587 results about "Fundamental frequency" patented technology

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 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 relates to the technical field of inverter control, and discloses an inverter output power control method and device, equipment and a storage medium. The method comprises the following steps: performing power frequency fundamental wave extraction and multi-band band-pass filtering on acquired voltage and current sampling data; performing phase compensation, first coordinate transformation and positive and negative sequence decoupling operation on the filtered fundamental wave principal component data; on the basis of a synchronous phase angle and a power grid fundamental wave frequency obtained by positive and negative sequence decoupling operation, carrying out second coordinate transformation, moving average and harmonic power delay difference operation on three-phase current and voltage data of an alpha-beta coordinate system; performing multi-level power calculation, power capacity distribution, error characteristic evaluation and decoupling operation on the inversion fundamental component and the inversion harmonic component subjected to the difference operation; and performing output signal modulation on the inversion power control quantity of the decoupling operation based on the fundamental wave synchronization phase angle, and generating a power control result. According to the invention, the control performance of the inverter on the output power in actual operation is improved.

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 provides a fumigation control method based on pest and disease damage trend prediction, and the method comprises the steps: carrying out the spectrum analysis of audio data information through employing a fast Fourier transform algorithm, extracting the frequency domain feature vector of the chirp sound of each pest species, and enabling the frequency domain feature vector to comprise a fundamental frequency, harmonic energy distribution, chirp duration and chirp rhythm; according to the extracted chirp frequency domain feature vector, chirps of local main agricultural pests are identified and classified by adopting a support vector machine algorithm, and the types and life cycle information of the pests are judged by matching with a preset pest species chirp feature template library; and performing spatial mapping on the predicted population density distribution data by adopting a Kriging interpolation algorithm to generate a spatial distribution diagram, determining the aggregation degree and diffusion trend of pests in each region of the field, and dividing a plurality of prevention and control regions and buffer regions.

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 provides a real-time dynamic harmonic detection method and system for a traction power supply system, and relates to the technical field of harmonic detection, and the detection method comprises the following steps: collecting a voltage signal of the traction power supply system in real time, and dynamically tracking fundamental frequency fluctuation through a phase-locked loop technology; dynamically adjusting the data window length of FFT analysis; dynamically adjusting a frequency spectrum calculation kernel of the FFT; carrying out linear compensation on the detected harmonic phase; taking the preliminarily detected harmonic parameter as an initial value, and iteratively updating the harmonic parameter until convergence by minimizing a signal reconstruction error; dynamically adjusting a sampling interval according to the fundamental frequency fluctuation, and carrying out anti-aliasing processing by adopting a filter with a variable cut-off frequency; and constructing a matrix model containing a fundamental frequency fluctuation parameter, and calculating a real harmonic parameter through a least square method. According to the method, the detection defect of the fixed window FFT during frequency fluctuation can be systematically solved, and high-reliability real-time data support is provided for harmonic resonance suppression of the electrified railway.

The invention provides a sound standardization evaluation system for multi-dimensional acoustic parameter and emotional scene dynamic analysis, and aims to realize structured and objective evaluation of voice performance. The system comprises an audio acquisition module, an audio processing module, a standard evaluation module and an integration processing module. The audio processing module performs noise reduction, pre-emphasis, sampling rate adjustment, framing and slicing operation on the original voice data; the standard evaluation module executes character and pronunciation accuracy analysis, acoustic basic skill feature evaluation or emotion and scene adaptation degree analysis based on multi-modal fusion according to an evaluation type set by a user; parameters including fundamental frequency, formant, sound intensity, fundamental frequency perturbation, amplitude perturbation and the like are extracted in evaluation, and classification prediction is completed in combination with a machine learning model; and finally, the integration processing module generates an evaluation report including a scoring result, question prompts and personalized training suggestions, and provides closed-loop feedback to support sound training and expression optimization.

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 provides a self-adaptive adjustment method for sound tone of a live broadcast person based on a network model, which relates to the technical field of audio signal processing and comprises the following steps of: determining an accurate starting position and an accurate ending position of packet loss through a sudden change point of a short-time energy function and an abnormal change point of a zero-crossing rate; therefore, the packet loss interval is repaired by pertinently utilizing the fundamental frequency track characteristic and the formant characteristic. The method provided by the invention can solve the problems of fundamental frequency track breakage and unnatural voice caused by the contradiction between acoustic parameter decoupling repair and real-time processing constraint in a high packet loss rate scene in a traditional voice repair method, thereby realizing high-precision and low-delay self-adaptive repair of packet loss voice, and improving the voice recovery efficiency. And the sound quality and the user experience in the live scene are obviously improved.

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 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 discloses a bridge fundamental frequency and deflection influence line synchronous identification method under vehicle-induced excitation, and relates to the technical field of bridge safety monitoring, and the method comprises the following steps: 1, deducing a fundamental frequency analysis formula through a formula, and setting the fundamental frequency analysis formula as an E-VMD method modal analysis cut-off frequency; 2, stripping a dynamic response component in the deflection response, and identifying a bridge operation frequency through FFT (Fast Fourier Transform); 3, taking the operation frequency as a threshold value, and stripping the dynamic response again; and 4, stripping the axle effect to obtain a static deflection influence line. According to the method, the bridge fundamental frequency obtained through indirect identification based on the dynamic response in the vehicle bridge crossing process has high precision, the relative error between the bridge fundamental frequency and the actually-measured bridge modal fundamental frequency is low, tedious steps of traditional modal testing are avoided, and the analysis efficiency is improved.

