14 results about "Pulse inversion" patented technology

The invention provides a nonlinear ultrasonic detection method for micro-damage of concrete, and particularly relates to the technical field of material detection. The method specifically comprises the following steps: S1, defining a scanning area and planning a scanning path; s2, exciting fundamental frequency ultrasonic waves to the signal excitation points in the signal excitation area in sequence through a transmitting probe by using a pulse reversal technology; s3, receiving the fundamental frequency ultrasonic waves and the generated second harmonics at the signal excitation points at the corresponding positions of the signal receiving area at the same time in sequence by using a receiving probe; s4, scanning all signal excitation points on the whole surface of the to-be-detected concrete scanning area according to a set scanning path; s5, nonlinear ultrasonic parameters on all sound paths are calculated; and S6, constructing a nonlinear ultrasonic imaging spectrum and judging the spatial distribution and damage degree of the micro-damage of the to-be-detected concrete. According to the method, the concrete micro-damage is represented by directly utilizing nonlinear ultrasonic parameters, and the detection limit of ultrasonic waves and the resolution of low-frequency ultrasonic waves are effectively improved on the premise that the penetrating power of the low-frequency ultrasonic waves is reserved.

An ultrasound imaging system is disclosed that performs enhanced B-mode imaging through a pulse inversion (PI) process. A controller transmits a PI sequence including a positive and a negative ultrasound pulse into biological tissue. A signal processing circuit receives echo signals resulting from this PI sequence and extracts three distinct signals: a direct current harmonic (DCH) signal, a fundamental signal at the transmitted frequency, and a second harmonic signal. Weights are assigned to these signals to create weighted signals spanning different nonlinear frequency bands. A final image is then generated from these weighted signals, improving image penetration, resolution, and clutter reduction compared to standard methods.

The invention provides a non-reference damage imaging method based on nonlinear Lamb waves and Bayesian inference, and relates to the field of damage imaging, and the method specifically comprises the following steps: collecting nonlinear Lamb wave signals of a plurality of propagation paths; an enhanced second harmonic signal is obtained through a pulse inversion technology; extracting a flight time feature of the envelope signal; the frequency spectrum of the nonlinear Lamb wave signal is obtained through fast Fourier transform, and nonlinear coefficient damage index features are obtained through calculation; feature level fusion is carried out based on Bayesian estimation; and solving a posterior probability density function of the damage position parameter by using Hamiltonian Monte Carlo sampling, and carrying out damage probability imaging positioning according to posterior probability distribution. According to the technical scheme, the problems that in the prior art, a large number of sensors usually need to be deployed, and the dual requirements for high-precision damage detection and sensor number minimization in engineering practice are difficult to meet are solved.

The invention discloses an ultrasonic imaging method and system based on amplitude modulation and singular value decomposition, and the method comprises the steps: obtaining baseband IQ data based on original radio frequency echo data, obtaining a positive polarity synthetic frame and a negative polarity synthetic frame, carrying out the pulse inversion summation to obtain an image set, constructing the image set at all sound pressure levels into a Casorati matrix of a space-sound pressure domain, and carrying out the pulse inversion summation to obtain a Casorati matrix of a space-sound pressure domain; performing singular value decomposition filtering to obtain a reconstructed singular value matrix, calculating a reconstructed matrix I, reshaping each column of the reconstructed matrix I back to a two-dimensional image, and performing coherent summation to generate a final ultrasonic imaging image. The ultra-high-speed single-frame imaging is realized only by depending on the current frame, and the limitation that a traditional method depends on a time sequence is broken through; firstly, fundamental waves are removed, second harmonics are highlighted, and the contrast ratio of a microbubble contrast agent and tissues is improved; signal separation is carried out based on sound pressure dimensions through singular value decomposition of a Casorati matrix, enhancement of secondary harmonic signals of the microbubble contrast agent is achieved, and purification of the harmonic signals is achieved.

