2033 results about "Harmonic" patented technology

A method for diagnosing rotor rub-impact in a rotating machinery based on vibration signal deconstruction and frequency modulation characteristic anti-noise enhancement, including: converting, based on two-stage integration transformation and high-pass filtering, vibratory acceleration signals from a rotating machinery device into vibratory displacement signals; performing targeted extraction on a rotating frequency component therein based on an improved variational mode decomposition method; calculating and estimating instantaneous fluctuation characteristics of a fundamental frequency of the extracted rotating frequency component using a quadrature-derivative-based normalized Hilbert transform to obtain an instantaneous frequency; inputting a calculated instantaneous frequency sequence into an optimum stochastic resonance system for anti-noise enhancement of intrawave frequency modulation characteristics; and processing FFT on an instantaneous frequency of intrawave frequency modulation characteristics after anti-noise enhancement, and diagnosing and identifying a rotor rub-impact fault of the rotating machinery based on a distribution characteristic of harmonic amplitudes related to a rotor rotating frequency.

The invention relates to the technical field of transformer harmonic monitoring, in particular to a harmonic detection and early warning system for an intelligent transformer, which obtains voltage and current signals of the transformer in real time, performs frequency domain decomposition by using Fourier transform, extracts multi-dimensional harmonic characteristics such as amplitude, phase, frequency and the like, and performs harmonic detection and early warning on the intelligent transformer. And inputting into a deep learning model to train and generate a dynamic harmonic characteristic model. On the basis, a harmonic wave anomaly classification module analyzes harmonic wave signals in real time, carries out type judgment and position association on abnormal harmonic waves, and generates a report containing anomaly types and positions. Through a dynamic early warning module, a power grid load coefficient is calculated based on power grid load state parameters collected in real time, and a harmonic detection threshold is dynamically adjusted in combination with an initially set amplitude and frequency threshold. The application of the dynamic threshold enhances the adaptability of the system to the load state change, and significantly improves the sensitivity and accuracy of harmonic detection and early warning.

The invention provides a wind generating set fault monitoring method and system based on voiceprint recognition, and the method comprises the steps: collecting gear box voiceprint signal data in real time, recording signal fluctuation caused by gear surface wear, and obtaining an original signal data set containing a frequency spectrum high-frequency component enhancement feature; a time-frequency analysis method is adopted for the original signal data set, non-linear interference of vibration signals is recognized, multi-scale decomposition is carried out, initial wear frequency spectrum narrow-band characteristics and medium-term harmonic components are separated out, and a frequency spectrum component set is obtained; extracting characteristic parameters related to modulation depth abnormal fluctuation from the frequency spectrum component set, identifying a gear pair meshing frequency change rule, and determining a distribution mode of a tooth surface contact noise proportion; and if the feature matching result shows that the deviation between the spectrum high-frequency component diffusion distortion feature and the reference feature library exceeds a threshold value, adding the tooth surface fatigue crack noise feature into the feature library to obtain a target feature library.

The invention discloses a multi-dimensional time sequence photovoltaic grid-connected harmonic current prediction control method, and particularly relates to the technical field of power system control. Grid-connected original multi-dimensional electrical signals are collected and decomposed into multi-dimensional frequency signals through Fourier transform, the characteristic components of an independent harmonic source are separated through the blind source separation and non-negative matrix factorization technology, and the frequency and amplitude characteristics of the characteristic components are extracted; then, a multi-dimensional time sequence prediction model is constructed through a recurrent neural network, dynamic behaviors of multiple harmonic sources are predicted at the same time, and frequency domain data are reconstructed and frequency aliasing errors are corrected in combination with high-frequency compensation and multi-scale analysis; and finally, inputting a prediction result into a photovoltaic inverter control system, dynamically generating a compensation current opposite to a target harmonic wave, realizing effective offset of the harmonic wave, accurately processing the multi-source harmonic wave problem in a complex power grid environment, and greatly improving the harmonic wave suppression capability, the electric energy quality and the system operation stability of a photovoltaic grid-connected system.

