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77 results about "Generalized s transform" patented technology
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Seismic wave absorption and attenuation compensation method
ActiveCN102109612AImprove signal-to-noise ratioHigh resolutionSeismic signal processingFrequency spectrumCurve fitting
The invention relates to a seismic wave absorption and attenuation compensation method, and belongs to the geophysical exploration data processing technology. The method comprises the following steps: selecting one of VSP (vertical seismic profiling) initial data as reference data, carrying out generalized S-transform on the reference data, selecting sampling points as reference points, and recording the time and time-frequency spectrums of the sampling points; carrying out generalized S-transform on data of each sampling point, and dividing the time-frequency spectrum of corresponding frequency in the time-frequency spectrums of the reference points by the time-frequency spectrum of each sampling point so as to obtain an absorption and attenuation curve; determining a natural logarithm to figure out a phase compensation operator according to a formula of frequency difference of absorption and attenuation signals in a time frequency domain; and carrying out absorption and attenuation compensation and phase compensation in the time frequency domain to obtain a fine VSP wave field profile. The method has the advantages that noise can be eliminated during the process of fitting the absorption and attenuation curve; generalized S-inverse transform without energy loss is realized; signal-to-noise ratio and resolution of the data are improved after compensation; log resolution control is realized; the reference points are selected flexibly; and algorithm is simple and efficient.
Owner:BC P INC CHINA NAT PETROLEUM CORP +1
Fault diagnosis method of variable-speed rotation machine based on time-frequency spectrum segmentation
ActiveCN108106830AQuick TroubleshootingFilter out strong background noiseMachine part testingFrequency spectrumTime frequency spectrum
The invention provides a fault diagnosis method of a variable-speed rotation machine based on time-frequency spectrum segmentation. The method includes following steps: step 1, obtaining normalized time-frequency spectrums of signals through multi-resolution generalized S transform, and generating multi-resolution binarized time frequency spectrums; step 2, combining the binarized time-frequency spectrums with all resolutions, and obtaining an optimal binarized time-frequency spectrum; step 3, segmenting the optimal binarized time-frequency spectrum into a plurality of connected domains, and performing information annotation on each connected domain; step 4, extracting an optimal expression atom of each connected domain, forming an optimal atom set, and calculating the expression of a fault signal in the optimal atom set; and step 5, calculating the appearance time and amplitude of an impact theory, and realizing fault diagnosis of variable-sped mechanical equipment through informationcomparison. According to the method, most strong background noises can be filtered, and fault diagnosis of impact type faults including cracking, pitting corrosion or spalling etc. of the variable-speed rotation machine can be realized.
Owner:WUHAN UNIV OF SCI & TECH +1
Method for determining stratum stack quality factor by direct scanning of prestack time migration
InactiveCN102305941AImprove signal-to-noise ratioAccurate portrayalSeismic signal processingFrequency spectrumGeneralized s transform
The invention relates to a method for determining a stratum stack quality factor by direct scanning of prestack time migration. By modeling methods for defining an equivalent stack quality factor, developing and utilizing prestack reflection seismic data and scanning and inversely demonstrating the stratum stack quality factor, a series of constant-Q and inverse-Q filtering is selected and combined with the prestack time migration to high-efficiently compensate ground reflection data and acquire a common reflection point set; generalized S transform is used for accurately solving an instantaneous frequency spectrum of a stack channel; the minimum average derivative after a logarithmic spectrum is used as an automatic selection standard of a correct stack Q value, so rapid and automatic inverse demonstration and analysis of a stratum stack Q value is realized; and a method for inversely demonstrating and analyzing the stack Q value of the common reflection point set based on viscous compensation migration is established. The method is applied to reflection seismic data processing in seismic exploration, is used for providing important input parameters for high-resolution seismic imaging, and has important application value in exploration of deep concealed oil and gas and mineral resources in China.
