Product
Patsnap Eureka
For R&D, Patsnap Eureka makes reading and utilizing patents & technical documents easy.
Patsnap Eureka AIR
Designed for self-driven R&D workflows. Generate viable solutions, solve complex R&D challenges, empower your innovation with AI.
Patsnap Eureka Materials
Designed for material experts only. Revolutionize your material R&D, from search, analyze, to developing new materials.
Feature
TechResearch
Generate reliable direction feasibility study reports for your R&D in just a few steps.
TechSeek
Discover and master advanced knowledge NOW. Basics, ideas, possibilities, all at once.
TechMind
As an expert in R&D Theories, TechMind can generates customized viable solutions instantly.
TechRisk
Analyze your overall solution with one click, know your potential R&D risks in advance.
TechMonitor
Get weekly tech updates, stay abreast of the latest tech innovations and key insights.
Patents
Literature
Hiro is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
120 results about "Hilbert huang transformation" patented technology
Efficacy Topic
Property
Owner
Technical Advancement
Application Domain
Technology Topic
Technology Field Word
Patent Country/Region
Patent Type
Patent Status
Application Year
Inventor
Empirical mode decomposition for analyzing acoustical signals
InactiveUS6862558B2Signal is generatedAccurate signalAmplifier modifications to reduce noise influenceDigital computer detailsFrequency spectrumDecomposition
The present invention discloses a computer implemented signal analysis method through the Hilbert-Huang Transformation (HHT) for analyzing acoustical signals, which are assumed to be nonlinear and nonstationary. The Empirical Decomposition Method (EMD) and the Hilbert Spectral Analysis (HSA) are used to obtain the HHT. Essentially, the acoustical signal will be decomposed into the Intrinsic Mode Function Components (IMFs). Once the invention decomposes the acoustic signal into its constituting components, all operations such as analyzing, identifying, and removing unwanted signals can be performed on these components. Upon transforming the IMFs into Hilbert spectrum, the acoustical signal may be compared with other acoustical signals.
Owner:NAT AERONAUTICS & SPACE ADMINISTATION UNITED STATES GOVERNMENT AS REPRESENTED BY THE ADMINISTATOR OF THE
Method for precisely marking arriving time of initial wave of fault generated traveling waves for electricity transmission line
ActiveCN101291055ACalculation speedNo lossEmergency protective circuit arrangementsFault locationDecompositionOriginal data
The invention relates to a method for precisely calibrating the arrival moment of initial wave head of traveling wave in transmission line faults by utilizing Hilbert-Huang transformation (HHT). The method comprises the following steps that: HHT transformation is carried out to faulty traveling wave data; EMD decomposition is carried out first, and IMF1 component intensively embodies the high frequency information of raw data and completely self-adapts to the time scale of the raw data; the IMF1 component is taken as an investigation object; an order difference curve of the IMF1 component is evaluated, and Hilbert transformation is carried out to the order difference curve so as to obtain an instantaneous frequency curve of the IMF1 component; the advantages of two curves are combined to seek an extreme point, and the extreme point is compared with the raw data to obtain the precise calibration for the arrival moment of the head of a traveling wave, and error is controlled to be less than one sampling point. In a strong-noise environment, IMF2 or IMF3 is selected, and the precise calibration for the arrival moment of the head of the traveling wave can be achieved as well according to the method. All the other mathematical methods cannot achieve the precision of the method of the invention. Principle analysis, simulation data and engineering data verification show that the method is precise to calibrate the arrival moment of the initial wave head of the traveling wave in transmission line faults.
Owner:KUNMING UNIV OF SCI & TECH
Flutter online monitoring method for machining equipment
ActiveCN103786069AIntuitive imageAccurate judgmentMeasurement/indication equipmentsDiagnostic Radiology ModalityFrequency spectrum
The invention discloses a flutter online monitoring method for machining equipment. The method comprises the steps that a proper sampling window is selected; empirical mode decomposition is carried out on sampled vibration signals; decomposed eigen modalities are screened to obtain a characteristic eigen modality; Hilbert transformation is carried out on the characteristic eigen modality to obtain a time-frequency spectrum; statistical pattern analysis is carried out on the time-frequency spectrum to obtain characteristic parameters; the statistical characteristic parameters are compared with a set characteristic threshold value and the statistical characteristic parameter of a historical adjacent signal, and the vibration state of a system is judged. The flutter online monitoring method aims to solve the problems that a flutter detecting method is strong in sample dependency and poor in generalization ability, threshold value measurement is difficult, and judgment is not carried out in time, the method combining Hilbert-Huang transformation and statistical pattern recognition is provided, statistical modeling and clustering analysis are carried out on the time-frequency spectrum of the vibration signal based on the aggregation character of energy on frequency in the fluttering process, the characteristic parameters are utilized, the physical characteristic of cutting flutter is represented essentially, the cutting vibration state is effectively monitored in real time, and the judgment result is accurate and visual.
