487 results about "Wave transformation" patented technology

The present invention provides a method and apparatus for logging an earth formation and acquiring subsurface information wherein a logging tool is conveyed in a borehole to obtain parameters of interest. The parameters of interest obtained may be density, acoustic, magnetic or electrical values as known in the art. As necessary, azimuths associated with the measurements are obtained and corrections applied. The corrected data may be filtered and/or smoothed. The parameters of interest associated with azimuthal sectors are depth matched, resolution matched and filtered, and the acquisition effects removed. The data are denoised using a multi-resolution wavelet transform. The data acquired with separate transducers are resolution matched to obtain a resolution matched data series. Subsequently the resolution matched data may be further denoised using a multi-resolution wavelet transform.

Methods and apparatus are provided for discriminating high rate polymorphic QRS complexes from high rate monomorphic QRS complexes to increase the specificity of detection of polymorphic VT and VF employing wavelet transform signal processing of the QRS complexes are disclosed. Wavelet transforms are applied to the sampled amplitude values of a sequence of QRS complexes to develop wavelet transform coefficient (WTC) data sets. At least selected ones of the WTC data sets are processed and comparisons are made to determine a wavelet match score. A determination is made as a function of the wavelet match scores of the series of successive QRS complexes that characterizes the most recent QRS complex as more or less likely to signify polymorphic VT or VF.

The invention relates to an auto-stability method for camera image and the auxiliary device used in hand held state or motion state. It uses angular velocity sensor to check the angular velocity of the camera rotating round the three space axes in real-time and records synchronistical with image signal. The variance of the attitude angle between two pictures would be gained by integral in afterward process software, and the attitude angle variance related to slow-varying low frequency element in motion angular velocity is reserved, meanwhile the attitude angle variance related to dithering angle element would be eliminated. Then, the image dithering would be eliminated by translation and rotation the image. The device is made up of three same circuits. And every process circuit is connected by angular velocity checking circuit which is belonged to signal collection circuit, power lever shifting circuit which is belonged to signal process circuit, voltage/frequency transformation circuit, frequency division circuit, wave transformation circuit, signal compound and extent regulation circuit in series. The output signal is sent to the interface of camera.

The invention provides a bearing fault diagnosis method and system device based on improved empirical wavelet transform. The method comprises: step one, collecting different fault bearing signals as analysis signals and converting a time domain waveform into a frequency domain waveform; step two, drawing an upper envelope of a frequency spectrum and transforming a frequency peak with a tight support into a flat top; step three, screening flat tops in the frequency domain based on criteria, removing meaningless flat tops, and keeping a main frequency; step four, using a minimum value between adjacent flat tops as the boundary of spectrum segmentation; step five, establishing wavelet filters respectively for segmented frequency spectrums and decomposing the signals into N mode components; step six, calculating similarity values between mode components and the original signals by using a cross-correlation coefficient and selecting a component with the highest similarity value; and step seven, taking a fault sample, calculating an IMF component with the largest correlation coefficient of the sample, calculating a multi-scale entropy of the IMF component, and drawing the multi-scale entropy curve of the sample to realize fault classification.

An integrated power amplifier can include a carrier amplifier, where the carrier amplifier is connected to a first quarter wave transformer at the input of the carrier amplifier. In addition, the power amplifier can further include at least one peaking amplifier connected in parallel with the carrier amplifier; a first differential combining structure, where the first combining structure includes a first plurality of quarter wave transformers that are configured to combine respective first differential outputs of the carrier amplifier in phase to generate a first single-ended output signal, and a second differential combining structure, where the second combining structures includes a second plurality of quarter wave transformers that are configured to combine respective second differential outputs of the at least one peaking amplifier in phase to generate a second single-ended output signal, where the first single-ended output signal and the second single-ended output signal are combinable in-phase to provide an overall output.

The invention discloses a multi-focusing image fusion method utilizing core Fisher classification and redundant wavelet transformation. The method comprises the following steps: firstly, carrying out image block segmentation on source images and calculating definition characteristics of each image block; secondly, taking part of areas of the source images as a training sample and obtaining various parameters of a core Fisher classifier after training; thirdly, utilizing the known core Fisher classifier to obtain preliminary fusion images; and finally, utilizing redundant wavelet transformation and space correlation coefficients to carry out fusion processing on the image blocks positioned at the junction of the clear and fuzzy areas of the source images to obtain final fusion images. The invention has better image fusion performance, does not have obvious blocking artifacts and artifacts in fusion results, obtains better compromise between the effective enhancement of the image fusion quality and the reduction of the calculation quantity and can be used in the subsequent image processing and display. When wavelet decomposition layers with less number are adopted, the invention is more suitable for an occasion with higher real-time requirement.