Owner:NORTHEAST GASOLINEEUM UNIV
Seismic spectrum imaging method based on deconvolution generalized S transform
InactiveCN106405654AImprove forecast accuracyAdaptableSeismic signal processingSeismology for water-loggingFrequency spectrumGeneralized s transform
The invention discloses a seismic spectrum imaging method based on deconvolution generalized S transform, which comprises the steps that a generalized S transform spectrum is acquired by performing two-dimensional convolution on Wigner distribution of original signals and a Gaussian window, a transform spectrum is acquired by performing generalized S transform on seismic data, and time-frequency distribution of the original signal can be acquired through deconvolution when the generalized S transform spectrum and the Wigner distribution of a window function are known. The seismic spectrum imaging method combines advantages of generalized S transform and Wigner-Ville distribution, generation of a cross term of the Wigner-Ville distribution is effectively suppressed through a generalized S transform window, and the generalized S transform spectrum is enabled to acquire high time-frequency aggregation at the same time; and deconvolution generalized S transform can adaptively adjust an analysis window along with variations of a frequency component, is applicable to time-frequency analysis for unstable seismic data, and can acquire high time-frequency resolution; and the seismic spectrum imaging method is applied to detecting the oil-gas possibility of a reservoir, thereby being conducive to improving the reservoir prediction accuracy.
Owner:CHENGDU UNIVERSITY OF TECHNOLOGY
Weak target detecting method based on generalized S-transform
InactiveCN101493934AImprove object detection performanceImage analysisImaging processingDimensionality reduction
The invention relates to a weak object detection method on the basis of generalized S transformation, which pertains to the field of image processing, in particular to a weak object detection method by applying the two-dimensional generalized S transformation of an image. The method carries out two-dimensional generalized S transformation to the original image I (x', y') at first to obtain a generalized S transformation result S (x, y, kx, ky); then detection is carried out to a weak object in the image according to the generalized S transformation result S (x, y, kx, ky); by fixing the value of spatial frequency kx or ky, a four-dimensional S transformation result S (x, y, kx, ky) is reduced into three-dimensional data; and the combination of frequency component power of a vertical section image (y, ky) or (x, kx) corresponding to each value selected along x or y direction is compared with a threshold value so as to determine the positions of row and line of the weak object in the original image. The method carries out generalized S transformation to the original image; on basis of the generalized S transformation result, by dimension reduction and visualization processing, the information of the S transformation domain is utilized to detect the weak object, thus being capable of effectively overcoming the influences by obstruction factors such as noise, flooding wave, cloud, and the like, in the spatial domain.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
High-precision synchronous extraction generalized S transform time frequency analysis method
InactiveCN108694392AHigh time-frequency resolution accuracyEasy to understandCharacter and pattern recognitionComplex mathematical operationsFrequency spectrumImage resolution
The invention discloses a high-precision synchronous extraction generalized S transform time frequency analysis method. The method comprises the steps of firstly performing generalized S transform ona signal to obtain a generalized S transform value, thereby obtaining a time frequency spectrum of the generalized S transform; based on the generalized S transform value, calculating an instantaneousfrequency, obtaining a synchronous extraction operator (SEO) according to the instantaneous frequency, extracting the time frequency spectrum of the generalized S transform by utilizing the SEO, onlyreserving energy near a time frequency ridge line in a time frequency plane, removing all other divergent energy, and obtaining a synchronous extraction generalized S transform value; and finally converting the synchronous extraction generalized S transform value into a time frequency spectrum of synchronous extraction generalized S transform. The size of a window function can be flexibly adjusted according to the actual need; the method has higher time frequency decomposition precision and relatively high flexibility; and the time and frequency resolution of the signal is greatly increased.
Owner:CHENGDU UNIVERSITY OF TECHNOLOGY
Motor bearing fault diagnosis method based on generalized S transformation and WOA-SVM
ActiveCN112036296AImprove search accuracyFlexible adjustmentMachine part testingCharacter and pattern recognitionTime–frequency analysisEngineering
The invention relates to a motor bearing fault diagnosis method based on generalized S transformation and WOA-SVM, and the method comprises the steps: inputting a motor bearing vibration signal, and obtaining two time-frequency matrixes after two times of different generalized S transformation; respectively obtaining a time domain cumulative characteristic curve with high time resolution and a frequency domain cumulative characteristic curve with high frequency resolution; obtaining a time domain feature and a frequency domain feature of the original signal; combining the time domain featuresand the frequency domain features to form a feature vector sample set, and dividing the feature vector sample set into training samples and test samples; inputting the training sample into a support vector machine optimized by a whale optimization algorithm WOA, and training a classifier; and inputting the test sample into the trained classifier WOA-SVM for testing, and outputting a fault diagnosis type. The method overcomes the defect that the Gaussian window function of S transformation cannot be adjusted along with the frequency and lacks flexibility, has better time-frequency analysis capability, and is more suitable for processing complex non-stationary and non-linear bearing vibration signals.
