55 results about "Dominant frequency" patented technology

This invention provides a non-destructive testing method and apparatus for defects in ferromagnetic pipes, belonging to the field of pipe inspection. The method includes: acquiring a voltage signal, which is obtained by converting the capacitance change signal continuously collected by the bipolar capacitor as the ferromagnetic pipe and the upper and lower semi-circular bipolar capacitor move at a constant axial velocity relative to each other; extracting time-domain and frequency-domain features from the voltage signal; and determining the defect type and location based on the voltage signal and the extracted features. The extracted features include time-domain and frequency-domain features; the time-domain features include the signal standard deviation, coefficient of variation, and density of local extrema; and the frequency-domain features include the dominant frequency component and harmonic energy ratio. This method utilizes the physical property that the dielectric constant of a ferromagnetic pipe differs depending on whether it has defects or not, enabling the detection of defects deep within the component. It effectively avoids interference from various environmental electromagnetic noises, ensuring the accuracy of the detection results, and eliminates the need for point-by-point scanning, resulting in higher detection efficiency.

This invention discloses a method and system for monitoring mechanical damage to batteries during electric vehicle transportation based on acoustic emission spectrum analysis. The method includes: performing multi-scale decomposition of the original signal sequence using wavelet transform to separate high-frequency transient components and low-frequency background noise, obtaining a denoised elastic wave signal; calculating time-domain features, including peak amplitude and duration, based on the denoised elastic wave signal, and combining this with frequency-domain features such as the dominant frequency component to obtain a comprehensive feature vector; if the peak amplitude of the comprehensive feature vector exceeds a preset threshold, it is judged as a potential damage event, and damage-related subsets are extracted from the feature vector to obtain damage candidate features; training the damage candidate features using a support vector machine classifier to obtain damage type labels; and fusing transportation environment data with the damage type labels, using sliding window analysis to track signal change trends and determine the degree of damage evolution. This invention achieves accurate identification, classification, and dynamic monitoring of battery pack transportation damage.

A method for controlling an OIS system of an image capturing device, the method comprising: obtaining a first and a second time-series of samples derived from a motion signal of a motion sensor of the image capturing device, wherein the motion signal indicates a motion of the image capturing device, and wherein the first time-series spans a longer time period of the motion signal than the second time-series; determining a current dominant frequency for the motion signal based on a frequency analysis of the first time-series; and determining a setpoint for the OIS system by: fitting to the second time-series a model function based on a sine and / or cosine function and the current dominant frequency, extrapolating the fitted model function past a last sample of the second time-series to predict a successive sample, and determining the setpoint based on the predicted successive sample.

This invention relates to the field of geotechnical engineering mechanics testing and non-destructive testing technology. Existing technologies suffer from high computational delays due to passive monitoring modes, the inability to perform real-time physical intervention before macroscopic brittle fracture of soil and rock masses, and the inability to effectively preserve the critical failure state of rocks for microscopic damage constitutive relationship studies. This invention discloses a system and method for analyzing acoustic emission signals from freeze-thaw damage in soil and rock masses. A signal acquisition module is used to capture acoustic emission signals in real time; a feature analysis module is used to extract frequency band energy distribution characteristics and the instantaneous rate of change of the dominant frequency drift; a state determination module is used to determine the microcrack damage evolution stage and the precursors to critical failure based on the above features; and a linkage intervention module is used to generate physical intervention commands based on the determination results, enabling real-time adaptive adjustment or state latching of mechanical loads and ambient temperature. This allows for microsecond-level closed-loop linkage intervention, suppressing sudden shear surface slippage and instability, and effectively preserving the microstructure of rocks on the eve of critical failure.