The invention discloses a partial discharge detection identification method based on ultrasound and ultraviolet information fusion. The method comprises the following steps: S1. uniformly setting sensing detection circuits in surrounding space of a detected object; S2. real-timely collecting an ultrasonic signal and an ultraviolet signal generated when partial discharge is generated in a detected area, after the signals are processed, sending to a digital signal processing circuit; S3. carrying out digital filtering processing; S4. extracting dual density wavelet transform wavelet coefficient Shannon entropy x from the ultrasonic signal generated in S3, extracting wavelet packet wavelet coefficient Shannon entropy y, and sending a characteristic vector x and a characteristic vector y to a detection system host via a communication module; S5. carrying out characteristic fusion by the detection system host so as to obtain the characteristic vector z after the fusion; S6. classifying the vector z obtained in S5 after the fusion by using support vector machine classification trees. By using the method of the invention, application of a detection identification technology based on the ultrasound and ultraviolet information fusion can be promoted; high accuracy, reliability and instantaneity of the partial discharge detection can be ensured.

The invention provides a wavelet transform and joint sparse representation-based infrared and invisible light image fusion method, and relates to the field of image fusion. The method comprises the following steps of: firstly, carrying out DWT transform on a source image, decomposing the source image into a low-frequency sub-band matrix coefficient and a high-frequency sub-band coefficient, decomposing the low-frequency sub-band coefficient into a matrix by using a sliding window strategy and learning a dictionary in allusion to the decomposed low-frequency sub-band matrix; secondly, respectively fusing the low-frequency sub-band coefficient and the high-frequency sub-band coefficient; and finally reconstructing a fused image through DWT inverse transform. According to the method, effective sparse representation can be carried out on outstanding detail features of source images, and multi-scale fusion can be carried out on detail information of the images, so that target information of infrared images and background information such as details, profiles and the like of invisible light images are well retained, the target identification ability is improved, and benefit is brought to subsequent processing systems to extract and use the information; and compared with the traditional wavelet transform-based fusion method and the existing joint sparse representation-based fusion method, method provided by the invention has advantages.

The invention relates to a modal parameter identification method based on response signal time-frequency joint distribution characteristics. According to the modal parameter identification method based on the response signal time-frequency joint distribution characteristics, signal analysis and structural modal parameter identification are carried out directly through a structural vibration response. The modal parameter identification method based on the response signal time-frequency joint distribution characteristics comprises the steps of firstly carrying out complex wavelet continuous transformation on a structural response signal, obtaining energy distribution characteristics of various wavelet transformation domains (a real domain, a virtual domain, a modal domain and a phase domain), obtaining a time average wavelet energy spectrum through a wavelet transformation coefficient, therefore carrying out quantification on selection of model orders and the scale corresponding to each order modality, on the basis, obtaining the optimum scale required by parameter identification, achieving pre-identification of modal frequency through the corresponding relation of the scale and the frequency, finally extracting a wavelet transformation coefficient slice at the specific scale, carrying out linear fitting through an amplitude value and a phase component, and achieving structural identification of inherent frequency and a damping ratio. As simulation and experiment results show, even if an external incentive function is not included, accurate identification of structural modal parameters can be achieved through the modal parameter identification method based on the response signal time-frequency joint distribution characteristics.

The present invention discloses an counterfeit-proof system of the identification certificate with the two-dimension barcode and the automatic identifying method thereof which obtains the information carried in the two-dimension barcode input by a scanning equipment through the image identifying technique. This system and method includes the manufacture of the counterfeit-proof identification certificate, the process of the photograph of the certificate holder, the formation of the two-dimension barcode and the identification of the real / false of the identification certificate. The photograph of the identification certificate is processed using the compression technique which comprises the small wave transformation, the main element analysis, the self-organic characteristic mapping nerve-cell web, the self-adaptive variable gathering sub-block and Huffman encode. In the identification of the two-dimension barcode, the input of the identification certificate with the barcode, the access of the area where the barcode stays and the process of the barcode area are performed by the scanning equipment to obtain the PDF417 encode according to the national standard, and then the carried information is obtained according to the compression of encode and the encryption of information. The real / false of the certificate is determined by comparing the literal information and the numerical information of the certificate obtained by decoding with the information stored in the data base and the information of the determined real certificate can be stored automatically in the data base according to the userí»s requirement.

A method of image compression with wavelet transforms applied locally rather than globally by image component partitioning into independently transformed macroblocks plus overlapping data for filter length compensation.

The invention discloses a wavelet transform and time search strategy based double-end traveling wave fault location method for hybrid power transmission line. The method comprises the following stepsof 1) determining an electrical topological structure of the hybrid power transmission line MN; 2) acquiring the motion time of traveling waves on a section line according to the length and motion wave speed of each section line; 3) according to fault traveling wave information acquired by traveling wave distance measuring devices at the two ends of the line, adopting wavelet transform to detect and identify the moment when the fault traveling wave moves to each bus measuring end for the first time so as to obtain a time difference when the traveling wave arrives at the two ends of the bus, and calculating t1 an t2 according to formulas by combining movement time of the fault traveling wave on the whole power transmission line; and 4) starts comparing from the end M of the bus, judging that the fault position is behind the xj1 section when t1>deltat1, and judging that the fault position is on the xd1 section when deltat1<t1<deltat1+deltat2, thus calculating the fault position. The method can be used to identify the initial traveling wave of a fault more accurately, and effectively solve the problem in fault distance measurement of the cable and overhead line hybrid power transmission line of the power system.

