335 results about "Fundamental frequency" patented technology

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.

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 multi-element microphone array sound source localization method based on multistage signal preprocessing and subspace spectrum optimization, and belongs to the technical field of acoustic detection. Aiming at the problems of poor noise immunity, weak multi-sound-source resolution capability and low calculation efficiency of the existing sound source positioning technology, a triple signal preprocessing and subspace collaborative optimization scheme is provided; firstly, incoherent noise is suppressed through phase coherent filtering, a signal is reconstructed through principal component analysis, and phase deviation is calibrated through fundamental frequency; then constructing a guiding matrix and decomposing a noise subspace, and extracting a coarse positioning result; and finally, high-precision angle optimization is realized based on a chaos initialization differential evolution algorithm, and the efficiency is improved by combining a dynamic search range and an early stop mechanism. According to the method, the anti-interference capability in a low signal-to-noise ratio environment is remarkably enhanced, the problems of missing detection and false detection during dense distribution of multiple sound sources are effectively solved, meanwhile, the positioning precision and the real-time performance are considered, and the method is suitable for acoustic fault detection of complex scenes such as power transmission line inspection.

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 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 composite insulator defect detection method and system based on a multi-source signal and VMD decomposition, and the method is characterized in that the method belongs to the technical field of power system and equipment monitoring, and comprises the steps: synchronously collecting an ultrasonic echo signal, a mechanical vibration signal and an infrared thermal image signal of a composite insulator, and carrying out the timestamp alignment; performing CEEMDAN denoising and VMD decomposition on the ultrasonic echo signal in sequence to extract time-frequency domain features, and generating an ultrasonic feature vector; performing frequency domain transformation on the mechanical vibration signal to extract fundamental frequency and harmonic characteristics, and generating a vibration characteristic vector; performing surface temperature abnormal feature extraction on the infrared thermal image signal to generate an infrared auxiliary feature vector; the ultrasonic feature vector, the vibration feature vector and the infrared auxiliary feature vector are spliced into a fusion feature vector, and after dynamic weight distribution, the fusion feature vector is input into a multi-layer perceptron model for defect classification; and analyzing and positioning the internal defect position of the composite insulator by combining the ultrasonic signal propagation path time delay and the vibration mode, and generating a three-dimensional visual report.

The invention provides an ultrasonic nonlinear static parameter monitoring method for creep damage of a high-temperature alloy component, and particularly relates to the technical field of material monitoring. The method comprises the following steps: S1, arranging an ultrasonic probe; s2, determining the emission frequency of the excitation end; s3, respectively calculating an incident angle and an emergent angle of the signal; s4, exciting fundamental frequency ultrasonic waves; s5, receiving the signal and uploading the collected signal to a cloud processing system; s6, carrying out fast Fourier transform and calculating a nonlinear parameter of a static component; s7, establishing a linear relation with creep time, and constructing a creep damage linear quantitative model; s8, calculating a static component nonlinear parameter of the healthy sample; and S9, completing quantitative analysis of the damage by using nonlinear parameters. The method solves the problems that a traditional nonlinear ultrasonic method depends on second harmonic nonlinear parameters, phase velocity matching conditions in the middle and later periods are seriously damaged, response shows a nonlinear trend, unique creep time cannot be determined according to the parameters, and then the unique damage state cannot be determined.

The invention provides a stay cable force recognition method based on frequency multiplication relation global optimization, and the method comprises the steps: recognizing a plurality of candidate frequencies through spectrum analysis based on stay cable vibration acceleration data collected in real time; the candidate frequency set is input into a fundamental frequency solving model, the sum of squares of frequency multiplication rounding deviation of each frequency and an approximate fundamental frequency is minimized through an optimization algorithm, and the approximate fundamental frequency is an optimization parameter for global search of the optimization algorithm; and determining a final fundamental frequency according to the solved approximate fundamental frequency, and outputting the cable force.