Owner:HUAZHONG UNIV OF SCI & TECH
Voltage sag source identification method based on Hilbert-Huang transformation and wavelet packet energy spectra
InactiveCN103424600AReduced ability to recognizeImprove recognition efficiencyCurrent/voltage measurementDecompositionElectric power system
The invention discloses a voltage sag source identification method based on Hilbert-Huang transformation and wavelet packet energy spectra, and belongs to the field of electric energy quality analysis of electric power system. The method includes the steps: firstly, performing EMD (empirical mode decomposition) for a three-phase voltage signal to obtain IMF (intrinsic mode function) components; secondly, performing n-layer wavelet packet decomposition for the IMF components to obtain energy spectra of frequency bands; thirdly, setting a larger wavelet packet coefficient of low-frequency band energy into zero, and reconstructing wavelet packet coefficients corresponding to other frequency bands to obtain an IMF without low-frequency illusive components; finally, performing Hilbert transformation on the IMF without the illusive components to obtain an HH (Hilbert-Huang) spectrogram, and identifying voltage sag sources according to catastrophe points, amplitudes, harmonic waves and frequencies of the HH spectrogram. Different characteristics of different voltage sag sources can be identified from the HH spectrogram only by taking the amplitudes, the catastrophe points and the harmonic waves as characteristics, the voltage sag sources are differentiated, so that times of non-identification and mistaken identification are effectively decreased, and identification efficiency is improved.
Owner:KUNMING UNIV OF SCI & TECH
Method and device for recognizing fault type of feed line of power distribution line
InactiveCN106226635AEasy to classifyClear logicElectrical testingBand-pass filterHilbert huang transformation
The invention discloses a method for recognizing the fault type of a feed line of a power distribution line, and the method comprises the steps: obtaining waveform sampling data, and sequentially carrying out the Hilbert-Huang transformation and band-pass filtering of the waveform sampling data; reconfiguring a time frequency matrix according to the band-pass filtering data, solving the singular value of the time frequency matrix, and forming feature vector matrixes; carrying out the normalization processing of all feature vector matrixes, and enabling the feature vector matrixes to serve as the input samples of a multi-stage support vector machine after normalization processing, so as to recognize the fault type of the feed line of the power distribution line. The invention also provides a device for recognizing the fault type of the feed line of the power distribution line. The multi-stage support vector machine is good in performance, is clear in logic, is simple, and can recognize four types of power grid faults: single-phase grounding faults, two-phase grounding faults, two-phase short-circuit faults and three-phase short-circuit faults. The method provided by the invention is stronger in adaptive capability, and still has a high recognition rate of fault types under the impact of noise.
Owner:STATE GRID FUJIAN JINJIANG POWER SUPPLY +1
Vibration signal processing method based on HHT (Hilbert-Huang Transformation) and related analyses
InactiveCN102506995AEfficient extractionCancel noiseSubsonic/sonic/ultrasonic wave measurementDecompositionHilbert huang transformation
A vibration signal processing method based on HHT (Hilbert-Huang Transformation) and related analyses includes steps as follows: using EMD (empirical mode decomposition) to decompose vibration signals; carrying out related analyses to each mode component obtained through decomposition; carrying out Hilbert transformation to denoised signals and obtaining a Hilbert spectrum. Aiming at the defect that noisy signals cannot be distinguished in signals if the HHT method is applied directly, the invention provides the method based on HHT and the related analyses, and denoises noisy signals. Through analyses on the Hilbert spectrum of the extracted noisy mode components and a marginal spectrum, the frequency and amplitude information of noisy vibration signals can be effectively extracted. The method can be used for processing signals of metallurgical machinery, aerospace, hydropower engineering, aeromancy and so on, and effectively remove noise.