The application discloses a shale gas type I reservoir quality parameter determination method and device and a storage medium, and belongs to the technical field of shale gas exploration and development. The method processes data obtained from actual drilling, obtains a forward geology model, and obtains forward seismic profile data. A time difference value data set is obtained based on the data, wave impedance data is obtained by inverting the forward seismic profile data, and then a wave impedance ratio data set is obtained. A first formula is adjusted based on the time difference value data set and the wave impedance ratio data set, a second formula is obtained, and the quality parameters of each position in a to-be-studied area can be obtained based on the second formula and actual exploration seismic data of the to-be-studied area. The method processes data through model forward and post-stack sparse pulse inversion, and compared with pre-stack geostatistics inversion for processing data, the method solves the problems of large data processing amount, many parameters and complex process in the related art, and achieves the effect of reducing the data processing amount.

The invention provides a reservoir prediction method based on constrained sparse pulse inversion and deep learning, and belongs to the technical field of geophysical exploration and development. According to the scheme, three-dimensional seismic data and logging data of a work area are obtained, well-side seismic data and a logging wave impedance curve are obtained, constrained sparse pulse inversion is carried out on the three-dimensional seismic data, and a three-dimensional wave impedance body is obtained; constructing a training sample which takes the logging wave impedance curve as a label and takes the well-side seismic data and the well-side wave impedance inversion result as input characteristics, establishing a prediction model based on a deep neural network, training the prediction model to obtain a wave impedance intelligent prediction model, inputting three-dimensional seismic data and a three-dimensional wave impedance body to obtain a three-dimensional wave impedance prediction body, and carrying out prediction on the three-dimensional wave impedance prediction body. And reservoir prediction is carried out. The method has the advantages that the advantages of high reliability and good transverse continuity of low-frequency information in traditional seismic inversion and the advantages of high resolution and good well matching of deep learning intelligent inversion are fully utilized, and high-precision reservoir prediction is achieved.

The present application relates to the technical field of casting billet quality evaluation, and particularly relates to a quality evaluation method and system for a casting billet forming process, which comprises the following steps: emitting an ultrasonic pulse to a detection area of the casting billet, receiving a full-matrix echo signal, and the full-matrix echo signal comprising a primary echo signal and a second harmonic signal; performing variational mode decomposition on the primary echo signal to separate a grain boundary scattering signal and a linear defect echo signal generated by a coarse grain structure of the casting billet; constructing a scattering texture atlas based on the grain boundary scattering signal and constructing a linear feature defect set based on the linear defect echo signal; performing pulse inversion processing on the second harmonic signal to construct a nonlinear response atlas; performing spatial registration on the scattering texture atlas, the linear feature defect set and the nonlinear response atlas to construct a multi-dimensional fusion feature vector; and obtaining a quality evaluation result of the casting billet forming based on the spatial distribution characteristics of the multi-dimensional fusion feature vector in the detection area. The present application effectively improves the accuracy of quality evaluation of the casting billet forming process.

This invention relates to the field of billet quality evaluation technology, and particularly to a method and system for quality evaluation of the billet forming process. The method includes: emitting ultrasonic pulses to the area to be inspected in the billet and receiving a full-matrix echo signal, which includes a first-order echo signal and a second-harmonic signal; performing variational mode decomposition on the first-order echo signal to separate grain boundary scattering signals and linear defect echo signals generated by the coarse-grained structure of the billet; constructing a scattering texture map based on the grain boundary scattering signal and a linear feature defect set based on the linear defect echo signal; performing pulse inversion processing on the second-harmonic signal to construct a nonlinear response map; spatially registering the scattering texture map, the linear defect feature set, and the nonlinear response map to construct a multi-dimensional fused feature vector; and obtaining the quality evaluation result of the billet forming process based on the spatial distribution characteristics of the multi-dimensional fused feature vector within the area to be inspected. This invention effectively improves the accuracy of quality evaluation in the billet forming process.

