54 results about "Wavelet processing" patented technology

Carrier Interferometry (CI) provides wideband transmission protocols with frequency-band selectivity to improve interference rejection, reduce multipath fading, and enable operation across non-continuous frequency bands. Direct-sequence protocols, such as DS-CDMA, are provided with CI to greatly improve performance and reduce transceiver complexity. CI introduces families of orthogonal polyphase codes that can be used for channel coding, spreading, and / or multiple access. Unlike conventional DS-CDMA, CI coding is not necessary for energy spreading because a set of CI carriers has an inherently wide aggregate bandwidth. Instead, CI codes are used for channelization, energy smoothing in the frequency domain, and interference suppression. CI-based ultra-wideband protocols are implemented via frequency-domain processing to reduce synchronization problems, transceiver complexity, and poor multipath performance of conventional ultra-wideband systems. CI allows wideband protocols to be implemented with space-frequency processing and other array-processing techniques to provide either or both diversity combining and sub-space processing. CI also enables spatial processing without antenna arrays. Even the bandwidth efficiency of multicarrier protocols is greatly enhanced with CI. CI-based wavelets avoid time and frequency resolution trade-offs associated with conventional wavelet processing. CI-based Fourier transforms eliminate all multiplications, which greatly simplifies multi-frequency processing. The quantum-wave principles of CI improve all types of baseband and radio processing.

Carrier Interferometry (CI) provides wideband transmission protocols with frequency-band selectivity to improve interference rejection, reduce multipath fading, and enable operation across non-continuous frequency bands. Direct-sequence protocols, such as DS-CDMA, are provided with CI to greatly improve performance and reduce transceiver complexity. CI introduces families of orthogonal polyphase codes that can be used for channel coding, spreading, and / or multiple access. Unlike conventional DS-CDMA, CI coding is not necessary for energy spreading because a set of CI carriers has an inherently wide aggregate bandwidth. Instead, CI codes are used for channelization, energy smoothing in the frequency domain, and interference suppression. CI-based ultra-wideband protocols are implemented via frequency-domain processing to reduce synchronization problems, transceiver complexity, and poor multipath performance of conventional ultra-wideband systems. CI allows wideband protocols to be implemented with space-frequency processing and other array-processing techniques to provide either or both diversity combining and sub-space processing. CI also enables spatial processing without antenna arrays. Even the bandwidth efficiency of multicarrier protocols is greatly enhanced with CI. CI-based wavelets avoid time and frequency resolution trade-offs associated with conventional wavelet processing. CI-based Fourier transforms eliminate all multiplications, which greatly simplifies multi-frequency processing. The quantum-wave principles of CI improve all types of baseband and radio processing.

The invention is suitable for the technical field of biological medicines and medical facilities, and provides a method and a device for measuring blood pressure upon radial artery pulse wave conduction time. The method comprises the following steps: acquiring a human body radial artery pulse wave signal through a photoelectric sensor, and performing filtering amplification and AD (analog-digital) conversion on the human body radial artery pulse wave signal through a microprocessor to finally obtain a human body radial artery pulse wave signal with low noise and obvious feature points; performing frequency-domain transformation, wavelet processing and second order difference on the obtained human body radial artery pulse wave signal to determine the feature points of a human body radial artery pulse wave form; calculating an accurate numerical value of the human body radial artery pulse wave conduction time; establishing a regression equation for measuring the blood pressure to finally obtain blood pressure values. According to the method and the device provided by the invention, the blood pressure only needs to be measured at a single point, so that the processing difficulty of the signal is reduced, a measuring process is simplified, and the comfort of blood pressure measurement is improved; meanwhile, the accuracy of blood pressure measurement is improved through method improvements, and moreover, the blood pressure can be continuously monitored for a long time.

The invention relates to a method for denoising wavelet images chosen on the basis of the neighbor data of a sliding window. The method comprises the following steps: step 1, decomposing a noisy image into sub-bands by wavelet transformation processing; step 2, processing the wavelet coefficient of each sub-band according to the following steps: 1), carrying out threshold judgment of the center wavelet coefficient of each neighbor centering on each wavelet coefficient in each sub-band, comparing the correlativity coefficient Theta of each neighbor of the coefficient, and carrying out 2) if the maximal correlativity coefficient Theta is higher than an empirical value, or carrying out step 3 directly if the maximal correlativity coefficient Theta is lower than the empirical value; 2), calculating the Bayes adaptive threshold value of the threshold processing window chosen in 1) so as to obtain a scaling factor; and 3), scaling the wavelet coefficient in the center of the window according to the scaling factor; and step 3, reconstructing the wavelet coefficient so as to obtain the filtered image after processing each sub-band of the wavelet with adaptive sliding window neighbor wavelet process. The method has the advantages of higher peak value signal-to-noise ratio and better protection effect for image edges.