Owner:HEFEI UNIV OF TECH
Stratum oil-gas possibility prediction method with high time resolution
ActiveCN102692647AImprove time resolutionImprove computing efficiencySeismic signal processingLow frequency bandGeneralized s transform
The present invention provides a stratum oil-gas possibility prediction method with a high time resolution. By utilizing improved generalized S transform, a Gauss window function with a time window width in directly proportional change with frequency f is employed, the time window is narrow at a low frequency band, the high time resolution is obtained, and seismic wave low frequency absorption attenuation gradient is calculated; at the same time, by using generalized S transform, a Gauss window function with a time window width in inversely proportional change with the frequency f is employed, the time window is narrow at a high frequency band, the high time resolution is obtained, high frequency absorption attenuation gradient is calculated, and the low frequency absorption attenuation gradient and the high frequency absorption attenuation gradient are utilized comprehensively. The method has better time resolution at a low frequency band, an influence of high frequency interference is avoided, at the same time, the method has better time resolution at a high frequency band, an influence of low frequency interference is avoided, oil and gas prediction time resolution is raised greatly, an algorithm is simple, and computational efficiency is high.
Owner:BC P INC CHINA NAT PETROLEUM CORP +1
Sparse feature extraction method for fault signal of rotating machine
ActiveCN107992843AImprove extraction accuracyReduce complexityCharacter and pattern recognitionFrequency spectrumFeature extraction
The invention provides a sparse feature extraction method for a fault signal of a rotating machine. The method includes the steps of constructing a fault overcomplete atom library according to a faultgeneration mechanism of an impact fault of the rotating machine; calculating a multi-resolution time-frequency spectrum of a to-be-analyzed signal through multi-resolution generalized S-transform resolution and normalization processing according to a mathematical model of a to-be-observed signal and the fault overcomplete atom library; calculating a maximum value of the normalized multi-resolution time-frequency spectrum, and calculating an atom set capable of best performing sparse representation on the to-be-observed signal by combination with an orthogonal matching tracking algorithm; andaccording to the fault sparse representation signal and fault feature frequency of a device and rotating speed information, determining a fault type, to achieve a rapid fault diagnosis of the mechanical device. The sparse feature extraction method has the advantages that the complexity of the atomic search and the search time are greatly reduced, the efficiency of sparse decomposition is improved,and the efficiency of fault diagnosis of impact faults such as crack, pitting or spalling is improved.
Owner:WUHAN UNIV OF SCI & TECH +1
Time frequency decomposition and reconstruction method of generalized S transform signals for synchronous extrusion
PendingCN107229597AHigh precisionImprove reconstruction accuracyComplex mathematical operationsFrequency spectrumDelayed time
The invention discloses a time frequency decomposition and reconstruction method of generalized S transform signals for synchronous extrusion. Firstly, the four parameter generalized S transform is conducted on a signal, the variation trend of a basic wavelet function is adjusted by the adjustment of the basic wavelet amplitude, energy attenuation rate, energy delay time and basic wavelet video rate; secondly, the modulus of the result of the four parameter generalized S transform is obtained, and the energy of each time-frequency point is obtained, thus the time-frequency spectrum is obtained; thirdly, the instantaneous frequency is obtained by the four parameter generalized S transform of the signal; fourthly, the frequency set after the generalized S transform is set as the central frequency set, each time frequency point corresponding to the instantaneous frequency close to the interval of the central frequency is extruded to the central frequency point, and the generalized S transform of synchronous extrusion is obtained; finally, the inverse transformation formula of generalized S transform for synchronous extrusion is deduced. The generalized S transform of synchronous extrusion has the advantages of synchronous extrusion transform and generalized S transform, and is a time-frequency decomposition and reconstruction method for high precision signals.
Owner:CHENGDU UNIVERSITY OF TECHNOLOGY
Pre-stack Q-value inversion method based on generalized S-transform and pre-stack Q-value inversion system thereof
InactiveCN106291693AHigh precisionHigh-resolutionSeismic signal processingFrequency spectrumTime–frequency analysis
The invention relates to the technical field of geophysical prospecting for petroleum, and discloses a pre-stack Q-value inversion method based on generalized S-transform and a pre-stack Q-value inversion system thereof. The pre-stack Q-value inversion method comprises the steps that a pre-stack CMP gather of a seismic wave layer model is acquired; time frequency analysis s performed on the pre-stack CMP gather trace by trace by using generalized S-transform so that the amplitude spectrum of a target layer is obtained; the spectrum ratio slope of each seismic trace of the target layer is solved based on the amplitude spectrum of the target layer; a zero-offset ray average quality factor is solved according to the linear relation of the spectrum ratio slope and the offset; and the interlayer Q-value of the seismic wave layer model is estimated according to the zero-offset ray average quality factor. The accuracy of the inversion result can be greatly enhanced, reservoir prediction can be effectively guaranteed, and the method and the system can be applied to reservoir prediction, crack detection and inverse Q filtering of the field of oil and gas prospecting so that the resolution of seismic data can be enhanced.