The invention relates to a control method of a digital ultrasonic flaw detector calibrating device. The control method comprises the following steps: acquiring shape data and material parameters of a to-be-detected material, calling a matched standard test block, calculating adaptive ultrasonic frequency and flaw detector parameters, creating and solving a multi-objective optimization model, and planning a detection path of the to-be-detected material based on an optimal solution; emitting ultrasonic waves with matched frequency to implant the quantum dot mark array to carry out fluorescence-ultrasonic dual-mode signal correlation calibration; scanning according to a planned detection path, establishing a time-varying channel model to predict a current time delay variation, extracting a fundamental frequency and a harmonic component of a probe excitation pulse by adopting an autocorrelation algorithm to serve as a reference, constructing a state vector of a filter based on the predicted current time delay variation, and performing phase correction on a received signal to obtain a phase correction signal; and analyzing the defect of the to-be-detected material based on the corrected receiving signal. By integrating material parameter dynamic modeling, multi-modal signal collaborative calibration and adaptive path optimization, the detection precision and efficiency under complex working conditions are improved.

The invention discloses an efficient and high-precision compensation system and method of an intelligent mutual inductor, and particularly relates to the technical field of mutual inductors. The method comprises the following steps: acquiring magnetic flux density and magnetic field intensity data of a mutual inductor under different current and voltage change rates, generating a hysteresis loop diagram, extracting hysteresis loop width, residual magnetism and coercive force characteristics, and establishing a hysteresis effect error model; the harmonic distortion is identified in combination with spectrum analysis, the harmonic distortion degree in a high-frequency environment is predicted, the hysteresis of the hysteresis effect and the harmonic distortion are comprehensively analyzed, and the accuracy of a compensation algorithm for processing nonlinear errors is evaluated; and finally, the compensation signals are divided into high-accuracy signals and low-accuracy signals, the high-accuracy signals are directly output, and the low-accuracy signals are output after error correction, so that the problem that a conventional compensation algorithm cannot correct non-linear errors is effectively solved, and the measurement precision of the mutual inductor in an extreme environment and the operation stability of a system are improved.

The invention discloses a multivariable fusion power load prediction method and system, and relates to the technical field of load prediction, and the method comprises the following steps: obtaining first data, and synchronizing the first data into second data based on a physical constraint interpolation method; shielding the harmonic dominant frequency band based on the second data, and de-noising the load waveform by combining the real fluctuation of the filtering separation load; a load prediction model is constructed based on the denoised load waveform in combination with a harmonic distortion rate weighted double-flow network, prediction model parameters are corrected in real time, and a load prediction value is output; the real-time correction is a dynamic correction strategy based on wavelet transform. Through a dynamic selection interpolation method, the load data, the meteorological data and the new energy output data can be synchronized on a unified time scale, the synchronism and precision of different data sources can be ensured, high-quality input data is provided for a prediction model, and the reliability of a prediction result is improved.

The invention relates to the technical field of motor fault diagnosis, in particular to a motor fault diagnosis algorithm based on multi-sensor fusion, and the algorithm comprises the steps: injecting a step excitation signal into a motor, synchronously collecting the original response waveforms of vibration and current sensors, and calculating the inherent response delay. Establishing a mapping relation library of delay values and current sensor filtering parameters, calling the delay values in real time according to the filtering parameters, performing reverse time offset compensation on a current harmonic signal time sequence, performing time alignment on the two types of data, finally performing cross-domain coupling analysis on the aligned data, extracting vibration pulse peak frequency and current harmonic fluctuation quantity, and determining the vibration pulse peak frequency and the current harmonic fluctuation quantity. Early faults are judged by combining the bearing outer ring fault characteristic frequency band and the load rate dynamic threshold value, graded alarm is generated by tracking characteristics, the problem of fault false judgment and missed judgment caused by sensor data space-time dislocation is solved, and the early fault diagnosis accuracy of the motor is improved.

The invention provides a frequency converter dynamic fault diagnosis method and system based on a multi-brand load test platform. According to the method, multiple real-time operation parameter sets are acquired, the amplitude attenuation threshold and the frequency fluctuation interval of a voltage waveform fragment are dynamically adjusted according to a load mode configuration file, the dynamic voltage reference parameter corresponding to the current load mode is generated, and then the actual waveform and an expected current phase curve are compared frame by frame; the method comprises the following steps: firstly, calculating to obtain a phase offset, then constructing a multi-dimensional operation characteristic spectrum, then carrying out time sequence cross validation on a sudden change time node of a power factor jump trajectory and an abnormal waveform position in a harmonic distortion incidence matrix, outputting an abnormal mode code, and finally, matching a load adaptation grade constraint condition to generate a diagnosis report; according to the technical scheme provided by the invention, the fault diagnosis precision and the cross-brand system adaptation capability in a complex load scene are remarkably improved, and the problem of misjudgment of a single brand threshold rule in a multi-device scene is effectively solved.