The present application relates to the technical field of pipeline hydrostatic test, and especially relates to a pressure water supplementing and metering device for municipal pipeline hydrostatic test, which comprises a water tank, a booster pump, a flowmeter and a control cabinet, a program controller is arranged in the control cabinet, further comprising a pressure sensor and a vibration sensor arranged along the axial direction of the pipeline to be tested, and an active tunable damper arranged between the pump outlet and the pipeline; the program controller synchronously collects pressure and vibration data, carries out correlation analysis on the data, generates a pressure wave space-time propagation graph, calculates a water hammer risk index and divides a risk level through a nonlinear fusion model according to the dominant frequency, amplitude, propagation speed change rate and vibration energy of the pressure wave, selects an inhibition strategy according to the risk level, calculates a pressure peak value reduction rate and a wave fluctuation decay time according to the data after inhibition, and generates an effect evaluation value. The present application realizes active sensing, graded inhibition and effect evaluation of water hammer risk, and improves the safety and intelligent level of the hydrostatic test.

This invention discloses a hearing screening and tinnitus assessment method based on multi-frequency cross-analysis, specifically relating to the fields of hearing testing and neural information processing technology. It constructs an initial hearing vector in the individual frequency domain, generates a deviation feature vector based on a standard population database, extracts a set of abnormal frequency bands, and constructs a frequency domain focusing model. Multiple-intensity sound stimulation is applied to the abnormal frequency bands, and neural response parameter sequences are collected. Further cross-spectral analysis is performed to construct an individualized tinnitus resonance map, and the dominant frequency features and response intensity are extracted. Combined with subjective tinnitus scores, a tinnitus risk index is calculated, and a screening conclusion is output. This invention can achieve objective, quantitative, and spectral-level tinnitus identification, improving screening accuracy and clinical applicability.

This application relates to the field of industrial automation testing technology and discloses an instrument anti-jitter reading method based on pressure pulsation characteristics synchronization. Through a synchronous triggering mechanism, continuous video streams of the pressure gauge and pipeline pressure fluctuation data are simultaneously acquired during the pressure holding phase. Frequency domain transformations are performed on the pointer displacement sequence and the pressure fluctuation sequence respectively to extract the dominant frequency of pointer oscillation and the dominant frequency of pressure pulsation, and the frequency difference is calculated. When the frequency difference is less than a preset threshold, it is determined to be a systematic jitter caused by pressure pulsation. The pressure fluctuation data is used as a reference to reconstruct the pointer displacement sequence to obtain the pressure reading value; otherwise, an abnormal jitter processing procedure is executed. This invention converts pressure pulsation interference into a reference signal, realizing the quantitative differentiation and differential processing of jitter sources. Without adding additional hardware, it provides a reliable anti-jitter reading scheme for automated pressure gauge verification, and also has online diagnostic capabilities for mechanical faults.

This invention provides a method for predicting the dominant frequency of blasting vibration by integrating parameter fluctuation processing and the Dream Optimization Algorithm (DOA), belonging to the field of underground engineering safety control technology. The system includes a data acquisition and uncertainty modeling module, a data preprocessing and feature construction module, a hyperparameter optimization module, and a prediction model training and result output module. The method obtains relevant parameters through on-site investigation and monitoring, and generates an extended sample set using a combination of probabilistic perturbation modeling and fuzzy triangular modeling. The data is preprocessed and features are selected. The DOA algorithm is used to globally search the hyperparameters of the Support Vector Regression (SVR) model, and the optimal hyperparameter combination is selected by combining a robustness fitness function. The SVR model is trained, and prediction results and uncertainty prediction intervals are generated. This invention can explicitly characterize the uncertainty of geological parameters, achieve efficient global optimization of hyperparameters, improve prediction accuracy, robustness, and generalization ability, and is applicable to different geological conditions and blasting scenarios. It can be extended to various blasting dynamic response prediction tasks.