A process for secured distribution of video sequences according to a digital stream format stemming from an encoding based on a processing by wavelets including frames including blocks containing coefficients of wavelets describing the visual elements, including analyzing the stream prior to transmission to client equipment to generate a modified main stream by deletion and replacement of selected information coding the original stream and having the format of the original stream, and complementary information of any format comprising the digital information coding the original stream and suitable for permitting reconstruction of the modified frames; and transmitting the modified main stream and the complementary information separately from a server to addressed equipment.

The invention discloses a method for detecting and locating an R wave in QRS (Quantum Resonance Spectrometer) waves of electrocardiographic signals of a mother and a fetus, which comprises the steps of: front-end filtering: sequentially adopting a low-pass filter, a high-pass filter and a differentiator in a preprocessing procedure; wavelet processing procedure: making the R waves of the electrocardiographic signals of the mother and the fetus relatively more obvious by adopting a wavelet resolution procedure according to the respective medical characteristics, distributed wave bands and amplitude sizes of the electrocardiographic signals of the mother and the fetus; and adaptive threshold R wave judgment, wherein a floating adaptive threshold is adopted in a Rdetect algorithm, firstly, the R wave position of the electrocardiographic signal of the mother is judged, and then is subjected to front-end processing, and the position of the appeared R wave characteristic point in the QRS waves of the electrocardiographic signal of the fetus is located by using the algorithm, and is subjected to post processing and signal adjustment so as to finish detecting the R wave positions of the electrocardiographies of the mother and the fetus on mixed signals. The invention can well achieve the purpose of respectively detecting the collected mixed electrocardiographic signals.

The invention discloses a multi-model multi-feature fusion method for predicting the wind speed along a high-speed railway, and the method comprises the following steps: 1, installing five auxiliary wind measurement stations nearby a wind measurement station; 2, carrying out the processing of original wind speed data through an interactive multi-model Kalman filtering method; 3, carrying out the wavelet processing of the filtered data, and building a prediction submodel for the low-frequency data after wavelet processing; 4, inputting target wind measurement station multistep-ahead prediction values and weather forecast target wind station prediction values obtained by a space-target wind measurement multistep-ahead prediction model, a self-target wind measurement station multistep-ahead prediction model and a weather-target wind measurement station multistep-ahead prediction model into a Bayes combined model, and obtaining the final target wind measurement station prediction value. The method can avoid the data interruption caused by a single wind measurement station hardware fault, and also can provide longer emergency processing time for the safety of the high-speed railway in a severe wind environment.

The invention relates to a method for denoising wavelet images chosen on the basis of the neighbor data of a self-adapting sliding window. The method comprises the following steps: step 1, decomposing a noisy image into sub-bands by wavelet transformation processing; step 2, processing the wavelet coefficient of each sub-band separately according to the following steps: 1), carrying out threshold judgment of the center wavelet coefficient of each neighbor centering on each wavelet coefficient in each sub-band, comparing the correlativity coefficient Theta of each neighbor of the coefficient, and setting a sliding window, in which the maximal correlativity coefficient Theta is located, as the window for threshold processing; and 2), calculating the Bayes adaptive threshold value of the threshold processing window chosen in 1) so as to obtain a scaling factor; and scaling the wavelet coefficient in the center of the window according to the scaling factor; and step 3, reconstructing the wavelet coefficient so as to obtain the filtered image after processing each sub-band of the wavelet with adaptive sliding window neighbor wavelet process. The method achieves a higher peak value signal-to-noise ratio, thereby having a better protection effect for image edges.

A method according to an aspect of the invention is for filtering coherent multipulse radar, sonar or lidar returns. The method comprises the steps of separating the returns into mutually orthogonal I & Q components, performing wavelet processing on the I and Q components to generate an I & Q wavelet filter output. The I & Q wavelet filter outputs are data compressed to remove clutter portions. Data compression may be removal of large-amplitude or earliest wavelet responses. An inverse wavelet filtering function is performed on the compressed wavelet filter outputs, to thereby generate edited coherent I & Q components. Doppler filtering, is performed on the edited coherent I and Q components to thereby generate frequency-domain target data in which the minimum discernible target velocity is improved.