The invention provides a multi-language cross-culture communication assisting method and system based on a large model. The method comprises the following steps: receiving a source language audio stream during a call, calling a multi-language sound frequency harmonic modulation feature library to extract fundamental frequency harmonic intensity distribution and tone turning features, and generating a cultural acoustic fingerprint vector; based on the vector, controlling a microphone array phase difference, directionally enhancing a fundamental frequency harmonic component of a speaker and suppressing noise, and outputting a high signal-to-noise ratio spectrogram; analyzing the pronunciation rhythm and tone turning characteristics of the spectrogram, capturing the pitch jump and duration of the syllable boundary, and generating an acoustic culture label; associating the spectrogram with a target semantic library, matching harmonic distribution and a cultural context rule based on a large model, and outputting a cultural interpretation prompt containing an ambiguity resolution suggestion; and generating a calibration result according to the acoustic tag and the semantic prompt, and overlapping the dynamic floating subtitles to the face area of the speaker in the video conference picture. According to the invention, cultural tone ambiguity in multi-language communication is eliminated.

According to the new energy grid-connected electric energy metering method and device, broadband harmonic characteristic information and inter-harmonic characteristic information are respectively obtained according to preprocessed power grid voltage and power grid current; after the broadband harmonic characteristic information and the inter-harmonic characteristic information are input into the influence analysis topology network, a first error compensation parameter is calculated by using an electric energy metering error output by the influence analysis topology network; based on a non-sinusoidal signal simulation model, combining the preprocessed power grid voltage and power grid current with the step wave signal to obtain a non-sinusoidal wave signal; performing error compensation calculation on the non-sine wave signal to obtain a second error compensation parameter; obtaining time-varying error data of the electric energy meter by using historical operation data of the electric energy meter; a target error compensation parameter is calculated based on the first error compensation parameter, the second error compensation parameter and the time-varying error data of the electric energy meter, the electric energy meter performs electric energy metering based on the target error compensation parameter, an electric energy metering result is obtained, and the accuracy of new energy grid-connected electric energy metering is improved.

The invention belongs to the technical field of intelligent health monitoring, and particularly relates to an FMCW radar-based night respiration and heartbeat monitoring signal processing method, which comprises the following steps of S1, acquiring a chest vibration displacement signal of a human body by using an FMCW radar, and completing the acquisition of a radar signal; according to the recovery separation method based on the two-parameter LMS filter, monitoring and target positioning of multiple life signals can be achieved by the FMCW radar under the condition of low signal-to-noise ratio, and compared with a band-pass filtering (BPF) method and a wavelet transform (WT) method, more accurate breathing and heartbeat signals can be obtained by the method based on the two-parameter LMS filter, and the method has the advantages of being simple in structure, convenient to operate and high in practicability. Particularly, when the breathing signal has multiple harmonic waves and the frequency changes, the method is more accurate compared with other methods, breathing and heartbeat signals can be rapidly converged by setting a proper step length, and small steady-state deviation is kept when the signals are received next time.

The invention belongs to the technical field of nondestructive testing, and particularly relates to a detection method for quantitatively evaluating fatigue damage in a pipeline through a nonlinear ultrasonic technology. 316 stainless steel and SA335GRP-11 ferrite steel samples are adopted, a welding seam area is formed through V-shaped groove welding, fatigue loading is conducted, and actual pipeline fatigue damage is simulated; for the samples with different fatigue cycles, nonlinear response signals of the samples are obtained; fourier transform is carried out on the obtained signal to obtain an energy spectrum of the signal, and energy changes of the signal on a fundamental frequency band and a second harmonic frequency band are analyzed; and calculating a nonlinear coefficient, and analyzing a change rule of the nonlinear coefficient along with fatigue cycles, so that the evolution process of fatigue damage in the pipeline is evaluated. According to the method, energy is used for replacing the amplitude value, on the basis of the formula principle, integration is used for replacing the amplitude value to improve the intensity of the characterization nonlinear ultrasonic signal, the early stage of damage and the later stage of crack initiation are detected, and reliable guarantee is provided for safe operation of an industrial pipeline system.

