals and discrete imaginary part signals in a frequency domain on the basis of an existing cycle graph spectrum analysis method, in the convolutional neural network, a convolution operation is performed by using frequency domain correlation characteristics of a window function used in a time domain, so that the problem of frequency domain distortion such as spectrum leakage, fence loss and the like caused by time domain processing of the window function in the frequency domain can be eliminated to a certain extent, and meanwhile, the accuracy of spectrum analysis can be effectively improved by combining the trained convolutional neural network.

The invention discloses a method for quickly estimating the reflection intensity of a defect of a buffer layer of a long-distance high-voltage cable. The method is mainly suitable for quickly and accurately estimating the reflection intensity of an ablation defect of the buffer layer of the long-distance high-voltage cable. The method comprises the following specific steps: (1) respectively testing the head end and the tail end of a defective cable to obtain head end reflection coefficients of the two ends; (2) obtaining frequency spectrum amplitude and pseudo frequency information at the corrected defect; (3) solving to obtain a defect position and a signal propagation attenuation constant; and (4) solving to obtain the reflection intensity of the defect of the buffer layer of the high-voltage cable at any position. The method is simple and rapid to operate and high in calculation accuracy, eliminates the influence of spectrum leakage, the fringe effect and the defect position on the calculation of the reflection intensity to a certain extent, can rapidly and accurately estimate the reflection intensity of the ablation defect of the buffer layer of the high-voltage cable at any position, and improves the calculation accuracy. The method has important reference value for timely mastering the severity of the defects of the buffer layer of the high-voltage cable and determining the priority level of defect processing.

The invention belongs to a signal direction finding method, and provides a signal direction finding method based on a space-time modulation metasurface and a related device in order to solve the technical problems that in the prior art, a traditional direction finding system has frequency spectrum leakage and poor direction finding precision, and related research for achieving direction-of-arrival estimation by modulating transmission amplitude lacks. When the space-time modulation metasurface receives a signal transmitted by a signal source, square waves of modulation array elements in the sub-arrays are estimated through a space-time modulation model, the space-time modulation model represents each sub-array signal in combination with a modulation frequency and a channel amplitude phase of each sub-array, and each sub-array signal is obtained; and estimating the square wave of the modulation array element in the sub-array through the relative phase difference of the + 1 harmonic and the + 2 harmonic of the represented sub-array signal. Then, according to square waves of modulation array elements in the sub-arrays, sub-array signals are recovered, and spatial frequency spectrum estimation is carried out on the sub-array signals to obtain the direction of arrival. And a non-uniform period modulation scheme is adopted to improve the estimation precision of the direction of arrival.

The present application relates to the technical field of signal processing, in particular to a kind of ECG signal noise suppression method and system based on singular spectrum analysis mean strategy, method includes: obtaining ECG noise signal sequence, ECG noise signal sequence is converted to frequency domain and obtains ECG signal spectrum;Frequency response matrix is constructed based on ECG noise signal spectrum, target function is established based on frequency response matrix with the orientation of inhibiting spectral leakage, the target vector is obtained by solving target function, the optimal window is determined according to target vector;Multiple noise suppression signals are generated based on ECG noise signal sequence and optimal window, noise suppression ECG signal is generated based on multiple noise suppression signals;The present application can suppress noise low-frequency component, to improve noise suppression effect.

The invention discloses a subspace joint parameter estimation algorithm for constructing an analytic signal based on Hilbert transform in high-precision multi-surface phase-shift interference, belongs to the technical field of high-precision optical interference measurement, and aims to solve the problems of inaccurate frequency estimation caused by spectrum leakage and a fence effect in a traditional algorithm. And the problem that a modern spectrum estimation algorithm cannot directly process real-value light intensity signals is solved. The method comprises the following steps: firstly, performing Hilbert transform on a real-value light intensity sequence to construct an analysis signal; then, a Hankel matrix is constructed based on the analysis signal, and subspace decomposition is carried out; further, taking the obtained high-precision frequency as prior information, and performing joint correction on the amplitude and the phase by using a double-section phase difference correction method; and finally, reconstructing the surface topography according to the corrected phase. According to the invention, the limitation of spectrum leakage and the like is overcome, the joint fine positioning of frequency, amplitude and phase is realized, and the precision, robustness and measurement repeatability of interference parameter demodulation are obviously improved.