Owner:CHINA BUILDING MATERIALS ACAD
Cavitation noise modulation feature extraction method based on empirical mode
The invention provides a cavitation noise modulation feature extraction method based on an empirical mode. The method comprises the following steps: firstly standardizing a short cavitation noise signal; carrying out bandpass filtering on the standardized signal to obtain the bandpass signal of cavitation noise; carrying out envelope detection on the bandpass signal to obtain an envelope signal; carrying out lowpass filtering on the envelope signal to obtain a low-frequency envelope signal; decomposing the low-frequency envelope signal into a plurality of intrinsic mode functions (IMFs) by using empirical mode decomposition analysis; selecting the optimum IMF through evaluation; carrying out Hilbert transformation on the optimum IMF to obtain a Hilbert spectrum of the optimum IMF; and calculating the instantaneous frequency at every moment by using the Hilbert spectrum, so as to complete cavitation noise modulation feature extraction. According to the method provided by the invention,based on the adaptability of empirical mode decomposition and high resolution of Hilbert-Huang transformation, the disadvantage of the traditional modulation feature extraction method that modulationfeature extraction is difficultly carried out on short-time and non-stably modulated cavitation noise data can be overcome.
Owner:SOUTHEAST UNIV
Vibration signal feature extraction method and device, storage medium and computer equipment
InactiveCN108229382ALimit frequency bandwidthOvercome Mode Aliasing PhenomenonCharacter and pattern recognitionFrequency spectrumFeature extraction
The invention relates to a vibration signal feature extraction method and device, a storage medium and computer equipment. The vibration signal feature extraction method comprises the following steps:collecting a vibration signal of target equipment; carrying out noise reduction on the vibration signal, so as to obtain a noise reduction signal; carrying out empirical mode decomposition on the noise reduction signal, so as to obtain an original intrinsic mode function corresponding to the noise reduction signal; acquiring a superposed signal according to the original intrinsic mode function corresponding to the noise reduction signal, and carrying out empirical mode decomposition and superposition removal on the superposed signal, so as to obtain a final intrinsic mode function corresponding to the noise reduction signal; and carrying out Hilbert-Huang transformation on the final intrinsic mode function, so as to obtain a spectrum signature of the vibration signal. According to the vibration signal feature extraction method, the feature extraction accuracy can be increased, and extracted features can well represent the operation states of the target equipment.
Owner:GUANGZHOU POWER SUPPLY BUREAU GUANGDONG POWER GRID CO LTD
Current transformer (CT) saturation detection method based on Hilbert-Huang transformation (HHT)
InactiveCN103050942AImprove reliabilityImprove efficiencyEmergency protective circuit arrangementsFault locationFrequency spectrumSignal on
The invention discloses a current transformer (CT) saturation detection method based on Hilbert-Huang transformation (HHT), and the method comprises the followings steps that instantaneous frequency spectrum, Hilbert spectrum and Hilbert marginal spectrum are obtained through EMD decomposition and Hilbert diversion by collecting differential current signals on both sides of a transformer; the detection of saturation faults and CT saturation outside a transformer area is completed respectively arranged to the three types of spectrum so as to realize the quick action and the reliable action of differential protection under CT saturation; the method serves as a preferential improvement to a traditional CT saturation detection method and combines instantaneous frequency criteria, Hilbert spectrum criteria and Hilbert marginal spectrum criteria in the forms of 'and' and 'or'; when a judgment result has errors, another method can correctly judge, so that the reliability of differential protection is improved; and in addition, fault current outside the transformer area, fault current in the area, conversion fault current and the like under the two circumstances of CT saturation and unsaturation are fully considered, and the CT saturation detection method based on HHT has the advantages of stronger functions, higher efficiency, higher reliability and the like.
Owner:SHANDONG UNIV OF SCI & TECH
Method for diagnosing commutation failure of extra-high-voltage DC power transmission system
ActiveCN105116208ASolve the problem of judging bit commutation failureAccurate extractionCurrent/voltage measurementElectrical testingHilbert huang transformationEngineering
The invention relates to a method for diagnosing a commutation failure of an extra-high-voltage (EHV) DC power transmission system and belongs to the technical field of HVDC power transmission system fault diagnosis. The method comprises steps of: performing hierarchical reconstruction on an extracted DC current signal sequence; denoising the DC current signal sequence, filtering the DC current signal sequence with a morphological filter, and extracting the high-frequency components of the DC current signal sequence; performing Hilbert-Huang transformation on the high-frequency components, solving the instantaneous frequency maximum value f and the instantaneous frequency amplitude mean value A of an intrinsic mode function, setting a frequency threshold value f0 and a amplitude average threshold value A0, determining that the system is faulted if the f is more than or equal to f0 or that the system operates normally if not; and if the system is faulted, determining whether the A is more than or equal to A0, and determining that a line is subjected to a short-circuit fault if yes or that the system is subjected to commutation failure if not. The method may accurately determine the running state, the commutation failure, and the line short-circuit fault of the EHV DC power transmission system.