The application provides a non-reference damage imaging method based on nonlinear Lamb waves and Bayesian inference, relates to the field of damage imaging, and specifically comprises the following steps: collecting nonlinear Lamb wave signals of multiple propagation paths; obtaining enhanced second harmonic signals through a pulse inversion technique; extracting time-of-flight characteristics of envelope signals; obtaining frequency spectra of the nonlinear Lamb wave signals by using fast Fourier transform, and calculating nonlinear coefficient damage index characteristics; performing feature-level fusion based on Bayesian estimation; solving a posterior probability density function of a damage position parameter by using Hamilton Monte Carlo sampling, and performing damage probability imaging positioning according to the posterior probability distribution. The technical scheme of the application overcomes the problem in the prior art that a large number of sensors usually need to be deployed, and it is difficult to meet the dual requirements of high-precision damage detection and minimization of the number of sensors in engineering practice.

An ultrasound imaging system, method, and computer readable medium, wherein the method performs enhanced B-mode imaging by a pulse reversal (PI) process. The controller sends a PI sequence including positive and negative ultrasound pulses into the biological tissue. The signal processing circuit receives an echo signal generated by the PI sequence, and extracts three different signals: a DC harmonic DCH signal, a fundamental wave signal of a sending frequency, and a second harmonic signal. Weights are assigned to the signals to create weighted signals across different non-linear frequency bands. Compared with a standard method, the method has the advantages that the image penetrating power and the resolution are improved, and clutters are reduced.

The invention discloses a water-drive reservoir full-grid scale automatic history fitting method based on disturbance pulse inversion, and belongs to the technical field of reservoir numerical simulation. The method comprises the following steps: simulating a discrete seepage field as a time-streamline set based on a streamline; solving the water phase seepage equation by using a characteristic line method to obtain a saturation propagation control equation along a streamline; constructing a water saturation disturbance transmission mechanism, establishing error mapping with the water content of the production well, and forming a linear equation set; solving a least square problem by taking a water content fitting error as a constraint to obtain an optimal correction of a saturation field; updating a saturation field and generating a new streamline, and iterating until fitting reaches the standard; and correcting the permeability field based on the injection-production well time sequence correlation coefficient and the production well pressure prediction error. The method has the characteristics of insensitivity to initial saturation, high inversion efficiency and high fitting precision, and is suitable for historical fitting and prediction of large-scale complex water-drive reservoirs.

The application discloses a water drive reservoir full-grid scale automatic history matching method based on disturbance pulse inversion and belongs to the technical field of reservoir numerical simulation. The method is characterized in that: a time-flow line set is obtained by discretizing a seepage field by using streamline simulation; a saturation propagation control equation along a flow line is obtained by using a characteristic line method to solve a water phase seepage flow equation; a water saturation disturbance transmission mechanism is constructed; a water cut error mapping with a production well is established and a linear equation set is formed; a saturation field optimal correction amount is obtained by solving a least square problem with a water cut fitting error as a constraint; a saturation field is updated and new flow lines are generated according to the saturation field; and iteration is performed until the fitting reaches a standard; and a permeability field is corrected based on a time sequence correlation coefficient of injection and production wells and a production well pressure prediction error. The application has the characteristics of being insensitive to an initial saturation, high inversion efficiency and high fitting precision, and is suitable for large-scale complex water drive reservoir history matching and prediction.

The invention provides a concrete ultrasonic signal chain type processing method based on a three-level collaborative algorithm, and the method comprises the steps: obtaining a concrete ultrasonic signal, processing the concrete ultrasonic signal based on a pulse reversal technology, eliminating linear noise, and processing the concrete ultrasonic signal after the linear noise is eliminated based on Bayesian wavelet transform. The method comprises the following steps: finely filtering environmental mixed noise, processing a finely filtered concrete ultrasonic signal based on adaptive filtering, tracking and inhibiting time-varying noise, performing feature enhancement and quality verification on the processed signal, and outputting an ultrasonic signal with a high signal-to-noise ratio. Through staged treatment and dynamic parameter optimization, accurate suppression of multivariate noise in the concrete ultrasonic signal is realized, meanwhile, microdefect characteristics are completely reserved, and the precision of subsequent defect detection is remarkably improved.