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.

A system for conducting voice modification on an audio input signal comprising speech to obtain an audio output signal according to an embodiment is provided. The system comprises a feature extractor for extracting feature information of the speech from the audio input signal. Moreover, the system comprises a fundamental frequencies generator to generate modified fundamental frequency information depending on the feature information, such that the modified fundamental frequency information comprises modified fundamental frequencies being different from real fundamental frequencies of the speech, and / or such that the modified fundamental frequency information indicates a modified fundamental frequency trajectory being different from a real fundamental frequency trajectory of the speech. Furthermore, the system comprises a synthesizer for generating the audio output signal depending on the modified fundamental frequency information and depending on the feature information.

An accurate and elegant model is provided to characterize HFTO. For Type 1 HFTO, the model can predict frequency of the HFTO based on the distance between a reference location on the bottomhole assembly (e g., the end of the drill bit) and a point 40% up the motor. In short BHA strings there is the fundamental frequency while in longer BHA the first harmonic is used. For Type 2 HFTO, the model can predict frequency of the HFTO based on distance between a reference location on the bottomhole assembly (e.g., the end of the drill bit) and the first slick contact point, which is optionally in the middle of a long flex joint.

The invention provides a method, medium and system for calculating the extension length of a hydraulic fracturing main fracture, and belongs to the technical field of hydraulic fracturing. The method, medium and system for calculating the extension length of the hydraulic fracturing main fracture comprise the steps that a water hammer wave signal at the position of a well mouth after hydraulic fracturing pump stopping is obtained; performing cepstrum analysis on the water hammer wave signal; the minimum period of the positive pulse extreme point of the complex cepstrum curve is calculated, and the time of the water hammer wave moving from a wellhead to a bridge plug is obtained; calculating the average speed of movement of the water hammer waves in the well; performing linear trend removal processing on the local signal of the water hammer wave; fourier transform is carried out on the local signal after linear trend removal processing, and a water hammer wave local signal frequency spectrum is obtained; extracting a fundamental frequency corresponding to a maximum value point in the water hammer wave local signal spectrum as a response frequency in the main crack; according to the response frequency in the main fracture, the propagation time of the water hammer wave in the main fracture is calculated; and calculating the extension length of the main crack.

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 relates to a blade flutter evaluation method based on an approximate time domain harmonic balance method under air inlet distortion, which comprises the following steps of: calculating a vibration mode of an aero-engine blade, and respectively appointing a blade vibration rule and an air inlet distortion boundary condition so as to determine and analyze an unsteady flow field fundamental frequency and a harmonic wave caused by blade vibration and air inlet distortion; and then, a coupling flow field of blade vibration and air inlet distortion is solved based on an approximate time domain nonlinear harmonic method, then accumulated work in a vibration period is calculated, and the flutter stability of the aero-engine blade is evaluated according to positive and negative accumulated work. According to the method, the influence of multiple parameters and any form of air inlet distortion on the flutter stability of the aero-engine blade can be evaluated at the same time; the evaluation result is calculated based on the numerical value of the single channel, the calculation time consumption and the calculation resource demand are remarkably reduced, and the method has important significance on the anti-vibration design of the rotor and stator blades of the aero-engine.

The invention provides a switch cabinet contact temperature rise wireless sensing method and system based on surface acoustic wave resonance, and relates to the technical field of power system switch cabinet detection, and the method comprises the steps: calculating the real-time offset of a fundamental frequency and a third harmonic relative to a reference frequency, and obtaining the fundamental frequency offset and the third harmonic offset; in combination with the fundamental frequency offset and the equivalent acoustic impedance variable quantity of the oxide film, surface acoustic wave propagation path deformation caused by thermal expansion of the contact material is compensated by using a thermal-acoustic coupling partial differential equation, and the fundamental frequency net offset after temperature decoupling is obtained; sparse reconstruction is carried out on the temperature field of the contact area of the contact by adopting a compressed sensing algorithm, and three-dimensional temperature gradient distribution of the contact area of the contact is output; and inputting the three-dimensional temperature gradient distribution and historical time sequence data thereof into an intrinsic mode decomposition model for processing, and generating a dynamic self-adaptive early warning threshold value. The system has the advantages that passive, wireless, high-precision and full-space temperature rise monitoring is achieved, and intelligent operation and maintenance decision making of the switch cabinet is directly driven.