Owner:CHINA PETROLEUM & CHEM CORP +1
Parameter optimization based time frequency analysis method for improved generalized S-transform
ActiveCN105373708AImprove energy concentrationEasy to calculateSpecial data processing applicationsInformaticsRadarS transform
The invention discloses a parameter optimization based time frequency analysis method for an improved generalized S-transform. The parameter optimization based time-frequency analysis method comprises the steps of firstly selecting the range of parameters in the improved generalized S-transform; for each group of parameters, calculating time frequency distribution of an input signal by using the improved generalized S-transform and carrying out energy normalization processing on the time frequency distribution; then calculating the corresponding time frequency aggregation degree of each group of parameters and employing one group of parameters corresponding to maximum values as optimized parameters; finally introducing the optimized parameters into the improved generalized S-transform to calculate the time frequency distribution of the input signal. According to the parameter optimization based time frequency analysis method for the improved generalized S-transform, a first-order function with frequency as an independent variable is introduced into a window function of the S-transform so that the form of the window function is flexible and adjustable, the parameters of the first-order function are optimized through the time frequency aggregation degree, the energy aggregation of the signal time frequency distribution can be improved, the estimated accuracy of signal instantaneous parameters is enhanced, the calculated amount is small, the parameter optimization based time frequency analysis method is suitable for analysis and processing of communication, radar, earthquake and biomedicine signals.
Owner:CHINA UNIV OF GEOSCIENCES (WUHAN)
Method and device for detecting gas content of reservoir
InactiveCN109557578AImprove accuracyIncrease reflectionSeismic signal recordingSeismic signal processingFrequency spectrumDecomposition
The invention relates to a method and device for detecting gas content of a reservoir, and belongs to the technical field of seismic exploration oil and gas detection. The method comprises the following steps: obtaining corresponding intrinsic function profiles (IMF) by empirical mode decomposition of the stacked seismic data, selecting the profile with the greatest correlation with the original seismic profile as an ideal intrinsic function profile, generalized S-transforming each record in the selected IMF profile, then superimposing the records to obtain a time-frequency profile, then dividing the time-frequency profile to obtain high-frequency and low-frequency profiles, calculating to obtain a formation absorption profile, and determining features of gas content of the reservoir by the formation absorption profile. The invention uses the empirical mode to decompose the seismic data to better reflect the underground geological information, and improve the detection accuracy of gascontent of the reservoir, and uses the spectral energy difference extracted by the high-precision generalized S transform to more accurately indicate the gas content of the reservoir, and meet the detection requirements of gas content of the high-precision reservoir.
Owner:CHINA PETROLEUM & CHEM CORP +1
Generalized S transformation and SVM electric energy quality disturbance efficient identification method
PendingCN111368892AImprove recognition accuracyImprove anti-interference abilityData processing applicationsCharacter and pattern recognitionPower qualityAlgorithm
The invention relates to a generalized S transformation and SVM power quality disturbance efficient identification method comprising the following steps: collecting voltage data of a power quality disturbance signal, using a power quality monitor to collect the voltage data of the power quality disturbance signal, and transmitting the voltage data to an upper computer; gST generalized S transformation is carried out on the voltage data received by the upper computer, two groups of GST parameters are set, and a time amplitude envelope curve and a frequency amplitude envelope curve are respectively obtained; extracting a feature vector of the voltage data; and inputting the feature vector obtained in the previous step into a GWO-SVM classifier for training and testing, thereby completing identification of the power quality disturbance signal. The method has high identification precision in power quality disturbance identification, has strong anti-interference capability in power qualitydisturbance identification, and has good performance in processing a small sample disturbance identification problem.