The invention relates to the technical field of earphone noise reduction, and discloses a bone conduction earphone intelligent noise reduction method and system based on multi-mode interactive fusion, and the method comprises the steps: collecting a multi-mode signal when a user uses a bone conduction earphone, carrying out the motion artifact elimination of the multi-mode signal, and obtaining a pure multi-mode signal; identifying a vocal cord vibration fundamental frequency and a formant of the pure multi-mode signal to perform noise fusion characterization processing on the bone conduction earphone to obtain a noise characterization matrix, and identifying a noise type of the bone conduction earphone by using the noise characterization matrix; analyzing a physiological fatigue index of the user, constructing noise reduction parameters of the bone conduction earphone based on the physiological fatigue index and the noise type, and constructing a noise reduction propagation link of the bone conduction earphone; and carrying out anti-howling adaptive filtering on the noise reduction propagation link by using the noise representation matrix to obtain a reverse sound wave, and carrying out noise reduction on the bone conduction earphone to obtain a noise reduction audio. According to the invention, the bone conduction earphone wearing experience of the user can be improved.

The invention relates to the technical field of cable force detection, in particular to a bridge inhaul cable fundamental frequency identification method, device and equipment, a storage medium and a product, vibration acceleration data of a bridge inhaul cable structure to be monitored in the duration time is converted into a power spectrum data set, a noise floor is calculated through the power spectrum data set, the noise estimation precision is improved, and the noise estimation accuracy is improved. Energy peak value screening is carried out on the power spectrum data, part of energy peak value data is screened out, a frequency-energy peak value array is obtained, energy evaluation and scoring are carried out on the frequency-energy peak value array and a predetermined candidate fundamental frequency through a preset fundamental frequency scoring model, and the energy evaluation and scoring precision of the candidate frequency is improved; finally, the actual fundamental frequency of the to-be-detected inhaul cable is determined through the score value of the candidate fundamental frequency, manual screening is not needed, the identification efficiency is improved, and meanwhile high-precision identification of the fundamental frequency of the inhaul cable is achieved.

The invention discloses a singing voice conversion method based on VITS. The method comprises the following steps of: 1, respectively extracting a bottleneck feature, a fundamental frequency, a singing style feature and a linear spectrogram from the singing of a source singer by utilizing a Whisper superficial layer encoder, an automatic singing transcription model AST and an AutoVC-based pitch-energy encoder, and taking the bottleneck feature, the fundamental frequency, the singing style feature and the linear spectrogram as the input of a VITS-based singing voice conversion model; reconstructing the singing voice by using a VITS-based singing voice conversion model in combination with the voiceprint characteristics of the singer to obtain converted singing voice of the target singer; and 2, performing pitch adjustment according to the pitch difference between the source singer and the target singer through a pitch shifter, and generating a target singing sound with the characteristics of the target singer by taking the bottleneck characteristics, the F0 and the singing style characteristics as the input of a voice conversion model. The method has the characteristics of multi-level refined acoustic feature decoupling, explicit singing style migration, high-fidelity waveform generation and dynamic adaptive pitch conversion.

The invention relates to the technical field of speech recognition, in particular to a Chinese learner-oriented tone evaluation and improvement method, which comprises the following steps of: extracting a fundamental frequency F0 curve and sound channel parameters of a speech signal, constructing a turbid and clear adaptive fusion model, and fusing to generate fundamental frequency related characteristics and fundamental frequency unrelated characteristics; constructing a tone error corpus, carrying out tone classification labeling, generating a multi-level tone feature set through a turbid and clear adaptive fusion model, aligning a voice signal with a reference voice time domain, and extracting and decoupling a tone shape feature vector and a tone domain feature vector; and based on the decoupled feature vectors, establishing a dual-channel evaluation path, hierarchically calculating the tone type distance and the tone domain distance of the tones, carrying out weighted fusion, generating a final evaluation score, and finally generating feedback information for the Chinese learner. According to the method, a complete method from feature decoupling to two-channel evaluation is constructed, the pronunciation problem of the learner is quantitatively diagnosed, and the pertinence and efficiency of Chinese tone learning are improved.