This invention discloses an adaptive filtering method and system for locating pipeline leaks, belonging to the field of pipeline leak detection and location technology. Addressing the problem that existing technologies for pipeline leak location use fixed filtering, which cannot match the dynamic dominant frequency band of the leakage sound and requires manual parameter adjustment by professionals, resulting in poor location accuracy, this invention uses dominant frequency range analysis to obtain the actual dominant frequency interval. After intersection determination, a common filtering range is determined according to rules, and the signal is then filtered and purified for location calculation. This invention can dynamically match the dominant frequency characteristics of the leak scene without manual intervention, reducing the location error to within three meters. It is also compatible with pipelines of different materials, diameters, and shapes, as well as media such as water, oil, and gas, reducing unnecessary excavation and lowering repair costs and safety risks.

This invention provides a method for controlling the optical image stabilization (OIS) system of an imaging device. [Solution] A first time series sample and a second time series sample are obtained from the motion signal of the motion sensor of the imaging device. The motion signal indicates the movement of the imaging device, and the first time series spans a longer period of motion signal than the second time series. A first time series sample and a second time series sample are obtained. Based on the frequency analysis of the first time series, the current dominant frequency of the motion signal is identified. A model function based on the sine and / or cosine functions and the current dominant frequency is fitted to the second time series. To predict consecutive samples, the fitted model function is extrapolated past the last sample of the second time series. The setpoint of the OIS system is identified by identifying the setpoint based on the predicted consecutive samples.

This invention belongs to the field of pipeline eddy current damage localization technology. It proposes a method, system, medium, and computer equipment for pipeline eddy current damage localization. The method involves acquiring multi-channel original discrete signals from the pipeline, performing mean-reduction processing, and determining the dominant frequency. Based on the dominant frequency, an optimal bandwidth parameter is adaptively determined from a candidate bandwidth set using a kurtosis maximization criterion. A complex Moray wavelet function is constructed using the dominant frequency and the optimal bandwidth parameter, and a continuous wavelet transform is performed on the signal after removing the DC component to generate a multi-channel time-frequency distribution matrix. A frequency-weighted operator is applied to this time-frequency distribution matrix for energy enhancement, resulting in a multi-channel weighted energy map. Time-frequency coherent fusion is performed on the multi-channel weighted energy map, and a global energy peak is searched in the fused energy field. The coordinates corresponding to this peak are determined as the pipeline damage location. This invention effectively improves the accuracy and robustness of damage localization.

This application provides a PM-BPSK signal demodulation method, apparatus, and electronic device based on error decoupling. The method includes: acquiring the PM-BPSK signal to be demodulated; performing time-frequency analysis on the PM-BPSK signal using continuous wavelet transform, extracting the wavelet coefficient sequence of the subcarrier neighborhood, and performing circular mapping on its instantaneous phase to obtain the subcarrier phase time-frequency characteristics composed of cosine and sine components; performing decarrier and phase differential processing on the PM-BPSK signal, compensating for the dominant frequency offset based on circular mean, and then orthogonally projecting it with the subcarrier reference signal to obtain phase difference domain phase-locked features; extracting the main channel data from the subcarrier phase time-frequency characteristics and extracting the main channel data from the phase difference domain phase-locked features, and splicing them according to the channel dimension to form a dual-channel fusion feature; inputting the dual-channel fusion feature into a signal demodulation model and outputting a demodulated bit sequence. This application achieves highly robust and high-precision demodulation of PM-BPSK signals, providing a novel technical solution for non-cooperative communication.

This application provides a method, apparatus, device, and computer-readable storage medium for determining the extension length of an observation line in seismic exploration. The method includes: acquiring layer information of a target layer; the layer information including depth, velocity, maximum dip angle, and the dominant frequency of the target layer's location; determining the offset aperture for the target layer to meet the first Fresnel zone requirement based on the velocity and the dominant frequency; determining the offset aperture for the target layer to meet the 30-degree diffraction repositioning requirement based on the depth; determining the offset aperture for the target layer to meet the stratigraphic dip angle requirement based on the depth and the maximum dip angle; and determining the extension length of the observation line based on each offset aperture. The observation line extension length determined by this method can meet the offset repositioning imaging requirements of all reflection points, improving the acquisition accuracy of the observation system.