The invention relates to a rectification harmonic suppression control method for a double reverse star transformer. The method comprises the following steps: establishing a rectifier bridge arm phase characteristic parameter table in a control platform, and recording a theoretical conduction phase, winding attribution and waveform synchronization characteristics of a bridge arm; in the operation process of the rectification control unit, the output current of a transformer and the conduction state of a bridge arm are collected, and a rectification operation state data set is generated; and calculating bridge arm conduction phase deviation, and analyzing a corresponding harmonic component to obtain a mapping relation between a bridge arm state and harmonic distribution. And judging whether the current bridge arm configuration meets the phase coverage requirement of the target rectification pulse number or not according to the mapping result, and if not, selecting a standby bridge arm group with a preset phase difference and generating a switching instruction. And the rectification control unit responds to the instruction to lock the current bridge arm conduction path and release the target bridge arm group so as to realize bridge arm resource dynamic reconstruction and rectification performance optimization. Harmonic waves can be effectively suppressed, and the topology adaptability and the output quality of the rectification system are improved.

The invention discloses a method for predicting and suppressing harmonic waves generated by photovoltaic grid connection, which relates to the technical field of harmonic wave prediction, and comprises the following steps: detecting a three-phase current signal of a photovoltaic grid connection circuit by using an ip-iq detection method, and decomposing the three-phase current into an active component and a reactive component through Clarke conversion and Park conversion; according to the method, high-precision detection and separation of harmonic waves in the photovoltaic grid-connected system are realized by combining an ip-iq method with Clarke and Park transformation, dynamic modeling and harmonic signal prediction are performed by using the LSTM model, the defect of poor adaptability of a traditional method to nonlinear loads is overcome, and the prediction error is as low as 0.1%. Through combination of LSTM prediction and APF dynamic compensation, the compensation current opposite to the harmonic current is generated in real time, the harmonic suppression efficiency and the power grid stability are significantly improved, the electric energy quality is optimized, and the dynamic change of a complex load is adapted.

The invention provides a city hidden unmanned aerial vehicle identification method and system. The method comprises the following steps: acquiring geometric morphology and material dielectric constant data of an urban building group, and generating a building material reflection parameter set; secondly, based on reflection parameters, millimeter wave frequency band combinations adaptive to building attenuation characteristics are screened, millimeter wave signals are directionally transmitted, reflection components of metal parts and unmanned aerial vehicle composite materials are separated, and a three-dimensional millimeter wave imaging map fused with multipath interference suppression parameters is generated; collecting a radio frequency signal, compensating path loss by using scattering phase offset, extracting a harmonic component of a propeller motor and a frequency hopping residual component of a communication module, and generating a time-space synchronous radio frequency fingerprint coding sequence; through constructing a millimeter wave and radio frequency coupling model, cross validation is carried out on a reflection component and a harmonic component, and accurate identification of the hidden unmanned aerial vehicle in the urban building group shielding area is realized. According to the invention, the urban hidden unmanned aerial vehicle identification precision is improved.

The invention relates to the technical field of energy management, in particular to a distributed energy optimization management method and system, and the method comprises the steps: determining an optimal switching control strategy of a switching device through employing a Q-Learning particle swarm optimization algorithm; performing intermittent conduction and turn-off control on the switching device according to the optimal switching control strategy, obtaining a time domain action signal of the switching device, and extracting harmonic spectrum data in the conduction and turn-off processes of the switching device by using a short-time Fourier transform algorithm; obtaining total harmonic power according to the harmonic frequency spectrum data, and if the total harmonic power exceeds a harmonic power dynamic threshold value, extracting an overproof harmonic signal; and the standard-exceeding harmonic signals are converted into energy storage voltage and current matched with the energy storage device, and the energy storage voltage and current are stored in the energy storage device. According to the invention, through management analysis of the harmonic waves, precise identification and efficient energy storage of the harmonic waves generated by the nonlinear load are realized, so that optimal management of the distributed energy system is realized.