The invention discloses an intermediate frequency electro-therapeutic apparatus, which comprises a controller and a waveform synthesis circuit, and is characterized in that the waveform synthesis circuit comprises a first amplitude adjusting circuit, a second amplitude adjusting circuit and a synthesis adjusting circuit, and the controller generates a first PWM signal according to the overall amplitude information; the first amplitude adjusting circuit performs amplitude modulation processing on an input original waveform according to the first PWM signal to generate a first analog waveform signal; the controller obtains amplitude information corresponding to the frequency of the modulation waveform by using the phase accumulator, and generates a second PWM signal; a second amplitude adjusting circuit performs multiplication operation on the second PWM signal and the first analog waveform signal to obtain a second analog waveform signal and obtain an inverted waveform signal; the controller obtains amplitude information corresponding to the frequency of the fundamental frequency waveform by using a phase accumulator, and generates a third PWM signal; and the synthesis adjusting circuit performs multiplication operation on the third PWM signal and the second analog waveform signal or the inverted waveform signal to generate an intermediate frequency treatment waveform.

The invention relates to a double-frequency filtering metasurface design method based on topological optimization. The method comprises the following steps: establishing a two-dimensional simulation model comprising a double-frequency filtering metasurface matrix and a scatterer; according to a preset target forbidden band, taking a forbidden band frequency covering frequency doubling target interval as a fitness function, coding the binary matrix representing material distribution as a chromosome to perform optimization iteration of the chromosome, and obtaining the chromosome with the maximum fitness function value; in optimization iteration, material distribution corresponding to chromosomes is constructed on a two-dimensional simulation model, an energy band structure of the two-dimensional simulation model is obtained, and a fitness function value is calculated; and according to the binary matrix of the chromosome with the maximum fitness function value, outputting final optimized material distribution of the double-frequency filtering metasurface, and performing performance verification on a result through simulation to obtain the double-frequency filtering metasurface of which a fundamental frequency wave can be blocked through a double-frequency wave. Compared with the prior art, systematic optimization of the frequency doubled sound filtering scene is realized.

The application provides a note-level automatic singing transcription method based on target detection and language characteristics, comprising the following steps: step 1: converting a one-dimensional audio sequence into two-dimensional mel spectrum slice and phoneme posterior slice with similar width-height ratio through a preprocessing method of mel transformation, phoneme classification, linear intensity mapping and slicing; step 2: performing target detection on the mel spectrum slice and phoneme posterior slice, post-processing and time adjustment on the left and right boundaries of the boundary box obtained by target detection, and then obtaining the final start time and end time through decision screening; step 3: taking the lower boundary of the target detection boundary box as the fundamental frequency, obtaining the final fundamental frequency through peak value search, and then converting the final fundamental frequency to obtain the MIDI pitch value. The method can effectively improve the phoneme feature extraction effect, improve the phoneme posterior slice quality and improve the feature extraction and analysis effect, thereby improving the transcription accuracy.

The invention relates to the technical field of power monitoring, in particular to an online monitoring method and system for a power control cabinet. The method comprises the following steps: acquiring a time domain signal, tracking a fundamental wave frequency, adjusting a sampling window, and performing Fourier transform to obtain a harmonic amplitude and a phase; harmonic waves are divided into harmonic wave correlation groups according to association rules, harmonic wave phase consistency coefficients are calculated to weight the total energy in the groups, and weighted harmonic wave energy is obtained; total inter-harmonic energy is calculated, and an inter-harmonic structure factor is obtained based on the spectral entropy. And acquiring a real-time load rate and a change rate, and calculating a synchronous change coefficient and a load factor. And summing the weighted harmonic energy and the corrected inter-harmonic energy to obtain total distortion energy, and obtaining a comprehensive distortion index according to the total distortion energy. According to the scheme, the structured inter-harmonics possibly caused by the early failure of the equipment can be found earlier, and the requirements of early warning and predictive maintenance are met.