The invention relates to a method for inverting vegetation parameters by remote sensing based on reflection spectrum wavelet transform. The method comprises the following steps of: 1) acquiring the vegetation parameters and the original spectrum thereof under different conditions, and performing spectrum transform on the original spectrum; 2) performing continuous wavelet transform on the original spectrum by using different wavelet functions, and generating wavelet coefficients with different frequencies; 3) performing stepwise regression by taking different scales of wavelet coefficients as independent variables and taking the vegetation parameters as dependent variables, selecting spectrum wave bands needed by the inversion of the vegetation parameters, constructing a model of quantitative inversion of the vegetation parameters, and calculating R2 of the model; and 4) comparing modeling R2 of the constructed model according to different wavelet decomposition scales, and determining the model with the maximum modeling R2 as the optimal model. By the method, the hyperspectral remote sensing inversion precision of the vegetation parameters can be obviously improved, and the remote sensing inversion precision of biochemical parameters can be improved preferably. The method has wide parameter applicability, is applicable to leaf or canopy reflection spectrum, and is applicable to satellite remote sensing hyperspectral data.

The invention discloses a fundamental frequency detection method based on improved experience wavelet transformation. The method comprises steps of step 1, preprocessing a speech signal: calculating short-term energy and zero-crossing rate of the speech signal, using a dual-threshold method to carry out rhythm segmentation and passing the segmented signal through a 50-1500Hz band-pass filter for filtering so as to obtain pre-processed speech signal; step 2, using the improved experience wavelet transformation method to decompose the preprocessed speech signal so as to obtain each mode function of the speech signal; step 3, according to the mode function, selecting the main mode of the speech signal; step 4, using Hilbert transformation to solve a transient fundamental frequency value of the main mode; and step 5, using a rectangular window function to carry smoothing processing on the transient fundamental frequency value obtained in the step 4 to finish the fundamental frequency detection. The method is characterized by high accuracy, quite good robustness and high time resolution.

The invention discloses a rolling bearing fault diagnosis method for improving a model migration strategy, and belongs to the technical field of rolling bearing fault diagnosis. The method is providedfor solving the problem of large distribution difference of data in the same state in a source domain and a target domain, and comprises: obtaining time-frequency spectrums of vibration signals of different types of bearings through wavelet transform, and constructing an image data set; selecting data of a certain model as a source domain, and selecting data of other models as a target domain; training a ResNet-34 deep convolutional network by using the source domain data to obtain a source domain data classification model; adaptively determining a migration knowledge level and knowledge content by using implicit gradient meta-learning to realize improvement of a model migration strategy and avoid a phenomenon that a gradient in a heterogeneous system structure is not easy to converge; introducing the migrated knowledge into a target domain ResNet-152 convolutional neural network data training process, and realizing model migration through parameter transmission; and optimizing network parameters by adopting a stochastic gradient descent algorithm when the source domain network and the target domain network are trained, and establishing fault diagnosis models of different types ofrolling bearings.

The invention discloses a radar based respiration and heartbeat signal detection method and system. The method comprises the steps of A, judging whether a target exists based on a transmitting signaland a receiving signal; and B, performing the following processing on a mixed vital sign signal of the target: B1, performing high-pass filtering and FFT on the mixed vital sign signal to obtain firstfrequency spectrum data; B2, if the frequency corresponding to a maximum amplitude value point is within a respiratory frequency range and the maximum amplitude value point exists at a Q frequency doubling position and/or near the Q frequency doubling position of the frequency, taking the frequency as a respiratory dominant frequency; B3, decomposing the mixed vital sign signal of the target based on empirical wavelet transform; and B4, if the maximum value frequency of a third component or a fourth component is within a preset heartbeat frequency range, taking the maximum value frequency asa heartbeat dominant frequency. Based on the empirical wavelet transform, respiration and heartbeat signals are adaptively separated and the frequencies of the respiration and heartbeat signals are accurately extracted, and the respiration and heartbeat frequencies of multiple persons can be simultaneously extracted and separated for a broadband/ultra-wideband radar.

The invention discloses a phase sensitive optical time-domain reflectometer (phi-OTDR) sensing signal noise separation and signal extraction method, a longitudinal time sequence signal of each point of a phi-OTDR space is used as a processing object, multi-scale decomposition is performed for the time sequence signal by utilization of wavelet transforming, component signals in each scale are analyzed and reorganized in a selective mode, undulate background noise, acoustic waves and other time-varying interference signals are separated, real disturbance invasion signals are extracted, not only can undulate background noise be restrained, but also influences from other complicated time-varying interference noise are avoided, an invasion detection accuracy rate can be effectively improved, a system false alarm rate is reduced, detection performance of an invasion detection system based on a phi-OTDR in an actual complicated noise environment is improved, and significant application requirements in perimeter security, long-distance pipeline safety, large structure health monitoring and the like for a country can be met.