The application discloses a kind of long-distance high-voltage cable buffer layer defect reflection intensity fast estimation method, this method is mainly suitable for the quick and accurate estimation of long-distance high-voltage cable buffer layer ablation defect reflection intensity.The specific steps of the method are as follows: (1) test at the defect cable first end and the end, obtain the first end reflection coefficient of two ends;(2) obtain the frequency spectrum amplitude and pseudo frequency information after correction at the defect;(3) solve to obtain the defect position and signal propagation attenuation constant;(4) solve to obtain the reflection intensity of high-voltage cable buffer layer defect at any position.The method is simple, fast, and the calculation accuracy is high, to a certain extent, eliminates the influence of spectrum leakage, aperture effect and defect position on the calculation of reflection intensity, can quickly and accurately estimate the reflection intensity of high-voltage cable buffer layer ablation defect at any position, has important reference value for timely grasping the severity of high-voltage cable buffer layer defect and determining the priority of defect treatment.

This invention relates to the field of exosome quantitative analysis technology, and discloses a multi-parameter joint quantitative analysis method and apparatus for exosomes based on the fluorescence intensity of encoded microspheres. The method includes: performing three-dimensional spatial attitude inversion to obtain a three-dimensional attitude characterization vector and constructing a feature point diffusion function; performing spatial deconvolution processing using the feature point diffusion function, and combining it with a visibility weight calculated from the longitudinal depth deviation for brightness gain compensation to obtain intrinsic feature intensity; constructing a channel intermodulation matrix to perform signal decoupling operations, obtaining decoupling intensity and mapping it to quantified abundance. This invention solves the problems of projection distortion, defocus blurring, and spectral leakage caused by random attitude, eliminates steric hindrance effects and system nonlinear interference, significantly improves the accuracy and repeatability of exosome detection, and achieves accurate analysis of high-fidelity biological quantitative information.

The application discloses a Ku-band satellite chain downlink signal interference suppression method, system, device and medium, and relates to the technical field of wireless communication signal processing. First, an OFDM signal from a satellite chain system is received, the OFDM signal is segmented, and fast Fourier transform is performed on the segmented signal to convert the segmented signal into a frequency domain to obtain a frequency domain signal. Then, an FCME algorithm is used to preliminarily locate a narrow-band interference frequency of the frequency domain signal to obtain an interference range. Further, a frequency offset value is calculated by using an interference frequency determined by DTFT, and then, spectrum shifting is performed on the frequency domain signal according to the frequency offset value, and interference alignment is completed through the spectrum shifting, so that interference suppression of the Ku-band satellite chain downlink signal is realized while spectrum leakage is avoided.

The application discloses an FID signal frequency estimation method and system based on improved interpolation DFT, and relates to the technical field of signal processing.The application adds a maximum sidelobe attenuation window to an input signal, derives an initial frequency estimation value under the condition of considering negative spectrum components, and significantly reduces the interference of negative spectrum leakage on frequency estimation on the basis of the initial frequency estimation value; on the basis, the application is no longer limited to discrete integer frequency points, but uses a discrete time Fourier transform (DTFT) to perform spectrum interpolation, thereby effectively alleviating the inherent fence effect of a fast Fourier transform (FFT), and making the frequency estimation no longer limited to the discrete interval of spectrum lines. A high-precision frequency estimation model further constructed can maintain consistent estimation performance in a full frequency band, and overcomes the defects of the existing IpDFT method that the precision fluctuates due to frequency changes. Therefore, higher estimation precision, smaller negative spectrum residual influence, and stronger robustness in a full frequency band can be realized in a complex electromagnetic environment.