Owner:HEFEI UNIV OF TECH
Generalized S transformation-based lightning interference identification method for high-voltage direct-current transmission line
PendingCN112881855AAvoid the influence of absolute amplitude magnitudeReduce computing requirementsElectric power transfer ac networkEmergency protective circuit arrangementsTransient stateLightning strokes
The invention discloses a generalized S transformation-based lightning stroke interference identification method for a high-voltage direct-current transmission line. Themethod comprises the steps: firstly carrying out phase-mode transformation on positive and negative voltage and current signal fault components of a rectification side, and obtaining a 1-mode component; secondly, carrying out generalized S transformation on a voltage 1-mode component within 3 ms after protection is started, and calculating low-frequency energy and high-frequency energy; then calculating the ratio of low-frequency energy to high-frequency energy of the voltage, and judging whether lightning interference or a line fault occurs according to a result; and finally, if lightning stroke interference occurs, resetting protection, and if a fault occurs, performing generalized S transformation on a current 1-mode component 1ms after protection is started, calculating the ratio of low-frequency energy to high-frequency energy of the current, judging whether a lightning stroke fault or a common short-circuit fault occurs according to a result, and protecting an outlet. According to the method, lightning stroke interference can be accurately identified, the reliability of transient state quantity protection of the DC line is improved, a lightning stroke fault and a common short-circuit fault are further distinguished, and the method has guiding significance in lightning protection, operation and maintenance of the line.
Owner:XUCHANG XJ SOFTWARE TECH +1
Method for efficiently extracting attenuation quality factor in complex reservoir
ActiveCN108957540AEfficient Reservoir PredictionAccurate Amplitude Spectrum ResultsSeismic signal processingTime domainUltrasound attenuation
The invention discloses a method for efficiently extracting an attenuation quality factor in a complex reservoir, comprising the following steps of S1, reading the seismic record data of a survey lineand determining a target stratum; S2, transforming, by using generalized S transform, each seismic record on the survey line from the time domain into the time-frequency domain to obtain a time-frequency map; S3, determining the attenuation estimated frequency band of the target stratum; S4, calculating the centroid frequency of a spectrogram in a selected frequency band at each time depth basedon the time-frequency map; S5, estimating the Q value sequence of the target stratum by an improved centroid frequency shift method; and S6, processing the Q value sequence by a stratum stripping method; and S7, drawing an output Q value profile map. The method utilizes the generalized S transform and the improved centroid frequency shift method to improve the accuracy and stability of the Q valueestimation.
Owner:HOHAI UNIV
Hydrocarbon detecting method and device based on wavelet energy attenuation features of generalized S transform
InactiveCN103353610AEasy to detectQuick analysisSeismic signal processingFrequency spectrumTime frequency spectrum
The invention provides a hydrocarbon detecting method and a hydrocarbon detecting device based on wavelet energy attenuation features of generalized S transform, belonging to the field of seismic data processing of petroleum geophysical exploration. The method comprises that a time-frequency spectrum of each seismic channel is calculated according to the generalized S transform; a time-frequency spectrum of a wavelet of a corresponding sampling point is obtained from the time-frequency spectrum of each seismic channel via a spectrum simulation technology; a dominant frequency of each wavelet is found out from the time-frequency spectrum of the wavelet; between a zero frequency and the dominant frequency of each wavelet, an attenuation coefficient QL of the wavelet in a charging hole portion at an objective exploration layer is calculated; between the dominant frequency and a cutoff frequency of each wavelet, an attenuation coefficient QG of the wavelet in a gassing hole portion at the objective exploration layer is calculated; and gas hydrocarbon exploration results in the objective exploration layer are obtained according to the acquired energy attenuation feature of each wavelet. Due to the fact that change speed of attenuation coefficients at high / low frequency end of the wavelet is directly related to whether a reservoir contains gas, the method and device of the invention can obviously improve success rate of gas hydrocarbon exploration.
Owner:BC P INC CHINA NAT PETROLEUM CORP +1
Small current grounding fault line selection method based on generalized S transformation transient energy
InactiveCN111077407AImprove accuracyIncrease reflectionFault location by conductor typesShort-circuit testingGeneralized s transformFault model
The invention discloses a small current grounding fault line selection method based on generalized S transformation transient energy. The method comprises the steps that: according to a 10kV line topological graph of a power distribution network, an actual overhead line-cable series-parallel line model and a fixed-value resistance fault model of the power distribution network are built on a PSCADplatform, and single-phase earth fault simulation experiments under various simulation working conditions are carried out; and then generalized S transformation is performed on the acquired transientzero-sequence current at the bus outlet in 1 / 4 power frequency period after each feeder line fails, generalized S transformation transient energy in a characteristic frequency band is calculated, andthe transient energy of each feeder line is compared so as to adaptively select a faulty line. The method is not influenced by the working conditions such as the fault position, the fault resistance,the line structure and the neutral point grounding mode, the fault line can be accurately selected; and the method has the advantages of being high in practicability, high in accuracy and wide in applicability.