A multi-band characteristic-based inverter micro-grid line fault direction detection method comprises the following steps of: S1, constructing a criterion # 1 that the phase difference of fundamental frequency positive sequence fault component voltage and current is in a range of-180 degrees to 0 degree, and constructing a criterion # 2 that the cosine similarity of high frequency positive sequence fault component voltage and current is less than-0.1; s2, collecting endpoint voltage and line current information of each line of the micro-grid; s3, extracting the phase difference of the fundamental frequency positive sequence fault component voltage and current of each line end point, judging whether a criterion # 1 is met or not, if yes, turning to step S5, and if not, turning to step S4; s4, extracting the cosine similarity of the high-frequency positive-sequence fault component voltage and current of each line end point, judging whether a criterion # 2 is met or not, if yes, turning to step S5, and if not, turning to step S6; s5, determining the fault direction of the end point as the forward direction; and S6, determining that the fault direction of the end point is a reverse direction.

The invention discloses a non-linear optical structure with perfect phase matching and high second harmonic generation efficiency. The non-linear optical structure comprises a fundamental frequency wave resonance structure, a non-linear optical layer, a second harmonic reflection structure and a substrate, the fundamental frequency wave resonance structure is used for generating electromagnetic field local enhancement at an incident fundamental frequency wavelength and realizing a phase matching condition by optimizing electric field phase distribution; the nonlinear optical layer is used for frequency conversion from fundamental frequency waves to second harmonics and regulating and controlling harmonic radiation capability and phase regulation and control; the second harmonic reflection structure is used for controlling coupling-out of second harmonics; the rotary nonlinear optical layer can adjust the phase characteristic of the radiated second harmonic so as to realize perfect phase matching of a harmonic field; according to the nonlinear optical structure with perfect phase matching and high-efficiency second harmonic generation efficiency, accurate control of phase matching conditions is realized through reasonable optical film stacking and phase matching technologies, and high-efficiency coupling-out and utilization of second harmonics are ensured.

The method comprises the following steps: obtaining training data of a voice data construction model, preprocessing the obtained training data to obtain original waveform features and multi-scale fundamental frequency features, inputting the features into the model to carry out model training, and obtaining an attention enhancement model; in the training process of the detection model, hyper-parameters of the detection model are set, a loss function is continuously reduced, the trained detection model is obtained when the set training frequency is reached, test data of the voice data construction model are obtained, and preprocessing is carried out to obtain original waveform features and multi-scale fundamental frequency features; the original waveform features and the multi-scale fundamental frequency features are input into a trained model for model testing, in the testing process, a voice authenticity classification result is obtained, the performance of the model is evaluated, and the performance of the detection model can be effectively improved.

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 discloses a transmission line disconnection fault identification method and device based on multi-stage current comparison, and the method comprises the steps: extracting the zero-sequence current data of a fault line and the tripping signal data and reclosing signal data of a protection device from a fault recording file or a protection recording file obtained from the two sides of the fault line, the fault process of the line is divided into a plurality of stages; calculating per unit values of the current fundamental frequency amplitudes of the two sides of the fault line in each stage by taking the maximum value in the current fundamental frequency amplitudes of the stage before the fault as a current amplitude reference value; and judging the disconnection condition of the faulty line based on comparing the per-unit value with the disconnection fault judgment coefficient kdx and the grounding judgment coefficient kjd. According to the invention, the fault process is divided into a plurality of stages, and each time period in which the line may be disconnected or grounded is fully considered; the method can efficiently and accurately judge the line breaking fault of the line and whether the condition of grounding after line breaking exists, and does not cause misjudgment with the grounding fault.

The invention discloses a three-phase squirrel-cage asynchronous motor rotor broken bar small sample fault diagnosis method. Firstly, Hilbert transform is carried out on an acquired original current signal to eliminate the influence of frequency spectrum leakage of a fundamental frequency component, and a fault characteristic frequency is highlighted; secondly, a double-branch residual shrinkage network structure is provided, noise components in the signals are eliminated, and multi-scale features in the current and vibration signals are extracted; meanwhile, aiming at the time sequence characteristics of the current signal and the vibration signal, a bidirectional circulation gating unit is introduced, and the advanced characteristics of the fused characteristics are extracted. According to the method, interference of noise and harmonic waves can be reduced, and rotor broken bar fault diagnosis and severity estimation under the small sample condition are realized by adopting the current signal and the vibration signal aiming at two aspects of regularization technology and model extraction.

The invention discloses an urban electromagnetic noise suppression method based on multi-source noise. The method comprises the following steps: 1, suppressing power frequency noise in noise by using a Wavelet-NGSE algorithm; 2, random noise in the noise is suppressed through minimum noise separation; (3) residual random noise in the noise in the step (2.3) is suppressed by using a CNN-GRU model; according to the invention, the noise in the collected transient electromagnetic signals is classified in a refined manner, and each type of noise features are removed. In order to solve the problem of power frequency harmonic noise interference, an accurate fundamental frequency value is extracted through a Wavelet-NGSE algorithm, and the suppression of power frequency noise with high correlation is realized by combining the periodicity of power frequency and adjusting the transmitting frequency and waveform; further suppressing random noise by using superposition average; and finally, the minimum noise separation + CNN-GRU network calculates data components and reconstructs signals after minimum noise separation, so that high-precision residual noise separation is realized, electromagnetic data with a high signal-to-noise ratio is obtained, and a foundation is laid for realizing accurate interpretation of deep signals.

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.