The invention discloses a loss tuning method of a power transformer, which is applied to a transformer body sleeved with a winding and comprises the following steps: applying scanning current excitation containing fundamental waves and harmonic waves to the winding, synchronously acquiring a body vibration signal and converting the body vibration signal into a frequency spectrum; extracting a formant from the frequency spectrum, matching the formant with a theoretical electromagnetic force wave and a structure inherent frequency library, and identifying a coupling formant to be optimized; aiming at each formant, installing a vibration exciter in a corresponding area, sending out an anti-phase periodic pulse force, and dynamically and finely adjusting a pulse force parameter by monitoring a vibration response in real time and taking equivalent mechanical impedance minimization as a target; when the optimal damping state is achieved, the vibration exciter output rod is locked, and static pre-tightening force is formed; and after all formants are adjusted and optimized in sequence and the prestress is locked, final pressing and fixing of the transformer body are completed in the state that the pretightening force is kept. According to the invention, the dynamic loss source of the individual transformer can be actively inhibited and cured before assembly and curing, the operation loss and noise are effectively reduced, and the structural stability is improved.

The invention discloses a micro-grid electric energy quality global optimization method, which comprises the steps of collecting real-time data, dividing the real-time data into a plurality of segments according to frequency, and calculating harmonic compensation capacity of each frequency band according to the real-time data; according to the harmonic compensation capacity obtained through calculation, priority distribution is carried out on the compensation sequence of the polluted nodes in the micro-grid; the virtual impedance and the injection damping resistance of the inverter are adjusted, and the harmonic current and the resonance phenomenon in the micro-grid are suppressed in different frequency bands; and according to the adjusted virtual impedance and damping resistance, updating a node admittance matrix, monitoring the compensation capacity of the inverter in real time, comparing real-time monitoring data with a threshold value, if the real-time monitoring data exceed the threshold value, correcting the inverter, otherwise, not changing. Through frequency-band-divided control, pertinence and effect of harmonic suppression are improved, frequency-band-divided suppression of micro-grid harmonic and high-frequency resonance is realized, residual capacity of an inverter and harmonic compensation requirements are dynamically matched, and safe and stable operation of a system is ensured.

The invention relates to the technical field of ground resistance detection, in particular to a single-core cable ground resistance detection method capable of resisting strong power frequency interference. High-frequency signals are injected in a non-contact mode through a coupling type capacitor clamp, background voltage and current signals are collected firstly, and injection frequency far away from power frequency and harmonic waves is selected through Fourier analysis; cancelling background noise by adopting a normalized least mean square adaptive filter to generate an enhanced signal; the signal is down-converted to a base band through digital quadrature demodulation, a Kalman filter estimates the amplitude and the phase in real time, and the state and noise parameters are periodically calibrated through a compressed sensing algorithm; and finally, loop impedance is calculated according to the voltage and current amplitudes and the phase difference to obtain grounding resistance. The method has the advantages of being non-contact, high in safety, strong in anti-interference capability, high in measurement precision and the like, and is suitable for monitoring the grounding state of the cable in a complex electromagnetic environment.

The invention discloses a main power grid short-time load prediction method using a hybrid active filter, and particularly relates to the technical field of load prediction. The method comprises the following steps: acquiring active control parameters and passive branch parameters of a hybrid active filter, combining a real-time load fluctuation signal of a main power grid, extracting harmonic suppression characteristics and phase distortion characteristics, and analyzing and generating a time scale compensation factor through a dynamic coupling effect; and constructing a phase correction model based on the transient harmonic residual component and the time scale compensation factor, and performing frequency domain and time domain combined reconstruction on the real-time load fluctuation signal to obtain a corrected load fluctuation characteristic sequence. A short-time load prediction model is calibrated through a collaborative mapping relation, a load power prediction value of a main power grid in a future preset time window is output, a secondary high-frequency interference signal generated by real load fluctuation and filter self-resonance is effectively distinguished, and the problem of coupling interference of harmonic residual components on the load prediction model in a power grid impedance sudden change scene is solved.

The invention relates to the technical field of composite material detection, in particular to a fiber-reinforced thermosetting thermoplastic composite structure interface quality detection method and system.The method comprises the steps that vibration excitation is applied to a target area of the surface of a to-be-detected sample, and the amplitude of the excitation is lower than the damage critical value of a weak bonding interface; a dynamic response signal perpendicular to the interface is collected in a vibration field non-diffusion area of the excitation point of the target area; performing frequency domain transformation on the dynamic response signal, and separating a fundamental frequency component and at least one high-order harmonic frequency component; according to the nonlinear enhancement effect of the high-order harmonic frequency component relative to the fundamental wave frequency component, whether the weak bonding defect exists in the target area or not is judged. According to the method, the technical bottleneck that the dynamic evolution process of the weak bonding defect of the composite material interface is difficult to capture in real time is effectively solved, sensitive response to the microdefect is realized through a nonlinear harmonic characteristic enhancement effect, and the recognition precision of traditional ultrasonic detection is improved.