The invention provides a nonlinear ultrasonic detection method for micro-damage of concrete, and particularly relates to the technical field of material detection. The method specifically comprises the following steps: S1, defining a scanning area and planning a scanning path; s2, exciting fundamental frequency ultrasonic waves to the signal excitation points in the signal excitation area in sequence through a transmitting probe by using a pulse reversal technology; s3, receiving the fundamental frequency ultrasonic waves and the generated second harmonics at the signal excitation points at the corresponding positions of the signal receiving area at the same time in sequence by using a receiving probe; s4, scanning all signal excitation points on the whole surface of the to-be-detected concrete scanning area according to a set scanning path; s5, nonlinear ultrasonic parameters on all sound paths are calculated; and S6, constructing a nonlinear ultrasonic imaging spectrum and judging the spatial distribution and damage degree of the micro-damage of the to-be-detected concrete. According to the method, the concrete micro-damage is represented by directly utilizing nonlinear ultrasonic parameters, and the detection limit of ultrasonic waves and the resolution of low-frequency ultrasonic waves are effectively improved on the premise that the penetrating power of the low-frequency ultrasonic waves is reserved.

The invention discloses an inland river ship ferry whole ship equipment health monitoring and early warning system based on the Internet of Things, and relates to the technical field of ship equipment monitoring. A dynamic dual-threshold coupling mechanism is adopted, and the method comprises the steps that a noise estimation module combines a navigation state and a historical working condition library to generate a fundamental frequency floating range vector and a harmonic ratio threshold, and the problem of signal distortion caused by vibration fundamental frequency drift is solved; the collaborative analysis module constructs a three-dimensional incidence matrix of temperature gradient, envelope energy and current distortion rate, expands a harmonic ratio threshold into a dynamic window, and realizes multi-parameter synchronous out-of-limit judgment; and the health scoring module quantifies the equipment degradation degree through dynamic regular comparison of a waveform envelope line and a historical curve. And when the incidence matrix is in a continuous five-period super-dynamic window, outputting a micro-fault feature code, and mapping the micro-fault feature code to an equipment topology library in combination with the health score to generate an operation instruction. The fault recognition rate under the variable working conditions of the ship is improved, and predictive maintenance of early faults such as bearing abrasion and electric overload is supported.

The invention discloses a fundamental frequency detection method, device and equipment and a storage medium, and relates to the technical field of audio processing, and the fundamental frequency detection method comprises the steps that time domain preprocessing is carried out on a multi-frame splicing signal to obtain first time domain preprocessing data, and the time domain preprocessing comprises filtering processing, clipping processing and windowing processing; performing fast Fourier transform on the first time domain preprocessed data to obtain preprocessed frequency domain signal data; carrying out peak detection on the preprocessed frequency domain signal data to obtain candidate fundamental frequencies; and performing harmonic matching on the candidate fundamental frequency based on a preset frequency deviation range to obtain a support degree score of the candidate fundamental frequency, and determining a fundamental frequency detection result according to the support degree score. According to the scheme, the stability and the accuracy of the fundamental frequency detection algorithm applied to the real-time audio processing system can be balanced.

A method for filtering periodic noise and a filter using the method are provided. The method includes: obtaining an input signal; detecting a fundamental frequency corresponding to a maximum peak in a spectrum of the input signal, detecting a harmonic frequency according to the fundamental frequency, and detecting an aliasing frequency corresponding to the harmonic frequency in response to the harmonic frequency corresponding to the fundamental frequency being greater than a Nyquist frequency of the input signal; filtering the fundamental frequency and at least one of the harmonic frequency and the aliasing frequency of the spectrum to generate a first filtered spectrum, and restoring the input signal according to the first filtered spectrum to generate an output signal; and outputting the output signal. The method for filtering the periodic noise and the filter using the method may filter the periodic noise in the input signal affected by an aliasing effect.

The invention provides a fundamental frequency calculation method for adaptive parameter adjustment, which is suitable for power signal frequency estimation under a noise interference or multi-harmonic background. Firstly, voltage and current signals are subjected to analog-to-digital conversion to obtain digital signals, a CIC filter in a non-recursive form is adopted for multi-stage extraction processing, and the data complexity is reduced; sequentially inputting the extracted signals into a plurality of notch filters with feedback structures for harmonic filtering; and iteratively updating the center frequency parameter of the notch filter through a gradient descent method, and when the error function is minimized, the current frequency parameter is the fundamental frequency of the signal. The method has the characteristics of fast convergence, strong robustness and high calculation precision, and is suitable for scenes of electric energy metering, frequency protection and the like.

