51 results about "Cross-spectrum" patented technology

The invention discloses a sound source localization method based on multi-frequency separation and Newton optimization deconvolution, relates to the technical field of array acoustic signal processing, and is used for solving the problem that weak sound sources and multiple sound sources are difficult to identify. According to the method, dominant frequency is extracted through multichannel frequency domain analysis, a cross-spectrum matrix is constructed in combination with a near-field propagation model and a guide vector, delay summation beam forming is executed to obtain sound source preliminary distribution, then the distribution is regarded as a convolution result, a maximum likelihood model is introduced, and a two-stage deconvolution strategy of coarse estimation and Newton method fine optimization is adopted to obtain a high-resolution sound source. According to the multi-sound-source positioning method, subgrid-level analysis of sound source positions and amplitudes is achieved, finally, all frequency results are fused, continuous sound source images are smoothly output through a two-dimensional Gaussian kernel, the resolution and real-time performance of multi-sound-source positioning are remarkably improved, and the multi-sound-source positioning method is suitable for high-precision acoustic imaging in a complex sound field.

The invention discloses a photovoltaic panel vibration monitoring method and system based on AI and heterogeneous convergence network communication, and the method comprises the steps: enabling each sensor terminal to transmit a local relative timestamp generated by a free operation timer to a gateway base station along with an uplink data message after completing the vibration data collection and processing in the same collection period; the gateway base station calculates the relative transmission delay inequality of any node pair according to each message receiving moment and the local relative timestamp, constructs a frequency domain phase correction factor at each discrete frequency point according to the relative transmission delay inequality, and corrects the uncorrected cross-spectral density to obtain the corrected cross-spectral density; and a coherence function value is further calculated by combining the self-spectral density of each node, and a vibration abnormal area is positioned according to the spatial distribution of the coherence function value on the photovoltaic array topology. The method can improve the accuracy of multi-node vibration joint analysis and the reliability of abnormal positioning, and is suitable for online monitoring of a photovoltaic power station.

Embodiments of the present application disclose a river bed load transport characteristic determination method and device, electronic equipment and a computer readable medium, relating to the field of engineering technology. The method performs fast Fourier transform on the sound pressure signals of the microphone array to obtain a sound pressure matrix in the frequency domain; based on the sound pressure matrix, cross-spectrum operation is performed to obtain a cross-spectrum matrix; based on each scanning grid point j on the surface of the monitoring sensor plate as an imaginary sound source point, a sound propagation model is selected according to the aerodynamics theory to determine the sound signal monitored by any microphone; each grid point is scanned, the auto-spectrum of the simulated sound signal is calculated, and the sound source holographic image of the bed load shock wave is determined; the sound source intensity is simulated, the bed load spatial position is obtained, and the bed load particle size component information is obtained through the calibration function relationship. That is, in the present application, the bed load spatial position and the bed load particle size component information are obtained, this method can accurately determine the transport characteristics of the bed load, and becomes an important support for quantifying the disaster prevention and reduction work of mountainous rivers.

The application discloses a kind of arbitrary pulsating wind field active control wind tunnel physical simulation method and system, comprising: establishing generalized pulsating wind field spectrum model, it has 6 controllable pulsating wind spectrum in the energy distribution model parameter of frequency domain;Based on generalized pulsating wind field spectrum model, inter-spectrum matrix is calculated using coherence function;Based on harmonic superposition method, inter-spectrum matrix is converted into pulsating wind field space-time information;Pulsating wind field space-time information is introduced into the control program of active control wind tunnel, through real-time monitoring and iterative adjustment model parameter, until the target wind field generated reaches expectation.The application can simulate wind field with arbitrary frequency energy distribution by generalized pulsating wind field spectrum model with 6 model parameters, combined with iterative closed-loop control, significantly improve the simulation accuracy and adaptability of complex wind field such as mountain valley wind, typhoon.

The invention discloses a multi-channel signal receiving calibration method and device based on a cross-spectrum method, and relates to the field of signal processing, and the method comprises the following steps: S1, configuring system parameters, and generating a test signal; s2, performing frequency domain transformation on the test signal; s3, performing cross spectrum analysis on the test signal; s4, performing time delay extraction on the test signal; s5, performing compensation calibration; and S6, experimental verification. According to the multi-channel signal receiving calibration method and device based on the cross-spectrum method, by optimizing a cross-spectrum calculation process, introducing high-resolution time delay estimation and improving a phase compensation mechanism, the problems existing in the prior art are effectively solved, time delay and amplitude inconsistency between channels are accurately estimated and corrected, and the accuracy of calibration is improved. The problems that the calibration precision is limited due to high calculation complexity and poor real-time performance of a traditional method, the time delay estimation performance is reduced in a low signal-to-noise ratio environment, and the requirements of a modern multi-channel system for high synchronism and low delay cannot be met are solved.