Various techniques can be used to improve classification of colon polyps candidates found via computed tomographic colonography computer aided detection (CTCCAD). A polyp candidate can be classified as a true positive or a false positive. For example, a two-dimensional projection image of the polyp can be generated from a three-dimensional representation and classified based on features of the projection image. An optimal viewpoint for the projection image can be found via techniques such as maximizing viewpoint entropy. Wavelet processing can be used to extract features from the two-dimensional projection image. Feature extraction can use a piecewise linear orthonormal floating search for locating most predictive neighbors for wavelet coefficients, and support vector machines can be employed for classification. The techniques can be useful for improving accuracy of CTCCAD techniques.

Carrier Interferometry (CI) provides wideband transmission protocols with frequency-band selectivity to improve interference rejection, reduce multipath fading, and enable operation across non-continuous frequency bands. Direct-sequence protocols, such as DS-CDMA, are provided with CI to greatly improve performance and reduce transceiver complexity. CI introduces families of orthogonal polyphase codes that can be used for channel coding, spreading, and / or multiple access. Unlike conventional DS-CDMA, CI coding is not necessary for energy spreading because a set of CI carriers has an inherently wide aggregate bandwidth. Instead, CI codes are used for channelization, energy smoothing in the frequency domain, and interference suppression. CI-based ultra-wideband protocols are implemented via frequency-domain processing to reduce synchronization problems, transceiver complexity, and poor multipath performance of conventional ultra-wideband systems. CI allows wideband protocols to be implemented with space-frequency processing and other array-processing techniques to provide either or both diversity combining and sub-space processing. CI also enables spatial processing without antenna arrays. Even the bandwidth efficiency of multicarrier protocols is greatly enhanced with CI. CI-based wavelets avoid time and frequency resolution trade-offs associated with conventional wavelet processing. CI-based Fourier transforms eliminate all multiplications, which greatly simplifies multi-frequency processing. The quantum-wave principles of CI improve all types of baseband and radio processing.

The invention relates to a ghost wave compression method based on wavelet processing. The method comprises the steps that (1) offshore seismic data information are input, wherein the seismic data information comprises three kinds of seismic wavelets and seismic data comprising uncompressed ghost waves, and the three kinds of seismic wavelets comprise the seismic wavelet comprising cable ghost waves and seismic source ghost waves, the seismic wavelet comprising the seismic source ghost waves only and the seismic wavelet comprising no ghost waves; (2) ghost wave compression is carried out on seismic data with uncompressed ghost waves through the seismic wavelets; (3) seismic data which compress the cable ghost waves and the seismic source ghost waves at the same time are output. According to the ghost wave compression method, the wavelet matching algorithm is adopted for compressing the ghost waves, and the ghost waves are compressed starting from seismic data processing instead of collection, so that the processing process is easy to implement, and the cost is saved; the ghost wave compression method can compress the seismic source ghost waves and the cable ghost waves in the offshore seismic data, and can be widely applied in the offshore seismic exploration process.

It is an object of the present invention to prevent an image distortion from occurring by using a line memory of small memory capacity. For example, an image is decomposed into strip regions 12, and each strip region 12 is filtered together with certain excess data 14 from a neighboring strip region 12 to prevent an image distortion from occurring at the boundary between the strip regions 12 while executing band decomposition on the strip region 12 which is smaller in size than the entire image with a smaller line memory. In the band decomposition, a line memory which supports band decomposition of, for example, 3 decomposition levels is repeatedly and recursively used, whereby band decomposition of deeper decomposition levels is executed without any problems. In this manner, line-based wavelet transform for deeper decomposition levels is executed with a small line memory. Also reverse wavelet transform is executed in the similar manner.

A laser phase Doppler dust particle monitoring method and apparatus belongs to particle measuring technique. It includes the steps that two beams of coherent incident light has concourse and irradiate normally to flowing direction of dust particle current; two sensors are installed with symmetry, optical signal of particle scattering received by which has the same frequency but different phase, its frequency is proportional to flight velocity of particle and phase difference is proportional to with diameter of particle, by using processor to extract frequency and phase difference of signal, the diameter, velocity and other information of particle are obtained. The apparatus consists of detecting system containing laser source, polarizer, beam splitter, objective lens and APD sensor and processing system containing signal preprocessor, high speed synchronous A / D converter, wavelet processor, parameter processor and data fractional, synchronous controller. The invention has the advantages including high accuracy and reliability of parameter measurement like velocity and diameter of dust particle, wide measuring range and excellent applicability.