An example method includes storing reconstructed electrophysiological data sets for at least two baseline time intervals and at least one modulation time interval. The electrophysiological data sets are representative of electrophysiological signals reconstructed at locations across a respective surface of interest within a patient's body based on non-invasively measured electrophysiological signals for respective time intervals. The modulation time interval can overlap with modulating an arrhythmia or arrhythmogenic activity. The method can also include computing dominant frequency maps from the electrophysiological signals reconstructed for at least two baseline data sets and the at least one modulation data set. The method can also include analyzing the dominant frequency maps to determine an indication of dominant frequency stability across at least a portion of the surface of interest.

This invention belongs to the field of fluid-structure interaction dynamics analysis technology, and specifically discloses a method and system for analyzing the dynamic characteristics of an acoustic-frequency resonant hybrid system. The method includes: introducing an external excitation force vector and a fluid feedback force vector into the dynamic control equations of the acoustic-frequency resonant hybrid system to form coupled dynamic equations; numerically characterizing the fluid feedback force using a multi-harmonic fitting method to obtain a fluid force model; based on the fluid force model, obtaining the dominant frequency component of the fluid force and mapping it equivalently to an additional mass parameter and an equivalent damping parameter; then fitting the optimal functional form of the additional mass parameter and the equivalent damping parameter relative to the excitation acceleration; updating the coupled dynamic equations based on the optimal functional form to achieve dynamic characteristic analysis under different excitation acceleration conditions. This invention can accurately analyze the dynamic characteristics of an acoustic-frequency resonant hybrid system under high-acceleration vibration environments to address nonlinear dynamic problems induced by fluid-structure interaction.

This invention provides a method for coordinated control of vibration and noise in mine blasting, relating to the field of blasting control technology. The method includes: acquiring historical blasting data to train a vibration and noise response prediction model; using geological parameters of the area to be blasted as fixed inputs and blasting parameters as optimization variables, inputting the blasting parameters into the model to generate an energy field distribution, determining overlapping high-risk areas with a safety threshold as the boundary, and iteratively optimizing to generate the optimal blasting parameter set with minimizing its area; inputting this into a coupled response model, decomposing vibration and noise energy components through wave field separation and generating time history curves; extracting the dominant frequencies of vibration and noise to calculate a frequency domain matching index, calculating a time domain peak shifting index based on the peak time difference; if both indices satisfy the constraints, executing the blasting operation; otherwise, adjusting and iterating again, thereby achieving coordinated control of vibration and noise.

This invention discloses an intelligent physiotherapy control system and method based on multi-scenario, multi-element collaboration, relating to the field of physiotherapy technology. The method includes the following steps: performing short-time Fourier transforms on the driving waveform of the magnetotherapy module and the excitation waveform of the phototherapy module respectively, extracting the dominant frequency component, harmonic frequency band, and energy density parameters within each working cycle, and constructing a set of magnetic-optical dual-channel spectral feature vectors; based on the spectral feature vector set, calculating the relative frequency ratio and energy superposition ratio between the dominant frequency point of magnetotherapy and the dominant frequency point of phototherapy and their higher harmonics, obtaining a spectral coupling degree index. This invention achieves quantitative assessment of the risk intensity of magnetotherapy and phototherapy by constructing a joint resonance superposition degree, and dynamically adjusts the waveform timing based on this index. By delaying the rising edge and limiting the conduction time, it achieves peak-shifting control of energy output, effectively reducing instantaneous superposition density and improving physiotherapy safety and system adaptability.