The invention relates to a nonlinear ultrasonic guided wave phased array imaging method based on mixed array elements and time reversal. The method comprises the following steps: exciting a fundamental wave and receiving a second harmonic wave at piezoelectric array elements of the fundamental wave and the second harmonic wave of an ultrasonic guided wave by using a center frequency respectively; full-matrix data of ultrasonic guided wave signals in the detected workpiece are obtained in a one-transmitting and one-receiving mode; a fundamental wave signal is suppressed and a second harmonic signal is enhanced by adopting a pulse inversion mode; for the full-matrix data after pulse inversion, utilizing continuous wavelet transform filtering to extract a second harmonic signal; respectively calculating the distance from the discretized imaging area to the excitation array element and the distance from the discretized imaging area to the receiving array element; and for each discrete pixel point, according to an excitation signal of a distance forward propagation fundamental wave and a received second harmonic signal back propagation, a pixel value is calculated by using a time domain topology energy equation, and local acoustic nonlinear imaging of the plate-shaped structure is realized.

The invention belongs to the field of magnetic resonance measurement signal noise filtering, and particularly relates to a ground magnetic resonance signal sparse denoising method of a combined dictionary, which comprises the following steps: reconstructing a power frequency harmonic component of a magnetic resonance signal according to frequency bands, and eliminating power frequency harmonics from the magnetic resonance signal to obtain a power frequency-removed signal; constructing a track matrix Z by adopting a Gaussian random matrix, constructing a track matrix Y by adopting a power frequency-removed signal, taking first K columns of the track matrix Z and normalizing to obtain an initial dictionary D, and using the track matrix Y as an original sample for constructing a sparse coefficient matrix X; updating the initial dictionary D and the sparse coefficient matrix X through K-SVD dictionary learning, and reconstructing a track matrix by adopting the updated dictionary # imgabs0 # and the sparse coefficient matrix # imgabs1 # to obtain a track matrix W; and obtaining a pure magnetic resonance signal by taking the first row of the track matrix W, and realizing effective removal of MRS signal noise in a complex electromagnetic interference scene under the condition of single signal acquisition.

The invention discloses a multi-sideband chirp modulation DAS system and a working method thereof, and relates to the technical field of distributed sound wave sensing. The DAS system comprises a narrow linewidth laser, an optical fiber coupler, a phase modulator, an electro-optical modulator, an erbium-doped optical fiber amplifier, an optical fiber circulator, a dense wavelength division multiplexer, a photoelectric balance detector, a data acquisition card, an arbitrary waveform generator, a direct current source and the like. The phase modulator is used for modulating constant-amplitude multi-frequency continuous light, the frequency number of light waves is related to the harmonic number of a microwave modulation signal, the frequency interval is determined by the fundamental frequency of the microwave modulation signal, the continuous light frequency can be flexibly modulated by adjusting the microwave modulation signal, and the modulation bandwidth is large; detected beat frequency signals are compressed into single-frequency signals through pulses, phase information of the single-frequency signals is demodulated, vibration signals along the sensing optical fiber can be detected, the spatial resolution of the system depends on the chirp frequency sweeping range, and the spatial resolution is high.

The invention relates to the technical field of power systems, in particular to a UPQC harmonic compensation method and system based on repetitive control, and the method comprises the steps: obtaining a load current signal and a voltage signal of a power distribution network, and extracting a harmonic instruction current based on the load current signal; and inputting the harmonic instruction current into a feed-forward channel constructed based on an adaptive filter, and generating a feed-forward control quantity. The phase and frequency of the voltage signal of the power distribution network are tracked in real time through a digital phase-locked loop, the fundamental frequency of the power grid is accurately solved, and the power distribution network can be accurately controlled. The internal model period and the phase lead compensation amount of the frequency adaptive repetitive controller are dynamically calculated, and the internal model structure of the repetitive controller is always matched with the current power grid frequency by updating the two core parameters in real time, so that the compensation precision decline caused by frequency deviation is avoided; and high-precision suppression of the periodic harmonic waves can be realized in a normal fluctuation range of the fundamental wave frequency of the power grid.