The invention discloses a resistive leakage current detection protection method of an intelligent circuit breaker, and belongs to the technical field of electric leakage detection. The method comprises the following steps: synchronous sampling; shaping a window function; performing high-resolution spectrum analysis; estimating a Kalman state; generating a fault evolution index; inverse time delay decision making; and tripping execution. According to the method, a dynamic fault evolution index is taken as a core, online joint estimation of the resistive leakage current amplitude and the change rate of the resistive leakage current amplitude is realized in a circuit breaker for the first time through high-resolution spectral analysis, Kalman state estimation and a multi-dimensional nonlinear inverse time limit curved surface, and protection delay is generated in a self-adaptive manner according to the online joint estimation. Meanwhile, milliampere-level sensitivity and working condition self-adaption reliability are met, and the problems of FFT spectrum leakage, fixed threshold misjudgment and non-self-adaption in time delay in the prior art are solved.

This invention discloses a fault identification method and system for wheel-rail conveyors based on deep learning. By introducing a dynamic harmonic sensing sinc convolutional layer based on physical priors, this invention can actively extract discrete harmonic components that match the characteristics of fault harmonics, effectively suppressing strong background noise. Secondly, by utilizing an offset field predictor and deformable convolution, it accurately models and corrects Doppler nonlinear frequency shift distortion caused by sensor movement. Furthermore, it employs dynamic pooling sampling to generate Doppler invariant feature maps and splits time and frequency token sequences for cross-attention weighting, enabling it to focus on transient impact signals as short as tens of milliseconds, avoiding spectral leakage and global average dilution effects caused by long-window STFTs. Finally, this invention achieves high-precision identification of three core faults: wheel flange wear, bearing failure, and fastener loosening, thus exhibiting strong engineering adaptability and generalization ability.

The invention relates to the technical field of image data processing, in particular to a garment fabric defect detection method and system based on image recognition. The method comprises the following steps: acquiring a grayscale image of the surface of a garment fabric, and dividing the grayscale image into local sub-blocks by adopting a sliding window; for each sub-block, constructing a texture structure tensor, and calculating a texture principal angle and a gradient intensity feature; calculating frequency domain energy divergence potential energy in combination with the global reference angle of the standard fabric image; based on a multi-notch model, an adaptive filtering attenuation weight matrix is constructed, and the filtering radius is dynamically adjusted along with divergent potential energy; performing weight matrix filtering and inverse transformation on the sub-block spectrogram to obtain a reconstructed image; and carrying out binary threshold segmentation and morphological processing on the reconstructed image, and identifying and positioning defects. According to the method, the energy diffusion degree can be accurately evaluated, spectrum leakage artifacts are inhibited, tiny flaw signals are reserved, the defect recognition accuracy is improved, and reliable support is provided for garment fabric quality detection.

The application discloses a kind of amplitude and phase high-precision estimation method and device suitable for fast dynamic change signal, the method of the application includes the discrete signal sequence of continuous signal sampling, constructs Hankel matrix and decomposes left singular matrix U, diagonal matrix D, right singular matrix V;The estimated value of the number of frequency components p is estimated by D, combined with extracting the subspace of right singular matrix V and using least square method to obtain diagonal matrix Q;The damping coefficient of frequency component is calculated by Q and constructs system matrix A;The dynamic phasor coefficient vector S is calculated by A and discrete signal sequence using least square method;The amplitude and phase of continuous signal are calculated by S and damping coefficient.The application aims at solving the problem that the main lobe overlap of dense harmonic / interharmonic with small frequency interval in power system causes spectral leakage interference, extremely serious even can submerge part of main spectrum line, and then lead to the accuracy of spectral leakage affecting the amplitude and phase estimation of dynamic change signal.