Owner:HOHAI UNIV
Near-surface Q-value inversion and classified evaluation method based on generalized S transform
ActiveCN110261904AHigh-resolutionImproving Imaging AccuracySeismic signal processingSeismology for water-loggingLithologyEffect factor
The invention provides a near-surface Q-value inversion and classified evaluation method based on generalized S transform. The near-surface Q-value inversion and classified evaluation method comprises the steps of: step 1, sorting data of two adjacent channels; step 2, respectively applying generalized S transform on the data of two adjacent channels to obtain high-resolution time spectra; step 3, extracting corresponding instantaneous amplitude spectra of first arrival signals; step 4, adopting a logarithmic spectrum ratio method to perform inversion fitting to obtain a Q value between two channels; step 5, repeating the steps from (1) to (4), and performing inversion to obtain Q values between adjacent channels in all micro-logging data; step 6, generating curves of the Q values varying with depths at the well positions; step 7, calculating an average attenuation effect factor by combining layer thicknesses and layer velocities; step 8, and performing near-surface classified evaluation by taking the average attenuation effect factor as a benchmark. The near-surface Q-value inversion and classified evaluation method based on generalized S transform studies the acquisition method for deeper complex structure and stratum lithology exploration, improves the acquisition quality and efficiency, and provides effective technical support and guarantee.
Owner:CHINA PETROLEUM & CHEM CORP +1
VSP seismic data frequency-varying Q value estimation and inverse Q filtering method
InactiveCN110967749AObvious frequency-varying Q value characteristicsImprove resolutionSeismic signal processingFrequency spectrumMathematical model
The invention provides a VSP seismic data frequency-varying Q value estimation and inverse Q filtering method, which is characterized by firstly transforming a seismic record signal to a time-frequency domain by utilizing generalized S transformation; constructing a quadratic polynomial fitting relationship between a time-frequency spectrum ratio and an inverse quality factor Q-1 value for each frequency, and when a frequency Q value is calculated, calculating a spectrum ratio change slope in a small frequency interval taking the frequency as a center to obtain a central frequency Q value soas to realize VSP data frequency change Q value estimation; based on an inverse Q filtering method which is provided by Hale based on a Futterman mathematical model and uses series expansion as approximate high-frequency compensation, obtaining a relationship between the inverse Q filtering output frequency spectrum and the input seismic record frequency spectrum, the quality factor and the frequency and Hilbert transform, and revising a constant Q value in the relationship into a frequency-variable Q value to realize inverse Q filtering of the frequency-variable Q value. According to the method, the oil and gas reservoir can be predicted by utilizing the Q-value frequency dispersion attribute, and meanwhile, the imaging resolution and the signal-to-noise ratio are improved.
Owner:EAST CHINA UNIV OF TECH
Earthquake strong shielding time-frequency information extraction and stripping method based on phase control
The invention provides an earthquake strong shielding time-frequency information extraction and stripping method based on phase control. The method comprises the following steps: 1, performing well-to-earthquake calibration and horizon tracking on earthquake data; 2, performing logging facies and near-well seismic facies analysis on a typical well, and roughly dividing a phase zone; 3, extractingseismic attributes from determined horizon upper and lower time window ranges, screening characteristic attributes with good performance for combinatorial analysis, and determining an accurate sedimentary facies strip graph; 4, performing generalized S transformation on the seismic data of a target processing layer to extract algorithm parameters; 5, determining variable wavelet information participating in the algorithm; and step 6, matching the optimal wavelet according to the multiphase band waveform characteristics to carry out strong layer stripping. The earthquake strong shielding time-frequency information extraction and stripping method based on phase control can provide shielding removal data for subsequent attribute extraction, oil and gas reservoir identification and reservoir prediction, so that the identification and exploration and development capability of a beach and dam sand weak signal layer is improved.