The invention discloses a wave filter merging method applied to a self organization pulse sensor. The method obtains multi-path pulse wave curves through placing a plurality of piezoelectric sensor point lattices at radial artery parts on the inner side of the wrist, wherein each single-point sensor can separately measure the pulse wave. The curves carry out digital wave filtering and factor analysis in an information merging center according to the following steps that: firstly, the digital wave filtering adopts a small wave processing method, and noise signals such as base line drifting, electromyographical interference, power frequency interference and the like mixed in the pulse waves can be effectively eliminated; and then, the multi-path pulse signals after the wave filtering carry out dimensionality reduction processing through the factor analysis, signal channels with server distortion in the multi-path pulse signals are eliminated, at the same time, two paths of pulse signals are optimized and selected, and finally, the two paths of pulse signals are merged into one path of pulse signals to be output. When the method of the invention is adopted, the real-time output weighing regulation of the sensor point lattices can be realized, so a path of pulse signals nearest to the actual pulse signals can be obtained, and then, the monitoring and the analysis of the real-time pulse signals can be finally realized through the connection of a wireless communication module and a subsequent processing module.

The invention discloses a micro-displacement thickness measurement method for a lithium battery film. The method disclosed by the invention is characterized by adopting a standard measurement block to calibrate the space between an upper sensor and a lower sensor to realize static denoising, and being combined with a joint algorithm of three-layer wavelet processing, threshold value judgment processing and seven-layer wavelet processing to realize dynamic denoising. By adopting the method, thickness measurement of any coating length of a lithium battery can be measured by the laser sensors on site in real time, and the measurement accuracy is high. The method comprises the steps of measurement in a relative stationary state as well as a relative motion state, wherein the relative motion state comprises three states that 1, a laser thickness measurement device is stationary and the lithium battery film to be measured is in motion, 2, the laser thickness measurement device is in motion and the lithium battery film to be measured is stationary and 3, the laser thickness measurement device is in motion and the lithium battery film to be measured is also in motion. The method disclosed by the invention is applicable to all the three states, so that the method has a wide application range in industry and has high adaptability.

The invention discloses an aero-engine blade test piece nondestructive testing method based on a terahertz technology, which comprises the following steps: performing nondestructive testing on a sample by utilizing a terahertz signal to obtain a terahertz original detection signal; carrying out fourier transform, frequency domain deconvolution and wavelet processing on the terahertz original detection signal to obtain a characteristic signal with a high signal-to-noise ratio; performing Fourier transform on the characteristic signal with the high signal-to-noise ratio to obtain a frequency domain power spectrum, and expanding the frequency domain power spectrum to obtain a sample image; and carrying out quantitative characterization on the thickness and defects of the ceramic layer in thesample image after the imaging contrast is improved. The invention further provides an aero-engine blade test piece nondestructive testing device based on the terahertz technology. According to the method, the problems of low detection precision, limited detection range and missed detection and false detection of a traditional nondestructive detection mode can be solved, and high-precision quantitative detection of the surface, interface and internal crack defects of the thermal barrier coating and the thickness of the ceramic layer is realized.

The invention discloses a face recognition method under complicated illumination conditions of an underground coal mine. The method mainly comprises an initialization stage, a training stage and a recognition stage, wherein image collection, image storage, image denoising, image enhancement and feature description are included at the initialization stage, feature vector dimension reduction and classifier model establishment are included at the training stage, and classified recognition is performed on to-be-recognized faces according to an established classifier model at the recognition stage;and image denoising and image enhancement are realized by the adoption of a fuzzy enhancement algorithm based on wavelet decomposition, an ALBP operator is adopted to perform feature description on aface image after wavelet processing, and a classifier is adopted to construct a face model and establish a face sample database. Through the method, the problem that the recognition rate is sharply lowered due to image shadows, bright and dark areas, dark light and high light under complicated underground illumination conditions can be overcome, and the face attendance recognition accuracy in theunderground coal mine is improved.

A process for secured distribution of video sequences according to a digital stream format stemming from an encoding based on a processing by wavelets including frames including blocks containing coefficients of wavelets describing the visual elements, including analyzing the stream prior to transmission to client equipment to generate a modified main stream by deletion and replacement of selected information coding the original stream and having the format of the original stream, and complementary information of any format comprising the digital information coding the original stream and suitable for permitting reconstruction of the modified frames; and transmitting the modified main stream and the complementary information separately from a server to addressed equipment.