This invention provides an adaptive cutoff frequency filtering method and apparatus for unsprung control, belonging to the field of automotive control technology. The method includes: determining a cutoff frequency based on the wheel's rotational fundamental frequency, the dominant frequency of vibration generated by road excitation, and the wheel's resonant frequency; establishing an initial upper cutoff frequency and a lower cutoff frequency; constructing a noise monitoring frequency band based on the cutoff frequency and preset pure noise setting frequency intervals and noise bandwidth; calculating the actual signal quality based on the theoretical target signal quality; determining the measurement deviation of the signal quality based on the cutoff frequency, the theoretical target signal quality, the total discretized signal power within the noise monitoring frequency band, the total discretized noise power within the noise monitoring frequency band, and the smoothing time constant; and determining the target upper cutoff frequency based on the measurement deviation, the theoretical target signal quality, and the actual signal quality, and performing cutoff frequency filtering based on the target upper and lower cutoff frequencies. This invention can solve the problem of poor consistency gains in unsprung control.

Systems and methods for simultaneously analyzing time-series and dominant frequency data from both a process domain and an electrical domain of a facility, such as an industrial plant, to detect instances of deviation from optimal, normal, or other predefined process conditions or electrical trips. Detecting when changes in frequencies occur in the time-series data creates a time-series of the changes in dominant frequencies. A data analysis server detects instances of deviation from the predefined process conditions or electrical trips by detecting one or more of correlations, patterns, clusters, and the like in the rates of change. The data analysis server employs one or more of statistical analyses, data mining, machine learning, deep neural networks, parallel coordinate analyses, etc. to identify the deviations and predict or detect onset of an undesired event such as a process perturbation or electrical trip.

The application discloses a fault determination method, device, equipment and medium. The method determines a first preset number of partial azimuth data bodies and a second preset number of partial frequency data bodies of a target block according to prestack common reflection point gathers and poststack seismic data of the target block; determines a dominant azimuth of a target layer in the target block according to a coherence attribute of each partial azimuth data body; determines a dominant frequency of the target layer according to a coherence attribute of each partial frequency data body; and determines whether the target layer is a fault according to the dominant azimuth and the dominant frequency. The technical scheme fully utilizes the prestack common reflection point gathers and the poststack seismic data of the target block to determine the dominant azimuth and the dominant frequency of the target layer, provides a reasonable and effective judgment criterion for fault identification, and improves the accuracy of fault identification.

This application discloses a method and device for early warning of sleep apnea in newborns, relating to the field of intelligent monitoring and pattern recognition technology. The method includes: acquiring initial audio data and real-time monitoring audio data of a newborn's sleep; performing feature analysis on the initial audio data to construct a standard breathing pattern, i.e., a dominant frequency signal, characterizing individual breathing features; dividing the real-time monitoring audio data into multiple time segments, calculating the pattern matching degree between each time segment and the standard breathing pattern to identify variations in the breathing waveform; and classifying and discriminating based on the matching degree to generate a risk warning signal for sleep apnea. This application achieves accurate identification and early warning of newborns' sleep breathing state by constructing personalized standard breathing patterns and using pattern matching algorithms to quantify the differences between real-time data and the standard pattern.

Computer-implemented method for estimating a respiratory rate of a subject, the method including acquiring a single-lead electrocardiographic signal from the subject, detecting R-peaks of the single-lead electrocardiographic signal, determining R-peak intervals from the R-peaks, extracting QRS complexes corresponding to the R-peaks based on the single-lead electrocardiographic signal, determining a time-domain sequence of root mean square amplitudes of the QRS complexes in a first window, the first window being in the time domain, generating, within a predetermined frequency range, a power spectrum of the sequence of root mean square amplitudes, determining a dominant frequency of the power spectrum, and estimating the respiratory rate of the subject based on the dominant frequency. Respirometry system employing same.

The application provides a kind of electrically conductive sponge electromagnetic leakage dynamic monitoring method and system, by utilizing the leakage feature recognition degree of auxiliary noise enhancement based on spectrum attenuation coefficient, and utilizing the set threshold value, a plurality of IMF components are obtained by ensemble empirical mode decomposition, for each IMF component, determine the dominant frequency point and phase retention band;While the phase is retained in the retention band, the out-of-band phase is randomized, the proxy data set is constructed and the confidence interval is established, so as to screen out the leakage feature component, by extracting the weighted hilbert energy with the energy proportion in the phase retention band as the weight, and the multiscale sample entropy with the total bandwidth as the scale factor, a joint feature vector is constructed, and the leakage is judged based on the mahalanobis distance of the vector and the normal state.