Owner:CHINA PETROLEUM & CHEM CORP +1
High-voltage circuit breaker fault diagnosis method based on GWO-KFCM
PendingCN112289329AImprove reliabilityIncrease dependenceKernel methodsSpeech analysisBandpass filteringAlgorithm
The invention discloses a high-voltage circuit breaker fault diagnosis method based on GWO-KFCM. The method comprises the following steps of: 1, carrying out the band-pass filtering of a sound signal,and constructing a voiceprint feature through generalized S transformation; 2, carrying out variational mode decomposition on a vibration signal to obtain a permutation entropy; 3, combining the voiceprint features and the permutation entropy features to construct a feature vector set; and 4, pre-classifying the feature vector set through GWO-KFCM to obtain an optimal feature vector sub-set, inputting optimal feature vector sub-set data into a model SVM, obtaining a final diagnosis result through classification, extracting voiceprint and permutation entropy features respectively by utilizingthe joint complementary advantages of the sound and vibration signals, then performing clustering optimization by adopting GWO-KFCM to obtain an optimal clustering center, and finally, adopting an SVMfor fault diagnosis. The mechanical fault of the high-voltage circuit breaker can be quickly and effectively detected, and the reliability of fault diagnosis of the high-voltage circuit breaker is improved.
Owner:HAIXI POWER SUPPLY COMPANY OF STATE GRID QINGHAI ELECTRIC POWER +1
Fractional order synchronous extraction generalized S transformation time-frequency decomposition and reconstruction method
ActiveCN110347970ATime-frequency energy concentrationHigh time-frequency resolutionComplex mathematical operationsFrequency spectrumReconstruction method
The invention discloses a fractional order synchronous extraction generalized S transform time-frequency decomposition and reconstruction method. The method comprises the following steps: inputting x(t), selecting different rotation angles alpha to carry out fractional Fourier transform spectral analysis on x (t); selecting an optimal rotation angle alpha opt to carry out fractional order generalized S transformation on the signal to obtain a fractional order generalized S transform value, and performing modeling; solving fractional order instantaneous frequency estimation on the basis of thefractional order generalized S transform value, obtaining a synchronous extraction operator according to the instantaneous frequency estimation, extracting a fractional order generalized S transformtime-frequency spectrum by using the synchronous extraction operator, retaining effective energy, and finally reconstructing a signal. According to the invention, the time-frequency characterization of the signal can be popularized to the time fractional order frequency characterization; time-frequency information details can be recognized by selecting the optimal rotation angle in a self-adaptivemode, on the basis, energy of a fractional order synchronous extraction generalized S transformation time-frequency spectrum is more gathered by adjusting window function parameters and conducting extraction operation, and therefore the time-frequency resolution of signals is greatly improved.
Owner:CHENGDU UNIVERSITY OF TECHNOLOGY
High-resolution thin and interbedded reservoir gas containing performance detection method
InactiveCN107748387AAvoid direct fitting to find the slopeHigh-resolutionSeismic signal processingFrequency spectrumFrequency conversion
The invention relates to the field of petroleum and natural gas exploration and development, and especially relates to a high-resolution thin and interbedded reservoir gas containing performance detection method. The thin and interbedded reservoir gas containing performance detection method provided by the invention acquires a time-frequency spectrum of collected seismic signals through adopting generalized S transform. Compared with time-frequency conversion performed according to the traditional method, the method provided by the invention has higher time-frequency spectrum resolution and accuracy. Meanwhile, the thin and interbedded reservoir gas containing performance detection method combines a method of performing linear processing on the amplitude between a starting frequency fs andan ending frequency fe, thereby avoiding an operation of performing direct fitting by using data of a segment with the frequency f being greater than the starting frequency fs and less than the ending frequency fe to solve the slope, and greatly improving the resolution, which is reflected by the seismic signals, in the longitudinal direction of a target detection area.
Owner:CHINA PETROLEUM & CHEM CORP +1
Current signal filtering and denoising method based on generalized S transformation containing variable factor
InactiveCN111046791AHigh time-frequency resolutionSuppress noiseCharacter and pattern recognitionTime domainFrequency spectrum
The invention discloses a current signal filtering and denoising method based on generalized S transformation containing a variable factor. The method comprises the following steps: firstly, converting a discrete sampling sequence of a group of continuous time domain current signals into a two-dimensional time-frequency complex matrix through generalized S transformation containing the variable factor; secondly, performing threshold filtering method processing on the two-dimensional time-frequency matrix, performing processing by using a time-frequency filter based on time-frequency spectrum distribution, reserving effective signals in a time-frequency domain, and extracting effective current signal components; and finally, obtaining a noise-removed one-dimensional time domain current signal through generalized S inverse transformation. According to the method, the current pure signal under the noise background can be effectively extracted, so that the current signal can be analyzed and processed under various working condition environments.