The invention relates to the technical field of motor control, and discloses a bearingless composite rotor cage type asynchronous motor vibration real-time compensation control method, which comprises the following steps: acquiring and preprocessing a rotor displacement signal to obtain a filtered displacement signal; processing the filtered displacement signal based on a second-order generalized integrator, and extracting a fundamental frequency harmonic component synchronous with the mechanical angular velocity of the rotor; adopting a simplified LMS algorithm to dynamically optimize the amplitude weight and the phase weight of the compensation force, and generating a feedforward compensation force according to the optimized weights; a two-channel control framework is constructed, and total control force is synthesized; the suspension force winding is driven by the inverter to generate corresponding radial suspension force, so that unbalance vibration of the rotor is counteracted; according to the invention, the second-order generalized integrator harmonic observer is adopted to realize high-precision extraction of the fundamental frequency component, and the mechanical angular velocity change of the rotor can be tracked in real time in cooperation with a frequency adaptive adjustment mechanism.

A tool abnormality detection system includes a detector configured to detect a sound wave generated in processing a workpiece with a tool and output a detection signal based on the sound wave, and a controller configured to generate, based on the detection signal, determination signals indicating intensities in respective frequency bands: a fundamental frequency band of a wear-indicative sound wave; and a higher frequency band that is higher than the fundamental frequency band, and determine whether the tool is worn by comparing each of the determination signals to its respective wear threshold which is set for the respective frequency bands.

The present invention relates to the technical field of vibration data detection, and specifically relates to an electric chain saw chain device and an operating safety detection method. The method comprises: obtaining a time-series initial noise factor of vibration data at each moment on the basis of the difference between local vibration data in a vibration signal data sequence and distribution of the differences between all adjacent vibration data within a local range, and obtaining a time-series noise factor of the vibration data at each moment by means of distribution of time intervals between all adjacent extreme points in a local vibration data curve; on the basis of the difference between the energy corresponding to a fundamental frequency and the energy corresponding to harmonic frequencies and the degree of disorder in energy distribution of the harmonic frequencies, obtaining a frequency domain noise factor of the vibration data at each moment, and filtering the vibration data to obtain a filtered vibration signal data sequence; and then performing operating safety detection of the electric chain saw chain device. The present invention reduces the interference of environmental noise and improves the accuracy of the operating safety detection of the chain device.

The invention relates to the technical field of dynamic balance testing of rotating machinery, and discloses a dynamic balance state testing system based on equipment operation data, which comprises a synchronous sampling module, a fundamental frequency vector analysis module and an influence coefficient self-adaptive calibration module, the synchronous sampling module collects key phase pulses and original vibration signals of the rotating equipment; a fundamental frequency vector analysis module extracts an instantaneous rotating speed and a real-time fundamental frequency vibration vector; the influence coefficient self-adaptive calibration module stores a weight matrix representing rotor supporting characteristics, monitors a rotating speed fluctuation variance, corrects the weight matrix according to complex deviation of a vibration vector when the variance exceeds a preset threshold value, solves a net unbalance vector of the controlled rotating equipment, and outputs the net unbalance vector. According to the method, the rotating speed micro fluctuation in the operation process is used as an excitation increment source, and the sensitivity model reflecting the rotor bearing characteristics is constructed, so that the dynamic balance test gets rid of the limitation of adding a physical test weight, and the online test requirement under the continuous working condition is met.