Owner:KUNMING UNIV OF SCI & TECH
Integrated learning based mountain wind generation set behavior predicating model
ActiveCN110685857AHigh precisionImprove accuracyWind motor controlEngine fuctionsLearning basedAlgorithm
The invention discloses an integrated learning based mountain wind generation set behavior predicating model which comprises the following steps: 1, adopting a self-adaptive threshold value method todetermine a wind speed power sub-interval data density threshold value to clear abnormal data; 2, defining a sample matrix, and adopting a self-adaptive comprehensive over-sampling method to generatea new sample matrix for uniformly distributing different wind conditions; 3, performing Hilbert-Huang transform on data generated in the step 2 to obtain decomposition amount of input amount of the mountain wind generator set model; 4, according to the data of the step 4, determining input and output of the mountain wind generator set model, selecting a component learner and adopting a fusion strategy of integrated learning of stacking, and training and integrating to obtain the mountain wind generation set behavior predicating model; 5, adopting a grid search method to determine optimal parameters of the model; and 6, operating and testing the mountain wind generation set behavior predicating model. The integrated learning based mountain wind generation set behavior predicating model canprovide service for wind generation set predicating control, so that maintenance staff can normally operate a maintaining unit more efficiently better.
Owner:XIANGTAN UNIV
Real-time detection method for high-speed rail injury based on vibration and audio composite signals
InactiveCN103808801AGuaranteed safe operationEasy accessAnalysing solids using sonic/ultrasonic/infrasonic wavesNonnegative tensor factorizationHilbert huang transformation
The invention discloses a real-time detection method for a high-speed rail injury based on vibration and audio composite signals. The method comprises the following steps: 1, installing a vibrating and acoustic sensor on a high-speed rail, forming a wireless sensor network by combining with a wireless node processor, and measuring a vibration signal and an audio signal of the rail in real time; 2, building a rail vibration model and an acoustic model by adopting a finite element method according to the actual structure of the rail, so as to obtain classic vibration and audio signals of the rail injury; 3, carrying out pretreatment on the signal by adopting Hilbert-Huang transformation; 4, building three-dimensional tensors of vibration, audio and injury varieties by fusing vibration and acoustic signals; 5, decomposing and extracting the injury variety feature coefficient by using a nonnegative tensor; 6, building an injury identification rule by using a related vector machine, and classifying real-time measurement signals, so as to determine the injury variety. By adopting the real-time detection method, real-time detection for the high-speed rail injury is achieved, and safe operation of the high-speed rail is ensured.
Owner:HARBIN INST OF TECH
Ship classification method based on vibration noise identification
PendingCN111488801ARealize underwater identificationAchieving covert detectionCharacter and pattern recognitionTime domainHilbert huang transformation
The invention discloses a ship classification method based on vibration noise identification, and the method comprises the following steps: 1, collecting ship vibration noise, and converting the shipvibration noise into a time domain signal; 2, performing improved ensemble empirical mode decomposition on the ship vibration signals; 3, performing Hilbert-Huang transform on the signal after modal decomposition; 4, performing Hilbert spectrum analysis on ship radiation noise; 5, extracting ship noise characteristics; 6, classifying the ship noise characteristics by using a ship classifier basedon a support vector machine; 7, verifying the accuracy of the ship classification result, and if the result is correct, ending ship classification; and if not, entering the ship classifier for re-classification. The ship classification method based on vibration noise identification is realized, and a new way for marine traffic management personnel, scientific research personnel and military personnel to acquire ship types is provided.
Owner:TIANJIN UNIV
Subsynchronous oscillation random time-varying mode identification method
InactiveCN108845230AExact fitExact endpoint effectFault locationHilbert huang transformationMirror image
The invention discloses a subsynchronous oscillation random time-varying mode identification method. Aiming at the problem that an error of mode identification result is relatively large due to an end effect, an improved Hilbert-Huang transformation based on a mirror image extension method is proposed to identify a random time-varying subsynchronous oscillation mode, first, symmetry points are determined at left and right ends of a signal, the signal is then extended, fitting of envelope lines adopts extreme points after extension as interpolation points to perform cubic spline interpolation,and then the local mean of the upper and lower envelope lines is calculated, so that the fitting of the upper and lower envelope lines is more accurate, the end effect is notably improved, and the feasibility and effectiveness of the method are verified by the identification of stable signals, non-stable signals and measured signals.