The application discloses a wide-frequency impedance spectrum cable defect positioning method and system based on improved Z transform, and the method comprises the following steps: according to an equivalent distributed parameter circuit of a cable with defects, input impedance of each section of the cable is regarded as load impedance of a previous section, and the input impedance is deduced from the end of the cable to the front section by section, and finally, input wide-frequency impedance spectrum of the first end of the cable with defects is obtained; the input wide-frequency impedance spectrum of the first end of the cable with defects is subjected to improved Z transform considering spectrum leakage suppression, the input wide-frequency impedance spectrum of the first end of the cable with defects is converted from the frequency domain to the time domain, and cable defects are positioned through wave peak positioning in the time domain. In the wide-frequency impedance spectrum analysis, the traditional Z transform method is subjected to spectrum leakage suppression processing, and the accuracy of cable defect positioning can be significantly improved.

To provide a method for digital demodulation of all even harmonics of a magnetic modulator based on full phase analysis.SOLUTION: According to the digital demodulation method for all even-order harmonics of a magnetic modulator based on full-phase analysis, when the magnetic modulator is calibrated, standard voltage time sequence data output by the magnetic modulator when a direct current calibration current of a set value flows through the magnetic modulator is obtained, an output voltage sequence of full-phase Fourier analysis is established and pre-processed according to the standard voltage time sequence data, and the pre-processed output voltage sequence of full-phase Fourier analysis is comprehensively analyzed to obtain standard even-order harmonic signals and current conversion coefficients of each order. The present invention uses the full-phase Fourier analysis technology to perform comprehensive pre-processing and comprehensive analysis on the output voltage signal of the air modulator, which greatly reduces the problems of spectrum leakage and phase disturbance, so that the data sampled at different time points are fully utilized, and the signal processing is more accurate.SELECTED DRAWING: Figure 1

This invention discloses a broadband transmission response measurement method for underwater acoustic transducers based on instantaneous frequency tracking. The method uses a linear frequency modulated (LFM) signal to excite the transducer under test (DUT), simultaneously acquiring the voltage and current signals at the transducer's input, as well as the sound pressure level (SPL) signal received by a standard hydrophone. The time-frequency spectrum is obtained through short-time Fourier transform. A peak search combined with parabolic interpolation instantaneous frequency tracking strategy is employed to accurately extract the instantaneous frequency and corresponding voltage, current, and SPL amplitudes at each moment to calculate the instantaneous transmission voltage and current responses. After outlier removal, smoothing, and logarithmic frequency space interpolation, a continuous and smooth response curve is obtained. This invention effectively overcomes the spectral leakage problem of non-stationary LFM signals, achieving simultaneous measurement of the transmission voltage and current responses. It offers advantages such as high measurement accuracy, complete information, high efficiency, and standardized results, and is suitable for broadband response testing of underwater acoustic transducers.

The invention discloses a channel estimation method and device, equipment, a medium and a product, and relates to the field of communication technologies and integrated circuits, and the method comprises the steps: obtaining a channel frequency domain initial value; applying a window function to the channel frequency domain initial value, performing frequency domain filtering to obtain a filtered channel frequency domain initial value, and converting the filtered channel frequency domain initial value to obtain a channel time domain initial value; cutting off the channel time domain initial value based on the cyclic prefix length, performing zero setting and complementing on points except the cyclic prefix length to obtain a cut-off channel time domain initial value, and converting to obtain a channel frequency domain response estimation value; according to the method, the window function is used for filtering in the frequency domain, the edge component of the frequency domain signal can be attenuated, truncation mutation during subsequent inverse discrete Fourier transform is reduced, the frequency spectrum leakage phenomenon is reduced, the channel time domain initial value is truncated based on the cyclic prefix length, and the frequency spectrum leakage rate is improved. A plurality of taps of the previous cyclic prefix length can be reserved through the time domain truncation operation, and noise suppression is effectively achieved.

A method for digitally demodulating all even-order harmonics of a magnetic modulator based on full phase analysis is provided. [Solution] A digital demodulation method for all even-order harmonics of a magnetic modulator based on full-phase analysis involves calibrating a magnetic modulator by obtaining standard voltage time series data output by the magnetic modulator when a set DC calibration current is passed through the magnetic modulator, establishing and preprocessing an output voltage sequence through full-phase Fourier analysis based on the standard voltage time series data, and comprehensively analyzing the preprocessed output voltage sequence through full-phase Fourier analysis to obtain standard even-order harmonic signals and current conversion coefficients for each order. By using full-phase Fourier analysis technology, the present invention performs comprehensive preprocessing and comprehensive analysis of the output voltage signal of the magnetic modulator, significantly reducing the problems of spectral leakage and phase disturbance, making full use of data sampled at different times and making signal processing more accurate.