The invention discloses a power supply reliability analysis method and system based on operation and maintenance characteristics of a power distribution network, and particularly relates to the technical field of power supply analysis of the power distribution network. Harmonic data, including harmonic current, harmonic voltage and frequency components, of each node in a power distribution network system are collected in real time; in combination with the topological structure of the power distribution network, the sparse linear equation set is solved through L1 norm optimization, and the main source of harmonic waves is identified; the contribution degree of each nonlinear load to the harmonic distortion of a power distribution network system is calculated, a list of key harmonic sources is screened out through Pareto analysis, a filter configuration optimization model is constructed based on the identified key harmonic sources, and the harmonic distortion level and the filter installation cost are used as constraint functions to optimize the filter configuration. The installation position and the parameter configuration of the filter serve as decision variables, an optimization algorithm is adopted for solving, and the recommended installation position and the parameter configuration of the filter are output; the harmonic suppression effects under different load conditions are evaluated, and the problem that the power supply reliability is reduced due to harmonic distortion is effectively solved.

The invention discloses a power quality rapid disturbance detection method based on improved K-S conversion. The method comprises the following steps: obtaining a discrete sampling sequence of power grid detection nodes; performing fast Fourier transform to obtain a signal frequency spectrum; iterative cyclic filtering processing is carried out on the signal frequency spectrum, and the maximum value of the filtered frequency spectrum is calculated to serve as a frequency feature point; carrying out improved K-S transformation on the signal to obtain a transformed matrix; extracting a fundamental frequency part from the transformed matrix to obtain a section of one-dimensional time signal representing a waveform of a fundamental wave in signal duration, calculating a maximum value, a minimum value and a sudden change time point to obtain time domain disturbance characteristics, and detecting disturbance amplitudes, starting time and ending time of voltage sag, voltage sag, voltage interruption and flicker; and determining the frequency, the amplitude and the duration of each frequency component according to the transformed matrix, and detecting frequency domain disturbance including harmonic waves and transient oscillation.

The invention relates to an electric power system broadband measurement method and system based on a wavelet packet and SVMD, and belongs to the technical field of electronic measurement. The method comprises the following steps: acquiring frequency information corresponding to a circuit signal of each measurement point in a circuit system; performing wavelet packet decomposition on the frequency information, and determining an optimal wavelet basis for broadband measurement of the power system; performing multilayer decomposition on the frequency information according to the optimal wavelet basis to obtain a plurality of wavelet frequency bands; performing component extraction on the wavelet frequency band to obtain a harmonic component corresponding to the wavelet frequency band; de-noising the harmonic components by using a wavelet coefficient correlation algorithm to obtain de-noised harmonics; decomposing the noise reduction harmonic wave according to an EMD algorithm to obtain a signal residual error meeting a preset stop condition; and calculating to obtain measurement and calculation data corresponding to each harmonic waveform according to the signal residual error. According to the technical scheme, the time-frequency characteristics of the signals can be captured more accurately, and the method has better performance on non-stationary signals and signals with complex frequency structures.

The invention relates to the technical field of frequency conversion, in particular to a radio frequency microwave signal modulation method and system, and the method comprises the following steps: detecting the ratio of the time domain peak interval to the frequency domain main sideband energy of a radio frequency signal, inputting the time domain peak interval and the frequency domain main sideband energy into a cross-correlation algorithm for synchronism analysis, extracting the periodic characteristics of a time domain peak sequence, and obtaining a frequency domain peak sequence; and generating an energy coupling factor based on a difference operation result of the frequency domain energy density gradient value and the time domain peak interval. According to the method, periodic characteristics are analyzed and extracted through the ratio of peak spacing to main sideband energy to generate an energy coupling factor, a main frequency point offset and an energy tilt vector are fused to generate a harmonic tendency parameter, an interference source path is positioned by combining a frequency trajectory vector, and disturbance levels are divided by clustering energy and harmonic parameters. And a conflict direction is pre-judged and stop band parameters are pre-loaded by grey prediction of a main sideband frequency difference value trend, and a closed-loop regulation and control system is constructed to improve the anti-drift capability and reduce the spectrum conflict risk.