Owner:STATE GRID SHAANXI ELECTRIC POWER RES INST +1
Space debris hyperspectral sequence detection method based on Hilbert-Huang transform
The invention relates to a space debris hyperspectral sequence detection method based on Hilbert-Huang transform, which belongs to the field of image processing and aims at solving the problems that the adoption of the traditional dangerous space debris detection method has to depend on sample information of an image about space debris, and the algorithm adaptability is poor, and the method comprises the following steps: 1) continuously sampling hyperspectral curves in the central position of a suspected target for T times, and processing and synthesizing the obtained T sections of the hyperspectral curves into the curve to be processed; 2) carrying out one-dimensional empirical mode decomposition and obtaining two intrinsic mode function components; 3) carrying out Hilbert transform on a two-order IMF component and obtaining the amplitude and the instantaneous frequency; 4) retaining the part which is higher than average value by one half of the amplitude, retaining the part which is higher than the average value of the instantaneous frequency, and dividing for forming a characteristics wave band set; and 5) cyclically searching the characteristic wave band set, judging whether the target rotates or not, if so, the suspected target can be determined to be the space debris, if not, the suspected target can be determined not to be the space debris.
Owner:HARBIN INST OF TECH
Radiation source signal identification method combining two-domain multi-features
ActiveCN111160171AImproved nonlinear time-frequency featuresGood time-frequency resolutionCharacter and pattern recognitionNeural architecturesHilbert huang transformationComputational physics
The invention belongs to the field of information detection, and particularly relates to a two-domain multi-feature combined radiation source signal identification method, which comprises the following steps of: performing short-time Fourier transform, improved Wigner time-frequency distribution transform and Hilbert-Huang transform on a radiation source signal to obtain three time-frequency feature images; respectively extracting Green single-channel images of the three time-frequency characteristic images, and carrying out channel fusion on the three Green single-channel images to obtain a new characteristic image. According to the invention, a new three-dimensional time-frequency image is obtained by adopting a multi-time-frequency image channel fusion means. The short-time Fourier transform reflects the linear time-frequency characteristic of the signal; the improved Wigner distribution reflects the nonlinear time-frequency characteristics of signals, Hilbert-Huang transform is notrestricted by the Hessian Bourger measurement inaccuracy principle, a good time-frequency resolution is achieved, a new three-dimensional time-frequency image obtained through channel fusion can represent time-frequency information of the signals more comprehensively, and the reliability of the system is improved.
Owner:HARBIN ENG UNIV
Device and method for identifying fluid type of high-pressure fluid in pipeline during rapid pressure change
InactiveCN102620905APrevent leakageQuick changeHydrodynamic testingCharacteristic spaceHilbert huang transformation
The invention discloses a method and device for identifying a fluid type of a high-pressure fluid in a pipeline during rapid pressure change, belonging to the field of fluid type identification. The device mainly comprises an incoming fluid pipeline, a fixed baffle, an incoming fluid pipeline joint, an incoming fluid sensor three-way joint, a high-pressure resistant quartz transparent tube, an outgoing fluid sensor three-way joint, an outgoing fluid pipeline joint, an outgoing fluid pipeline, an adjusting sleeve, an adjusting bolt with a through hole, an incoming fluid pressure sensor, an incoming fluid pressure transmitter, an outgoing fluid pressure sensor, an outgoing fluid pressure transmitter, a computer, a light source and a high-speed video camera. The pipeline is sealed by adjusting the screwing length of the adjusting sleeve and the adjusting bolt with the through hole. The method comprises the steps of: performing Hilbert-Huang transformation on pressure differential data to obtain each modulus energy ratio; then regarding each modulus energy ratio as input vectors of an Elman neural network to finish mapping from a characteristic space to a fluid type space. The method and device for identifying the fluid type of the high-pressure fluid in the pipeline during the rapid pressure change, disclosed by the invention, has advantages of simple structure, convenience in detachment and capability of identifying fluid type of high-pressure fluid in the pipeline rapidly and exactly during the rapid pressure change.