The invention discloses a sparse and dense stacked nonlinear electromagnetic ultrasonic detection transducer and a pipeline creep detection device, and relates to the technical field of pipeline creep damage detection. The sparse coil (namely the first coil) with the distance between the wires equal to the half-wavelength of the fundamental frequency ultrasonic waves and the dense coil (namely the second coil) with the distance between the wires equal to the quarter-wavelength of the fundamental frequency ultrasonic waves are arranged in a stacked mode to form the sparse and dense stacked coil. Fundamental frequency ultrasonic waves with enough strength can be effectively excited to enter a material of a detected pipeline, and nonlinear ultrasonic response signals (namely second harmonic signals) generated by lattice nonlinear change caused by early creep micro-damage (such as micro-voids, grain boundary slippage and dislocation pinning point weakening) in the material are captured and enhanced in a high-sensitivity manner; and timely and reliable technical guarantee is provided for safe operation of the pipeline.

The application discloses a piano music segmentation and note recognition algorithm based on a deep learning network, and comprises the following steps: based on a recurrent neural network, obtaining the starting point of each single tone from a continuous piano audio; according to the starting point of each single tone, segmenting a complete piano audio signal into several single tone audios; constructing an audio data set for pitch recognition; pre-processing signals in the audio data set, drawing a transformed spectrogram, and simultaneously segmenting the spectrogram according to the frequency band of each fundamental frequency to obtain a sub-spectrogram; taking the multiple sub-spectrograms segmented from the spectrogram as input, and recognizing the pitch through multiple convolutional neural networks. Compared with a traditional time domain method, the application no longer depends on the selection of a threshold, improves the generalization ability, compared with a traditional frequency domain method, simplifies the calculation process, and improves the running speed.

The application discloses a multi-frequency harmonic injection system and method of a radio frequency power supply, comprising: a signal generating device configured to generate a target fundamental frequency component and at least one target harmonic component synchronized with the target fundamental frequency component, and output a multi-frequency radio frequency signal containing the target fundamental frequency component and the target harmonic component; a sampling device configured to sample the multi-frequency radio frequency signal to obtain a sampling signal; a signal processing device configured to separate an actual fundamental frequency component and an actual harmonic component from the sampling signal; and a control device configured to adjust the amplitude ratio and / or the phase between the target fundamental frequency component and the target harmonic component according to the amplitude and the phase of the actual fundamental frequency component and the actual harmonic component. The application realizes precise adjustment of plasma ion energy, waveform stability, process uniformity and reliability improvement through multi-frequency harmonic synchronous generation, real-time closed-loop regulation and decoupling control of ion energy-flux.

The present application provides a directional sound pickup method, system, device, and storage medium, relating to the field of sound pickup. The method comprises: performing MVDR beamforming processing on the initial speech signal input by the microphone array, and then extracting the BFCC features and fundamental frequency features of the speech signal. The BFCC features are processed using a pre-trained speech / noise separation DNN to obtain a time-frequency mask. Comb filter parameters are adaptively designed based on the fundamental frequency features, and the initial speech signal is comb filtered. The time-frequency mask is used as a weighting coefficient and multiplied with the comb-filtered speech signal and the initial speech signal, respectively, to estimate the target speech energy and noise energy. The frequency-dependent Bark gain coefficient is calculated on the Bark frequency scale and used to enhance the speech signal in the time-frequency domain. Finally, the enhanced speech signal is converted into a time-domain signal through an inverse BFCC transform to obtain the target enhanced speech pointing in the target direction. The above scheme improves the directional sound pickup effect.

This application provides a control method, system, and electronic device for a PWM rectifier. The control method includes: determining the actual current of the PWM rectifier and determining a current error based on the actual current and a reference current; obtaining a first control parameter based on the current error using a preset algorithm; determining an error compensation value based on the current error using a repetitive controller, and compensating the first control parameter with the error compensation value to obtain a second control parameter; determining the fundamental frequency of the modulation wave based on the second control parameter, and obtaining a control signal based on the fundamental frequency of the modulation wave using a discontinuous pulse width modulation (DPWM) method to control the PWM rectifier. This application introduces a repetitive controller into the discontinuous pulse width modulation (DPWM) method, which improves the problem of large current harmonics caused by periodic errors due to periodic entry into clamping state in the DPWM modulation method, thereby improving control accuracy.