The application particularly relates to a power signal effective value calculation method and system based on a phase-locked loop and a sliding window. The method comprises the following steps: S01, a discrete sampling of a continuous target electric signal is carried out by an analog-to-digital converter based on a preset fixed sampling frequency; S02, a phase-locked loop module receives the discrete sampling data, carries out phase tracking and frequency estimation, and detects and outputs the running frequency of the target electric signal in real time; S03, a dynamic window length n is calculated based on the fixed sampling frequency and the running frequency of the target electric signal; S04, the first 2n-1 discrete sampling data stored in a cache unit are called, the dynamic window length n is taken as a reference, and point-by-point sliding calculation is carried out with a step of 1 to obtain n intermediate root mean square values; and S05, arithmetic average processing is carried out on the n intermediate root mean square values to obtain the effective value of the target electric power signal. The method can solve the problems of spectrum leakage and excessively large calculation error caused by non-synchronous sampling, and improve the calculation precision of the effective value of the electric signal in a non-synchronous sampling scene.

This invention relates to the field of power system parameter monitoring technology and discloses a high-precision analysis method for electrical parameters based on a lightweight DSP algorithm, comprising the following steps: sampling and data buffering, lightweight DSP core processing, electrical parameter output, and code-level optimization. This invention suppresses spectral leakage through integer-cycle sampling combined with window functions, achieving harmonic measurement accuracy of ±0.5%. After Kalman filtering, data fluctuation is reduced by 80%, and steady-state accuracy is improved to within 0.1%, enabling high-precision measurement. Simultaneously, downsampling and integer operations reduce computational load, and code-level optimization keeps CPU utilization ≤15%, allowing it to run on low-cost MCUs such as the STM32F407.

The invention discloses a new energy weak power grid dynamic harmonic separation method and device, and the method comprises the steps: tracking a fundamental frequency in real time through a phase-locked loop, and dynamically calculating a synchronous integral window length to suppress spectrum leakage; a phase angle synchronous updating algorithm is adopted to ensure that the harmonic phase reference is accurate; inputting the harmonic amplitude sequence into a Kalman filter of which the process noise variance can be adaptively adjusted for filtering; and characteristic harmonic waves are processed according to priorities through an FPGA multi-channel parallel architecture. The device comprises a sampling preprocessing module, a PLL (Phase Locked Loop) module, an FPGA (Field Programmable Gate Array) core processing module and a data interaction module which correspond to the device. According to the method, the problem of insufficient harmonic separation precision caused by frequency fluctuation and strong noise in a new energy weak power grid in a traditional method is solved, and high-precision and high-real-time harmonic separation is realized.

The invention belongs to the technical field of seismic data processing, and particularly relates to a high-precision seismic data time-frequency spectrum generation method based on a sidelobe suppression method, and the method comprises the following steps: 1, calculating an analysis signal of a seismic channel for seismic data; 2, solving the instantaneous frequency of the seismic data; 3, solving a stabilized seismic dominant frequency of the seismic data; 4, constructing a discrete matrix related to the Kaiser window; 5, multiplying the discrete matrix by the seismic trace to obtain a time-frequency spectrum; and step 6, displaying and analyzing the seismic data time-frequency spectrum. Aiming at the problem that a Gaussian window applied by a conventional W transformation method cannot flexibly adjust a balance relation between a main lobe width and sidelobe attenuation, the suppression of sidelobe intensity in a W transformation process is enhanced by introducing a Kaize time window, and the frequency spectrum leakage crosstalk between different signal components in a time spectrum is suppressed, so that the suppression of the sidelobe intensity in the W transformation process is enhanced. And the resolution of the time-frequency spectrum frequency domain is improved.