Owner:CHINA JILIANG UNIV
Air valve fault diagnosis method based on HHT and neural network
InactiveCN107908812AMachine part testingDesign optimisation/simulationSingular value decompositionFeature vector
The invention discloses a compressor air valve fault diagnosis method based on HHT (Hilbert-Huang Transformation) and an RBF (radial basis function) neural network. Based on preprocessing of a vibration signal through interceptive matrix singular value decomposition, HHT is utilized to perform decomposition and time-frequency analysis on the signal, and then the RBF network is utilized to train and recognize fault sample features. The method comprises the steps that 1, interceptive matrix singular value decomposition is utilized to perform denoising preprocessing on vibration signals generatedwhen an air valve is in a normal state and in a fault state; 2, an HHT algorithm is utilized to obtain EMD (Empirical Mode Decomposition) results and Hilbert marginal spectra under various states after denoising; 3, based on the EMD results and the Hilbert marginal spectra, feature vectors of the air valve under all the operating states are extracted, and normalization processing is performed; and 4, the RBF network is utilized to train feature samples under all the states. Test samples are recognized, and the effectiveness of the method on air valve fault diagnosis is verified.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
Parameter estimation method for artificial circuit fault component based on Hilbert-Huang transforming (HHT)
ActiveCN103064010ASuitable for practical engineering applicationsLow estimation accuracyAnalog circuit testingMarginal spectrumEstimation methods
The invention discloses a parameter estimation method for an artificial circuit fault component based on Hilbert-Huang transforming (HHT). The premise of the parameter estimation method for the artificial circuit fault component based on HHT is that a single fault component is already located, a sinusoidal excitation signal is applied on a circuit to be detected, and the output end of the circuit is used as a test point. First of all the relation of the parameters of the component and the Hilbert marginal spectrum total energy of a corresponding output signal is acquired through computer simulation, a relation curve equation is fitted, and the parameter estimation equation of the fault component of an actual circuit can be acquired after errors are compensated. The test point signals acquired by actual measurement are analyzed and calculated through the HHT to acquire the corresponding total Hilbert marginal spectrum energy, and the total Hilbert marginal spectrum energy is substituted into the parameter estimation equation to solve to gain the parameter values. The parameter estimation method for an artificial circuit fault component based on HHT is simple and effective, and is suitable for linear artificial circuits and non-linear artificial circuits, the estimated accuracy of the parameters is up to 95%, and only one accessible test node is needed, and therefore the parameter estimation method for an artificial circuit fault component based on HHT is suitable for practical engineering application.
Owner:ZHEJIANG UNIV
Method and system for locating single-phase grounding fault of distribution network
InactiveCN108051705ARapid positioningFault location by conductor typesSimulationHilbert huang transformation
The invention provides a method and a system for locating a single-phase grounding fault of a distribution network. The method includes the following steps: obtaining a voltage traveling wave, and carrying out Karenbauer transformation on the voltage traveling wave to obtain an aerial mode component and a zero mode component; carrying out Hilbert-Huang transformation on the aerial mode component and the zero mode component to obtain the time of arrival of the initial wave front; determining the fault area according to the voltage traveling wave; if the fault occurs in a single-phase distribution branch, obtaining a first time difference according to the time of arrival of the initial wave front; if the fault occurs in a three-phase line, obtaining a second time difference according to thetime of arrival of the initial wave front; and obtaining a first fault distance and a second fault distance according to the first time difference and the second time difference respectively. A faultof a single-phase distribution branch can be located quickly.
Owner:NORTH CHINA ELECTRIC POWER UNIV (BAODING)
Spectrum signal denoising method based on Hilbert-Huang transformation
The invention relates to a spectrum signal denoising method based on Hilbert-Huang transformation. The method mainly comprises the steps of performing empirical mode decomposition on an original spectrum signal to obtain a series of IMF (intrinsic mode function) components; performing Hilbert transformation on each IMF component to obtain the instant frequency corresponding to each IMF; calculating the average value of the instant frequencies, and adopting t inspection to determine the boundary point k of a signal region and a noise region; finally performing adduction reconstruction on the IMF after the k to obtain a denoised spectrum signal. The method provided by the invention has the advantages that the parameter setting is not needed; the signal can be denoised in a complete self-adaption way; the denoising effect on nonlinear and non-stable spectrum signals is good. The spectrum signal denoising method is applicable to the denoising of complicated substance spectrum signals of petroleum, tobacco, traditional Chinese medicine, food and the like.