Owner:HOHAI UNIV
Lightning trip type identification method
ActiveCN113158781AExpand the scope of extractionImprove running stabilityElectrical testingCharacter and pattern recognitionTime domainAlgorithm
The invention discloses a lightning trip type identification method, which comprises the following steps: extracting lightning trip transient voltage signal feature image data, inputting the feature image data into a deep residual neural network model, and outputting an identification result by the deep residual neural network model. The step of extracting the feature image data of the lightning trip transient voltage signal comprises the steps of performing multi-scale generalized S transformation on the extracted one-dimensional time domain voltage signal, drawing time-frequency distribution images of different-scale generalized S transformation, and taking the time-frequency distribution image data as the feature image data of the lightning trip transient voltage signal. According to the method, the one-dimensional time domain voltage signal is subjected to multi-scale generalized S transformation, so that the extraction range of lightning trip transient voltage signal feature image data is expanded, the problem that transient feature quantities are not sufficiently utilized by a one-dimensional signal analysis method in neural network discrimination is solved, and the accuracy of lightning trip type discrimination is improved.
Owner:ELECTRIC POWER RES INST OF STATE GRID ANHUI ELECTRIC POWER +1
Seismic Time-Frequency Analysis Method Based on Generalized Chirplet Transform with Time-Synchronized Extraction
A seismic time-frequency analysis method based on generalized Chirplet transform with time-synchronized extraction, which has higher level of energy aggregation in the time direction and can better describe and characterize the local characteristics of seismic signals, and is applicable to the time-frequency characteristic representation of both harmonic signals and pulse signals, comprising the steps of processing generalized Chirplet transform with time-synchronized extraction for each seismic signal to obtain a time spectrum by: carrying out generalized Chirplet transform, calculating group delay operator and carrying out time-synchronized extraction on seismic signals, thereby the boundary and heterogeneity structure of the rock slice are more accurately and clearly shown and subsequence seismic analysis and interpretation are facilitated.
Owner:XI AN JIAOTONG UNIV
Electrocardiogram identity recognition method
PendingCN112215196AResolve incoherenceAccurate and error-free identificationCharacter and pattern recognitionNeural architecturesEcg signalNonlinear approximation
The invention discloses an electrocardiogram identity recognition method. The method comprises the following steps: acquiring an ECG (Electrocardiogram) signal of a human body; preprocessing the collected ECG signal to obtain a clean short-period ECG signal; generalized S transformation is carried out on the short-period ECG signals, and a phase domain feature vector Y1, a time domain feature vector Y2 and a frequency domain feature vector Y3 are extracted; inputting the phase domain feature vector Y1, the time domain feature vector Y2 and the frequency domain feature vector Y3 into a sparsity-constrained nonlinear approximation model to obtain an optimal dictionary and a corresponding optimal sparse coefficient matrix, and performing lightweight processing on the optimal sparse coefficient matrix to obtain a sparse coefficient vector; and inputting the sparse coefficient vector into a trained deep neural network model based on a bidirectional long-short-term memory network for identity recognition. According to the invention, the multi-modal feature vector is extracted from the original ECG signal to serve as the input vector of the deep neural network, so that the recognition precision is improved, and the recognition rate is increased.
Owner:HANGZHOU DIANZI UNIV
Action recognition method based on GST and VL-MOBPNN
ActiveCN111242100AEasy to handleSolve fixed puzzlesCharacter and pattern recognitionDiagnostic recording/measuringTime–frequency analysisEngineering
The invention relates to an action recognition method based on GST and VL-MOBPNN. The method comprises the steps: acquring sample data of human lower limb electromyographic signals; performing time-frequency generalized S transformation on an electric signal to obtain a time domain cumulative characteristic curve when the time resolution is relatively high and a frequency domain cumulative characteristic curve when the frequency resolution is relatively high; obtaining a feature vector of the signal; and inputting the feature vector into a learning rate variable quantity back propagation neural network for identification and classification to obtain a classification result. According to the invention, time-frequency generalized S transformation is adopted to analyze signals more meticulously, so that the problem that the window width of a Gaussian window is fixed in a traditional time-frequency analysis method is solved; Gaussian window adjustment parameters are introduced into time-frequency generalized S transformation, the inverse proportion change rate of the Gaussian window width along with the frequency can be flexibly adjusted according to the frequency distribution characteristics and the time-frequency analysis emphasis of the electromyographic signals in practical application, the method can better adapt to analysis and processing of specific signals, and therefore the signal processing capacity is improved.
Owner:HEFEI UNIV OF TECH
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