The invention relates to a DA-SVM (dragonfly algorithm optimized support vector machine)-based rolling bearing fault detection method, and belongs to the field of mechanical automation fault detection. The DA-SVM-based rolling bearing fault detection method comprises the following steps: firstly, performing feature extraction on signals of four states, namely a normal state, an outer ring fault, an inner ring fault and a shaft body fault, of the rolling bearing by using a wavelet packet method; and subjecting the extracted signals to multi-wavelet processing and then inputting the extracted signals into an SVM model optimized through a dragonfly algorithm to serve as training samples, and after training is completed, inputting the test samples into the trained DA-SVM model for fault detection. The detection recognition rate and the detection speed are important bases for measuring the detection method, and the DA-SVM rolling bearing diagnosis model formed by optimizing penalty factorsand kernel function parameters in the SVM through the dragonfly algorithm has the excellent performance of high diagnosis precision and high detection speed.

A method of processing an image using a difference wavelet. The method includes loading the image into an image processing program, decomposing the image using a difference wavelet, truncating the image below a predetermined threshold level or enhancing the image according to an enhancement function, reconstructing the image using the difference wavelet, and outputting the image.

The invention discloses a health monitoring and rupture early warning system and method for a sewage pipeline based on an OFDR. The system comprises a distributed optical fiber sensor, a temperature compensating optical fiber, an optical fiber data acquisition and transmission system, an optical fiber data processing and analysis system, a wavelet processing and noise reduction system, a monitoring result display system and an early warning system. The optical fiber is paved on the urban sewage pipeline, the real-time acquisition and transmission of optical fiber data are carried out by usingthe optical fiber data acquisition and transmission system, and then, the optical fiber data are processed through the optical fiber data processing and analysis system to obtain the information, suchas deformation condition, of the sewage pipeline. Then, smoothing and noise reduction processing is carried out on the data through the wavelet processing and noise reduction system, the data are displayed in the monitoring result display system in the forms of a graph and the like, the health information of the sewage pipeline is learned, and early warning is carried out before rupture. The system has the advantages of high precision, high survival rate, distributed measurement and the like and realizes the functions of carrying out health monitoring on pipeline deformation and carrying outrupture early warning.

The present invention relates to a method of coding and / or decoding groups of pictures. According to the invention, during the temporal decomposition of a stream of pictures within the framework of 3D wavelet processing, the number of pictures, the choice of the reference picture and the direction of temporal decomposition for each picture sequence of GOP type are adapted in order to minimize the number of unconnected pixels.

The invention discloses an image enhancement and fusion method applied to a CMOS image sensor. Particularly, for image data output by the CMOS image sensor, firstly, an image is subjected to segmentation processing to obtain two images, the two new images are subjected to image quality enhancement processing to enable image contrast to be modulated, and image denoising processing is performed forreducing noises caused by previous image processing to meet the demands of subsequent processing on the image quality; secondly, the two images are subjected to wavelet decomposition; and finally, theimages subjected to the wavelet processing are subjected to fusion and invert wavelet transform processing to obtain a final output image after restoration. According to the image enhancement and fusion method applied to the CMOS image sensor, the problem of image distortion caused by the noises is solved; the image quality and the image transparency are enhanced; the image edge details are kept;and real-time processing is realized in finite platform resources.

The invention discloses a distribution network failure moment determining method based on multi-order wavelet function transformation. The method is capable of adapting to multiple failure types and multiple failure locations and accurately positioning the failure moment. The method disclosed by the invention comprises the following steps: adopting FFT (Fast Fourier Transform) of a moving time window according to a general format (COMTRADE) waveform file exchanged by transient data of a power system collected by a failure indicator, judging aiming at the calculated distortion factor, and generally locating the failure moment, so as to save time for subsequent wavelet processing; and accurately locating failure points by adopting a method for performing wavelet transform by adopting a multi-order wavelet function. According to the method, characteristics of wavelet functions of different orders are utilized, the stability and accuracy of failure moment determination are taken into account, the effectiveness of the method is validated by analyzing various different actual failure waveforms, and reliable method supports are provided for detection of the failure indicator device.