Owner:四川安好众泰科技有限公司
OPGW lightning strike site polarization state waveform signal processing method
InactiveCN109270346APresent comprehensively and accuratelyPrecise positioningSpectral/fourier analysisLight polarisation measurementLightning strikeWavelet denoising
The invention discloses an OPGW lightning strike site polarization state waveform signal processing method. According to the method, a polarization demodulation device is adopted to acquire OPGW lightning strike site polarization state signals, and a wavelet denoising method is adopted to perform denoising preprocessing on sampling signals, so that wavelet denoised polarization state signals x(t)can be obtained; EMD decomposition is performed on the signals x(t), an equation described in the descriptions in the invention is obtained, rn in the equation is called a residual function, and ci inthe equation is the i-th component of the signals x(t) that satisfies an IMF condition; HHT (Hilbert-Huang) transformation is performed on each intrinsic mode function ci(t) of the polarization statesignals, and then analytical signals are constructed, and a lightning strike point can be accurately located on the basis of optical polarization state signals extracted by the final Hilbert-Huang transformation; and therefore, the problem of low accuracy of the analysis and processing of optical polarization state signals in an OPGW in the prior art can be solved, and the problem of inaccurate fault location caused by the low accuracy, and other problems can be also solved.
Owner:GUIZHOU POWER GRID CO LTD
Voice processing method used for electrical cochlea
InactiveCN103393484AKeep basic featuresAdaptableEar treatmentSpeech analysisHilbert huang transformationChannel modulation
The invention discloses a voice processing method used for an electrical cochlea. The voice processing method used for the electrical cochlea comprises the steps of pre-processing, namely carrying out pre-processing on a voice signal input through a microphone; Hilbert-Huang transformation, namely carrying out Hilbert-Huang transformation on the pre-processed voice signal to obtain Hilbert-Huang transformation signals of multiple channels; modulation, namely processing the Hilbert-Huang transformation signal of each channel to obtain an amplitude signal and a frequency signal which correspond to the Hilbert-Huang transformation signal of the channel, modulating a biphase pulse by means of the frequency signal corresponding to the Hilbert-Huang transformation signal of each channel to obtain a biphase pulse modulation frequency signal corresponding to the Hilbert-Huang transformation signal of the channel, and modulating the biphase pulse modulation frequency signal corresponding to the Hilbert-Huang transformation signal of each channel by means of the amplitude signal corresponding to the Hilbert-Huang transformation signal of the channel to obtain a channel modulation signal used for driving an electrode corresponding to the channel.
Owner:刘洪运
Motor abnormal noise detection method based on Hilbert-Huang transformation
ActiveCN108447503AProtect your healthIncrease productivitySpeech analysisMachine learningNoise detectionHilbert huang transformation
The invention discloses a motor abnormal noise detection method based on Hilbert-Huang transformation, and the method comprises the six steps. The method can assist a worker to recognize the abnormalnoise of a motor, improves the detection efficiency, guarantees the delivery quality of a product, improves the overall production efficiency of an enterprise, reduces the manufacturing cost of the enterprise, and protects the health of the worker. The method can effectively solve a problem of an unsteady state of an audio signal of the motor, effectively detects the abnormal noise fault of an unsteady state motor, and is high in recognition accuracy.
Owner:SHANDONG IND TECH RES INST OF ZHEJIANG UNIV
Rapid imaging method for ultra-wide band microwave detection based on Hilbert-huang transformation
InactiveCN103799982AImprove the display effectDiagnostic recording/measuringSensorsRapid imagingTumor response
The invention relates to ultra-wide band microwave imaging, ultra-wide band wireless detection, biomedical detection equipment and microwave detection, and in particular to a rapid imaging method for ultra-wide band microwave detection based on Hilbert-huang transformation. According to the method, biological information can be displayed simply, conveniently, rapidly and obviously. According to the technical scheme, the rapid imaging method includes the following steps that an antenna Ai is used for emitting ultra-wide band microwave signals, and other antennas are used for receiving reflecting signals from the inner portion of one breast so as to obtain signals containing tumor information and signals containing no tumor information; tumor response signals are obtained by subtracting the signals containing no tumor information from the signals containing the tumor information, Hilbert transform is conducted on all the obtained tumor response signals, the signals are constructed into analytical signals, and then the instantaneous amplitude of the signals is obtained; for a breast area, scanning is conducted on each point in an imaging area through a confocal imaging method, and the position and size information of a tumor is obtained clearly. The rapid imaging method is mainly used for designing and manufacturing medical apparatuses and instruments.