This invention discloses a method for detecting scale thickness on equalizing electrodes based on multidimensional features and deep learning. This method considers the noise distribution characteristics in the ultrasonic testing signal of the scale-equalizing electrode and proposes a VMD-WPT noise reduction method based on dominant frequency selection. Furthermore, it analyzes the ultrasonic testing signal from the perspectives of time-domain waveform, frequency-domain spectrum, time-frequency energy distribution, and spatiotemporal distribution to fully extract the scale thickness information contained in the signal. Based on the proposed features, a deep learning model for fusing recognition results is constructed using a CNN-RNN neural network, thereby enhancing the robustness and generalization ability of the model method and improving the accuracy and precision of scale thickness detection on equalizing electrodes.

The invention relates to the field of optical fiber sensing, and discloses an optical fiber sensing signal diagnosis method based on TimesNet two-dimensional time-frequency transformation, which comprises the following steps: S1, inputting an original signal, and carrying out adaptive time-frequency denoising through learnable wavelet packet transformation; s2, extracting a dominant frequency component based on the enhanced signal, and constructing a two-dimensional time-frequency tensor through zero padding and remodeling; s3, using depth separable convolution to extract features, using grouping convolution to capture local space-time coupling, using point-by-point convolution to fuse abnormal features, and combining a SimAM attention mechanism to enhance the weight of a key area; s4, modeling time sequence evolution through minLSTM, and realizing parallel long-range dependence modeling by adopting a logarithm domain correlation scanning algorithm; and S5, performing joint training through a gradient conflict coordination mechanism based on the shared features by using a multi-task output head, and outputting fault detection, type classification and positioning results at the same time. According to the method, two-dimensional orthogonal expression is constructed through physical prior dimension raising and noise reduction, and the signal-to-noise ratio, the feature interpretability and the diagnosis precision are remarkably improved.

This invention relates to the field of geological hazard identification technology and provides a method for identifying site liquefaction. The method includes: filtering collected seismic records based on surface acceleration in the horizontal direction; performing a Hilbert-Huang Transform (HHT) on the acceleration signals recorded in "time-acceleration" format to obtain the corresponding Hilbert time-frequency plot; and determining the dominant frequency time history curve and marginal spectrum based on the Hilbert time-frequency plot. Then, calculating the average dominant frequency decrease rate (MEFDr) based on the average dominant frequency (MEF) before and after the occurrence of peak ground acceleration; and determining the proportion of low frequencies (R) in the seismic record based on the marginal spectrum. L Finally, the possibility of liquefaction is determined by comprehensively considering the average dominant frequency decline rate and the proportion of low frequencies. Compared with the site liquefaction identification method in the current "Code for Seismic Design of Buildings" GB50011-2010 (2016), the identification method provided by this invention has the advantages of wide applicability, speed, and reliability.

This invention belongs to the field of ecological visual perception technology, specifically relating to a method and system for bird identification in complex dynamic background environments. The method includes: real-time monitoring of illuminance to drive low-level collaborative reconstruction using visible light and long-wave infrared sensors; expanding multi-source image sequences along the time axis into three-dimensional spatiotemporal data blocks, applying a Fast Fourier Transform to the temporal signal of each pixel to generate a dominant frequency feature map to remove broadband background noise; using the mean of infrared thermal radiation area and the variance of the dominant frequency local energy to jointly drive the neighborhood radius and minimum number of points of the DBSCAN algorithm to achieve adaptive density clustering; finally, confirming the target through morphological opening and closing operations and aspect ratio temporal verification, and linking a PTZ pan-tilt unit to complete close-up capture. This invention can effectively suppress false foregrounds in high-frequency dynamic backgrounds such as water surface ripples and swaying canopies, achieving highly stable extraction and continuous trajectory tracking of bird targets.