The invention discloses an OFDR-based expressway roadbed disease monitoring system and method. The system comprises a roadbed settlement optical fiber sensing device, a roadbed horizontal deformationoptical fiber sensing device, a bridge foundation pile deformation optical fiber sensing device, a water level change and precipitation optical fiber sensing device, an OFDR optical fiber data acquisition and transmission system, an on-site road condition monitoring system, a solar power supply and data transmission system, an OFDR optical fiber data processing and analysis system, a wavelet processing and noise reduction system, a monitoring result display system, a cloud platform data management and early warning system and a remote receiving system. According to the invention, OFDR opticalfiber data is collected and transmitted in real time; roadbed settlement difference, horizontal displacement, foundation pile dynamic strain response, precipitation, underground water level and riverwater level information are obtained through the optical fiber data processing system; and the information is displayed in a monitoring result display system in a chart manner, is uploaded to the cloud platform data management and early warning system and then is compared with an early warning value, and a disease treatment scheme is searched in time, so that remote monitoring and timely treatmentare realized.

The invention relates to an embedded zerotree coding method on the basis of inverse Loop subdivision, which comprises the following steps of: (1) constructing an offset wavelet tree, i.e. forming an offset d by obtaining difference of an actual vertex O and a forecast vertex O' and simultaneously, establishing a corresponding quad-tree relation of edges in each mesh Mj-1 and four edges in a thinner layer mesh Mj, wherein the offset d is generated on a corresponding edge of a delete vertex reconstruction mesh; (2) carrying out offset wavelet processing and selecting a threshold value; and (3) encoding and carrying out code-stream ordering, wherein important information is preferentially encoded by adopting an embedded encoding mode on the basis of a three-dimensional graph triangular mesh and a result obtained after compression is placed at an initial part of a code stream. The invention provides the embedded zerotree coding method on the basis of inverse Loop subdivision, through which compression efficiency is greatly improved.

The invention relates to a camera capable of embedding descriptive information in the photo, belonging to the fields of the computer application, the digital product application, the mode identification, the image processing and the like. The camera is capable of taking a photo and embedding descriptive information in the photo with the digital watermarking technology. To make the descriptive information embedded in the photo resist the impact from compressing, scaling and filtering, the watermark is embedded in the photo with the robust digital watermarking technology in such a way of lifting wavelets in the two layers of the photo, returning the lowest effective position of the obtained low-frequency subband to zero, transforming the descriptive information into a binary image and embedding the binary image in the lowest effective position of the low-frequency subband. The camera is capable of taking a photo and embedding descriptive information in the photo, can be widely applied to the crime investigation field, the claim settlement field and other places needing to embed descriptive information in the photo in time and can be used for taking a photo in the daily life.

The invention discloses a wavelet feature extraction method and system for a voice signal, and a storage medium. The wavelet feature extraction method comprises the following steps: carrying out the wavelet processing of an obtained original voice signal, and obtaining a wavelet coefficient of the original voice signal; arranging the wavelet coefficients according to a first preset rule; calculating the variance of the arranged wavelet coefficients; normalizing the variance of the wavelet coefficient; arranging the normalized variances of the wavelet coefficients according to a second preset rule; and converting the variance of the arranged wavelet coefficients into a grayscale image to obtain wavelet features of the original voice signal. According to the wavelet feature extraction method, wavelet processing is carried out on the original voice signal and normalization processing is carried out on the variance of the wavelet coefficient, so that the influence of noise on the feature extraction process is reduced and thus the anti-noise capability during the feature extraction process of the non-stationary voice signal and the overlapped voice signal is improved. The wavelet feature extraction method can be widely applied to the technical field of speech recognition.

The invention discloses a wavelet analysis post-processing method and device for a power transient signal. The method is to conduct the following one or more post-processing on the wavelet coefficients after the power transient signal is analyzed by wavelet, and the result is to send power Monitoring center processing: modulus maximum extraction, singularity detection, obtaining modulus maximum points and singularity; statistical processing or cluster analysis of wavelet coefficients; neural network classification, that is, wavelet coefficients or wavelet post-processed data as neural Network input, output neural network classification results; energy analysis, to obtain energy distribution coefficient and energy fluctuation coefficient; wavelet entropy calculation, to obtain wavelet energy spectrum entropy or wavelet time entropy or wavelet singular entropy or wavelet time-frequency entropy or wavelet average entropy or wavelet distance entropy. It can effectively extract the characteristics of power transient signals, which can be applied to power system transmission line traveling wave distance measurement and fault identification, power quality analysis and equipment fault diagnosis.