Interference removal device (100), comprising: a Fourier transform unit (3) to divide an input signal into frames which are divided into segments by a fixed time, wherein the input signal contains a component other than a target signal, and to transform the input signal into a frequency spectrum to generate a plurality of pairs of frequency spectra by using a delay amount, wherein the pairs of frequency spectra have a fixed time difference; a cross-spectra unit (4) to generate a plurality of cross-spectra or a plurality of coherences from the plurality of pairs of frequency spectra with the fixed time difference; and a disturbance removal unit (5) to average the multitude of cross-spectra or the multitude of coherences in order to extract a power spectrum of the target signal.

This invention relates to a method and system for locating coaxial counter-rotating sound sources in rotorcraft, belonging to the technical field of sound source identification methods. It includes: processing the sound pressure signal of the moving sound source using continuous wavelet transform to obtain time-frequency domain variation results; performing Doppler effect correction based on experimental conditions; estimating the spatial location and relative intensity of the noise source using a cross-spectral matrix and weight vector; and performing phase-locked analysis of the rotor noise source intensity using a phase-locked averaging method. This invention differs from traditional time-domain delay superposition algorithms and frequency-domain cross-correlation spectrum methods. It can image unsteady sound sources using time-frequency domain characteristics, solving the acoustic imaging problem of counter-rotating propeller noise and possessing potential applications in the rotorcraft industry.

The invention discloses a weak sound source sound pressure level calibration method based on an improved DAS beam, relates to the technical field of sound source positioning, and is used for solving the problem of repeated weak sound source positioning. According to the method, a distance matrix is constructed based on array geometric parameters, and a cross spectrum matrix and a steering vector are respectively calculated for a plurality of target frequencies in combination with a near-field propagation model to obtain a multi-frequency acoustic image; and performing normalization and relative threshold side lobe suppression on each frequency sound image result, superposing and highlighting a real sound source area on a scanning grid, suppressing a side lobe irrelevant to a position, and utilizing a sound pressure level calibration model obtained by training reference data to convert a sound image output quantity into a real sound pressure level, so as to realize spatial positioning and quantitative sound pressure evaluation of multiple sound sources. The weak sound source can still be clearly distinguished under the background that the sound pressure level difference of the strong and weak sound sources is large and the noise is complex, and the sound source positioning precision and the engineering detection reliability are improved.

The invention discloses a rotating sound source recognition and positioning method based on a deep convolutional attention neural network, and belongs to the field of rotating sound source recognition, and the method comprises the steps: firstly carrying out the motion compensation and modal expansion of a sound pressure cross-spectrum matrix through a modal decomposition rotating beam forming algorithm, and generating a sound source distribution diagram in a rotating scene; then the sound source distribution map is input into a deep convolution attention neural network model, the model adopts an encoder-decoder structure, a channel and a space attention mechanism are fused, key sound source features are dynamically focused, noise interference is suppressed, and high-precision reconstruction of the sound source distribution map is achieved; and finally, carrying out local maximum value detection on a prediction map output by the network, and extracting a sound source space position. According to the method, the Doppler effect and phase distortion problems in rotating sound source positioning are effectively overcome, and the positioning precision, the anti-noise performance and the calculation efficiency in a complex rotating field are remarkably improved.

The invention relates to a high dynamic range sound source imaging method based on a double attention mechanism, and the method comprises the steps: receiving a space sound field signal through a microphone array, and processing the space sound field signal into a frequency domain signal; performing cross-spectrum matrix characteristic filtering processing on the frequency domain signal to obtain a complex frequency domain signal vector; performing adaptive enhancement on a real part and an imaginary part of the complex frequency domain signal vector by using a double attention mechanism; fusing the enhanced real part with the enhanced imaginary part to obtain an enhanced signal vector; and performing beam forming calculation by using the enhanced signal vector to generate an acoustic image. According to the invention, the real part attention module and the imaginary part attention module are introduced in parallel at the front end of beam imaging, and the amplitude and phase characteristics of the acoustic signal are subjected to adaptive weighted enhancement, so that the spatial information in the array signal is fully mined, the dynamic range of acoustic imaging and the robustness in a noise environment are significantly improved, and the method is suitable for wide application. And a better solution is provided for precise fault diagnosis and acoustic monitoring.