Owner:TIANJIN UNIV
Water turbine running state identification method
ActiveCN111259864AProminent featuresImprove decomposition abilityHydro energy generationCharacter and pattern recognitionWater turbineControl engineering
Owner:HARBIN UNIV OF SCI & TECH
Air radiation source individual intelligent increment identification method, system, terminal and application
PendingCN112668498AReduce dependenceSave spaceCharacter and pattern recognitionNeural architecturesHilbert huang transformationEngineering
The invention belongs to the technical field of radiation source individual identification, and discloses an air radiation source individual intelligent increment identification method, system, terminal and application. Four features of fuzzy function, bispectrum transformation, Hilbert-Huang transformation and short-time Fourier transformation are extracted from received air radiation source ADS-B (broadcast type automatic dependent surveillance) signals respectively; performing linear feature fusion on the features to obtain a new feature map; and classifying and identifying the radiation source individuals of known types through a convolutional neural network to obtain a network model. For untrained category data, an incremental learning mode is adopted for training, and intelligent incremental recognition of aerial radiation source individuals is achieved. According to the method, good recognition accuracy can be achieved under the low signal-to-noise ratio, good recognition capacity can still be achieved under different channels, dependence on a certain single feature is not high, the problem that training data arrives in batches is solved, the time needed by training is greatly shortened, and the space needed by data storage is reduced.
Owner:XIDIAN UNIV
Sound enhancement method and sound enhancement system
ActiveCN111107478AOvercoming misperceptionsImprove claritySpeech amplifier applicationsHearing aids signal processingHilbert huang transformationLetter to sound
The invention discloses a sound enhancement method and a sound enhancement system. The method comprises the following steps: obtaining a sound signal, and converting the sound signal into a digital signal; decomposing the digital signal to obtain a plurality of intrinsic mode functions or a plurality of similar intrinsic mode functions; selectively amplifying the amplitudes of the plurality of obtained intrinsic mode functions or the plurality of similar intrinsic mode functions; integrating the selectively amplified intrinsic mode functions or similar intrinsic mode functions to obtain an integrated reconstruction signal; and converting the integrated reconstructed signal into an analog signal. Based on Hilbert-Huang transform, sound can be effectively and selectively enhanced, only high-frequency consonants in the sound are amplified instead of amplifying vowels, the method can effectively improve the sharpness of the amplified sound, and the problem that only the loudness of the sound is increased but the sharpness is not increased in an existing sound enhancement method is solved.
Owner:南京生物医药谷建设发展有限公司
Manifold learning and Hilbert-Huang transformation combined structural modal parameter identification method
PendingCN108614926AHigh precisionHigh mode shapeDesign optimisation/simulationSpecial data processing applicationsHilbert huang transformationCombined method
The invention discloses a manifold learning and Hilbert-Huang transformation combined structural modal parameter identification method. The method comprises the following steps of: 1, acquiring time domain response data of a measure point in a structure; 2, processing the time domain response data acquired in the step 1 by adoption of a manifold learning algorithm so as to obtain a vibration modeand a fixed frequency of the structure; and 3, processing the time domain response data acquired in the step 1 by adoption of a Hilbert-Huang transformation method so as to obtain a damping ratio of the structure. Compared with the prior art, the method has the beneficial effects as follows: 1, when modal parameter extraction is carried out by utilizing the manifold learning and Hilbert-Huang transformation combined method, vibration modes, fixed frequencies and damping ratios with relatively high precision can be obtained through response data when material parameters and experiment conditions of structures are unknown; and 2, the method can be used for processing nonlinear data and retaining nonlinear manifolds of the structures.
Owner:XI AN JIAOTONG UNIV
Single-phase half-bridge five-level inverter switching tube open-circuit fault diagnosis method
ActiveCN112710969AImprove accuracyCharacter and pattern recognitionCAD circuit designHilbert huang transformationNeural network nn
The invention discloses a single-phase half-bridge five-level inverter switching tube open-circuit fault diagnosis method, which belongs to the field of power electronic circuit fault diagnosis, and comprises the steps of building a semi-physical experiment platform taking a DSP controller and an RT-LAB real-time simulator as cores, and selecting an output side voltage as a fault signal variable, extracting a fault feature vector by using empirical mode decomposition, extracting a Hilbert-Huang transform time-frequency diagram of the fault feature vector, and converting the voltage signal into diagram data to obtain time-frequency diagram fuzzy sets corresponding to different fault types, fusing the time-frequency diagram fuzzy sets of the same fault type to obtain a fused image retaining more fault features, and inputting the fused images corresponding to all the fault types into a deep convolutional neural network for training and testing to obtain a fault diagnosis result. The method can improve the accuracy and stability of single-phase half-bridge five-level inverter fault diagnosis, and can be extensively applied to fault diagnosis of other power electronic equipment.
Owner:WUHAN UNIV
Who we serve
- R&D Engineer
- R&D Manager
- IP Professional
Why Patsnap Eureka
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com