The invention provides a rotating sound source beam forming method based on improved wavelet transform, which comprises the following steps of: firstly, executing Morse wavelet transform on data received by each microphone, and converting a time domain signal into a time-frequency domain signal; then, parameters related to the Doppler effect are calculated, and a Doppler effect correction Green function is introduced; then, calculating a weight vector and a cross-spectrum matrix formed by an array beam; and finally, grid division is performed on a plane where a target signal is located, and beam forming is performed on each grid point by using the time-frequency array signal model on each wavelet domain so that sound imaging of a target sound source can be realized. Compared with a traditional beam forming method based on Fourier transform, the beam forming method based on improved wavelet transform has the advantage that the real-time imaging quality and background noise suppression are remarkably improved.

The application discloses a sparse Bayesian learning vector acoustic direction finding method based on orthogonal acoustic intensity flow, and belongs to the technical field of array signal processing. First, an orthogonal acoustic intensity flow data model is constructed, an acoustic intensity flow is obtained by cross spectrum of sound pressure and vibration velocity channels, and acoustic energy flow density is obtained by acoustic pressure autospectrum. Then, a joint probability density distribution function is established by means of a sparse Bayesian learning model. Finally, according to maximum log-Bayes evidence estimation of signal power, spectral peak search is performed on the signal power estimation value, and the direction estimation of the target is realized. The method uses acoustic intensity and acoustic intensity flow as input, has the effect of suppressing isotropic noise and reduces the calculation amount. When the hyperparameters are updated for the first time, a deconvolution algorithm is introduced to avoid the judgment error of the number of signal sources and the direction of arrival caused by the proximity of two targets. Moreover, the method has good direction estimation accuracy and direction resolution capability, and can maintain good performance under the condition of low signal-to-noise ratio.

The invention discloses a pulsating pressure wave number-frequency spectrum two-dimensional surface array data processing method, which is based on concepts such as a cross-spectrum matrix and a position difference vector, obtains a corresponding discrete area by defining a plurality of key sets related to a two-dimensional surface array and applying a Worronoi diagram method, and finally obtains the pulsating pressure wave number-frequency spectrum two-dimensional surface array data. And a two-dimensional wave number-frequency spectrum is obtained through a multiplication method. On one hand, the method can adapt to all types of two-dimensional surface array forms, the problem of applicability limitation of a traditional method is thoroughly solved, meanwhile, an analysis result directly corresponds to a TBL pulse pressure wave number-frequency spectrum, and effective measurement of real physical quantities is achieved; and on the other hand, by introducing a parallel computing architecture, the data computing time consumption can be remarkably shortened, the processing efficiency is greatly improved, the universality and high efficiency of two-dimensional pulsating pressure wave number-frequency spectrum data processing are considered, and a better support is provided for engineering landing of related technologies.

The invention discloses an ocean surface wave monitoring system based on a synthetic aperture radar, which relates to the technical field of ocean surface wave monitoring, and comprises the following steps: carrying out azimuth split view on single-view complex data, and generating a split view cross spectrum and an azimuth self spectrum; determining a frequency domain selection area according to the cross spectrum energy, and calculating azimuth antisymmetric phase skewness in the area; determining azimuth cut-off by the azimuth auto-spectrum, constructing an odd phase compensation operator, and performing phase correction on the split-view cross-spectrum; performing direction projection on the correction spectrum to obtain a dominant propagation direction, and determining a peak wave number according to a direction correlation weight; and the peak wavelength and the peak period are obtained by using linear dispersion relation conversion. According to the invention, the monitoring reliability and consistency under complex sea conditions can be improved.

This invention relates to the field of engineering machinery safety technology, specifically disclosing a load stability prediction system for telescopic boom forklifts based on the force exerted by the boom. The system collects motion sensing data and stress wave sensing data at the boom hinge; calculates a cross-spectral coherence function based on the motion data to generate a hinge coherence disorder index; performs time-frequency transformation on the stress wave data and automatically identifies energy impact patches, extracting their peak energy, center frequency, and duration; and generates a transient collision intensity spectrum index based on sensitive frequency band mapping and aggregation; constructs a time-series comprehensive feature vector from the two indices, inputs it into a pre-trained multi-layer gated recurrent unit structure for nonlinear dynamic system identification, and outputs a fused stability assessment state quantity; maps this state quantity to a virtual potential energy surface for multi-step forward extrapolation, calculates the dynamic stability margin value, and issues an early warning when the margin is lower than an adaptive threshold; this invention achieves early and accurate prediction of nonlinear jump instability.

The invention relates to the technical field of electronic test and measurement, and discloses a cross-spectrum correlation-based semiconductor low-frequency noise measurement system, which comprises an electromagnetic shielding unit, and an adaptive bias unit, a calibration switching unit and a dual-channel signal amplification unit which are arranged in the electromagnetic shielding unit, the external power supply unit, the data acquisition unit and the main control processing unit are arranged. The adaptive bias unit is integrated with a floating drive shielding circuit to eliminate a cable parasitic capacitance effect; and the calibration switching unit is internally provided with a standard noise source to realize full-link in-situ gain calibration. The system adopts a physically isolated dual-channel amplification architecture, signals to be detected are injected into two channels at the same time, and rigid synchronous sampling is carried out through a data acquisition unit. And the main control processing unit performs cross-power spectral density calculation and statistical averaging on the two digital sequences. According to the method, the background noise in the amplifier can be effectively suppressed, the sensitivity limit of single-channel measurement is broken through, and the ultralow-frequency weak noise of the semiconductor device is accurately extracted.

Enabling generation of comfort noise in an encoder using an estimated coherence parameter in a network using a discontinuous transmission, DTX, includes receiving time domain audio input comprising audio input signals; and processing the input signals on a frame-by-frame basis by: encoding active content of each input signal at a first bit rate until an inactive period is detected in the input signals; switching the encoding from the active encoding to inactive encoding to encode background noise at a second bit rate during the inactive period; estimating coherence parameters during the inactive period based on a low-pass filtering or averaging of cross-spectra including reinitializing a low pass filter state of the cross-spectra based on a coherence parameter from a previous inactive period; encoding the coherence parameters estimated; and initiating transmitting of the encoded active content, background noise, and coherence parameters towards a decoder.

The invention relates to a reduced scale model wind turbine inlet wind field observation and reconstruction method based on a laser radar, and the method is characterized in that the method comprises the following steps: S1, carrying out the discretization of a reduced scale model wind turbine scanning round surface, forming finite calculation points, and calculating the average wind speed spectrum of an impeller; s2, obtaining an average wind speed self-spectrum of the impeller; s3, calculating a cross spectrum between the impeller average wind speed spectrum and the impeller average wind speed self-spectrum; s4, calculating coherence between the average wind speed observed by the laser radar and the actual average wind speed of the impeller, and calculating an optimal scanning cone angle and a focusing position by adopting an optimization algorithm; s5, acquiring a vertical wind profile of the wind field; and S6, calculating a reconstructed wind field. According to the method, the laser remote sensing technology is adopted, and the physical acting force generated after the laser and the aerosol act can be ignored, so that the interference and wake flow effect on a flow field due to the existence of a relatively large physical structure in a traditional wind measurement method do not exist.

The application discloses a dynamic equalization and howling suppression intelligent tuning method of a digital audio processor and belongs to the technical field of computers. The method is characterized in that a distributed high-fidelity microphone array is laid out, a wideband sweep excitation signal is output, and sound pressure data are synchronously collected; potential howling modal regions are extracted through spatial Fourier transform and cross-spectral density analysis, real resonance modes are confirmed through modal matching combined with finite element simulation; the critical state of howling is determined by monitoring the growth of modal energy and the spatial deviation, and finally, local equalization filtering is activated according to the howling position. The application realizes accurate positioning and local suppression of howling, maximally retains the original sound quality, and improves the stability and adaptive ability of an audio system in a complex acoustic space.

The invention provides a three-dimensional dereverberation beam forming method and system based on a cross-correlation matrix, and relates to the technical field of sound source recognition, and the method comprises the steps: collecting sound pressure data through a spherical microphone array; performing fast Fourier transform on the sound pressure data to obtain corresponding frequency domain data; calculating a cross-spectrum matrix corresponding to the spherical array according to the frequency domain data; eliminating reflected sound components contained in the cross-spectrum matrix to obtain a filtered cross-spectrum matrix; and drawing a sound source identification cloud picture based on the filtered cross spectrum matrix. According to the three-dimensional dereverberation beam forming method based on the cross-correlation matrix, the technical problem of insufficient sound source recognition precision of a spherical array in a complex sound field environment in the related technology is solved.

The embodiment of the invention provides an array gain calculation method and device for a deep-sea near-sea-surface vertical array buoy, and relates to the technical field of array signal processing. The method is applied to a vertical array buoy and comprises the following steps: acquiring related parameters of the vertical array buoy and noise source parameters; calculating a first contribution value of near-field noise to noise cross-spectrum density and a second contribution value of far-field noise to noise cross-spectrum density based on the vertical array buoy related parameters and the noise source parameters; determining a noise cross-spectral density matrix based on the first contribution value and the second contribution value; determining the noise directivity gain of the vertical array buoy based on the beam scanning pitch angle and the noise source parameter; determining the signal directivity gain of the vertical array buoy based on the beam scanning pitch angle, the received signal and the signal cross-spectral density matrix; based on the noise directivity gain and the signal directivity gain, the array directivity gain of the vertical array buoy is determined, and then the array gain of the vertical array buoy is determined. According to the invention, the accuracy of array gain calculation can be improved.

The application discloses a kind of modular hydraulic system test system and method, it is related to hydraulic test technical field, comprising the following steps: S1, using nanosecond level synchronous time scale system to the outlet pulsating pressure signal of high-pressure plunger pump and low-pressure vane pump is collected, generates phase residual diagram, and preliminary determination is carried out to implicit resonance risk by frequency drift and amplitude gradient calculation;S2, on the basis of synchronously collected baseline, to pulsating pressure sequence is carried out to mutual spectrum coherence degree calculation and phase difference time series analysis, identifies frequency misplacement anchor point, and generates pump source pulsating interference fingerprint, determines the time window of implicit resonance.The application is through nanosecond level synchronous collection, phase conjugate inversion and misfrequency traction strategy, realizes to the real-time identification, dynamic intervention and closed-loop control of implicit resonance in hydraulic system, effectively avoids the energy coupling caused by frequency misplacement, improves system operation stability and security, prolongs equipment service life.

The application discloses a fiber seismic wave velocity monitoring method and system using vehicle vibration signals, and a medium, relates to the technical fields of fiber sensing and vehicle-road cooperation, and comprises the following steps: step one, detecting vehicle signals recorded by each fiber channel; step two, sequentially calculating the cross spectrum, coherence and weight after S transforming the vehicle signals, and calculating the delay by weighting; step three, repeating step two to obtain a delay sequence set corresponding to all vehicle signals; and step four, taking the sign inversion of the travel time difference obtained by bidirectional propagation of the vehicle signals between two fiber channels as prior information, screening the delay sequence set, calculating the delay change of each vehicle signal between the two fiber channels, and thus obtaining a velocity change sequence; the monitoring method realizes high-resolution time-varying monitoring of the wave velocity of underground media.

The application relates to the technical field of vehicles, in particular to a noise identification method and device of a vehicle, a vehicle and a storage medium, wherein the method comprises the following steps: acquiring a vibration acceleration signal and a vehicle interior noise signal when the vehicle drives on a preset impact road and performing time domain preprocessing; constructing a cross spectrum matrix based on the vibration acceleration signal after the time domain preprocessing and performing target principal component analysis to obtain a principal component signal of the cross spectrum matrix; then obtaining a transfer function matrix from each wheel center excitation point to an interior response point by using a hammering method test; calculating and identifying road impact loads at each wheel center of the vehicle based on the principal component signal and the transfer function matrix by using an inverse matrix method; and calculating contribution amount quantization results of each noise transmission path to the vehicle interior noise signal according to the road impact loads and the transfer function matrix. Therefore, the problems of noise identification result distortion and instability caused by the ill-conditioned transfer function matrix and the coupling of multiple reference point signals in the related art are solved.

The invention provides a shallow sea sound source depth discrimination method and system suitable for a scene with incomplete sediment parameters. The method comprises the following steps: determining environment information and parameters of a shallow sea sound field to be subjected to depth discrimination; the parameters comprise the sound velocity, the density and the attenuation coefficient of a seabed sediment layer; the seabed sediment layer is one or more of a sedimentary layer, a mudstone layer and a half space; constructing a shallow sea sound field model based on the environmental information and parameters of the shallow sea sound field to be subjected to depth discrimination; the method comprises the following steps: acquiring sound pressure data from a shallow sea sound field model by adopting a binary vertical array, and performing conjugate cross-spectrum calculation on the acquired sound pressure data of the shallow sea sound field model to serve as copy field data; the method comprises the following steps: acquiring an actual sound pressure signal by adopting a dual-element vertical array based on actual measurement data of an existing experiment, and calculating to obtain signal field data by adopting a conjugate cross-spectrum method; and calculating a correlation coefficient between the copy field data and the signal field data set, and determining the depth of the sound source according to the depth corresponding to the maximum value of the correlation coefficient.

The embodiment of the invention discloses a tinnitus subtype recognition system, and the system comprises a preprocessing module which is used for preprocessing tinnitus electroencephalogram data to be recognized, and obtaining preprocessed electroencephalogram data; the segmentation module is used for segmenting the preprocessed electroencephalogram data to obtain N pieces of segmented electroencephalogram data; the traceability module is used for performing brain voxel-level traceability on the segmented electroencephalogram data to obtain a voxel cross-spectrum matrix of each frequency band of the brain; the summarizing module is used for spatially summarizing the target voxel cross-spectrum matrix under each frequency band to obtain a brain interval cross-spectrum matrix; the construction module is used for constructing a target function connection matrix under each frequency band according to the brain interval cross spectrum matrix under each frequency band; the fusion module is used for fusing the target function connection matrixes under different frequency bands to obtain a feature matrix; and the clustering module is used for performing spectral clustering on the feature matrix to obtain tinnitus subtypes corresponding to the tinnitus electroencephalogram data. The technical problem that existing tinnitus grading is general and high in subjectivity is solved.

The application discloses a PICC tip positioning method and system based on R-wave reference and multi-dimensional morphological characteristics, relates to the technical field of intravascular device positioning, and provides the following scheme, which comprises the following steps: collecting a target object multi-lead ECG original waveform, detecting R peaks and recording time points and amplitude, performing time-frequency analysis on the ECG original waveform with each R peak as a phase zero point, calculating multi-beat phase consistency metrics in combination with a preset P-wave physiological phase range, determining the phase main lobe position of each beat and taking the P-wave candidate segment, and calculating the cross-spectrum characteristics and envelope energy between selected lead pairs based on the P-wave candidate segment. The application solves the problem of insufficient P-wave segment extraction stability in multi-beat signals caused by weak P-waves and noise interference by performing multi-beat time-frequency analysis with R peaks as phase zero points and calculating phase consistency metrics in combination with a preset P-wave physiological phase range.

The invention relates to a self-adaptive line spectrum detection method based on sound pressure and acceleration combined processing. The self-adaptive line spectrum detection method comprises the steps that a co-vibration type vector hydrophone collects a sound pressure signal and an acceleration signal in a sound field; calculating a cross spectrum of the sound pressure and the acceleration signal; target signal energy is obtained by extracting an imaginary part of a cross spectrum by utilizing a phase relation between sound pressure and an acceleration signal under a far-field condition, so that low-frequency noise accumulation caused when a vibration velocity signal is generated by acceleration signal integration is avoided; carrying out adaptive Gaussian smoothing filtering on the extracted cross-spectrum imaginary part to remove a trend term; and finally, automatically extracting the line spectrum signal. According to the method, the problem of low-frequency noise enhancement caused by acceleration-to-vibration velocity integral operation in a traditional method is avoided, multiple times of band-pass filtering processing are not needed, the complexity of a signal processing system is reduced, the method has better signal sensing ability than a traditional sound pressure and particle vibration velocity combined processing method in a low-frequency band, and the method is suitable for large-scale popularization and application. Accurate detection of underwater sound target line spectrum signals can be realized.

The invention discloses a safety tamper-proof control method for an electric energy meter, and aims to solve the problems that hidden wiring tampering is difficult to identify and legal impact load is easy to report mistakenly. According to the method, through phase-locked loop phase alignment and half-cycle pairing, fundamental wave phasor mirror image residual and odd-even consistency index, amplitude-phase joint harmonic symmetry entropy and cross spectrum coherence degree weighting, and cooperation with an anomaly detection Transform model of half-cycle pairing block sparse attention and persistent judgment, virtual full waves are reconstructed and metering and control reporting are compensated when establishment is established; the technical effects of high-sensitivity low-false-alarm identification, metering correction, rate freezing and evidence data retention of half-bypass and half-wave rectification tampering are achieved.