185 results about "Frequency dispersion" patented technology

The invention provides a high-temperature chemical pipeline defect detection system and method based on magnetostrictive ultrasonic guided waves, and relates to the technical field of high-temperature chemical pipeline defect detection.The method comprises the steps that magnetostrictive excitation signals are applied, the propagation process of the guided waves in a pipeline is calculated through numerical simulation, and the amplitude and phase information of guided wave signals is obtained; performing time-frequency domain analysis on the guided wave signal, extracting group velocities and phase velocities of guided waves in different modes, determining frequency dispersion characteristics of the guided waves, and evaluating the influence of a high-temperature environment on guided wave propagation; processing the received guided wave signal by adopting a modal decomposition and reconstruction algorithm to obtain a corrected guided wave signal; and carrying out feature extraction and parameter estimation on the corrected guided wave signal to obtain the position, size and type information of the pipeline defect. According to the invention, the problem of multilayer heterogeneous pipeline guided wave detection in a high-temperature environment is solved, the accuracy and reliability of defect detection are improved, and an effective method is provided for pipeline health monitoring and safety assessment.

The invention relates to the technical field of model construction, in particular to a method for constructing an effective dielectric constant model of a carbon fiber composite material. The method comprises the following steps: collecting a sample, carrying out electromagnetic orthogonal frequency sweep analysis, generating a spectrum distribution map, obtaining internal field distribution mapping data through boundary topology recombination, carrying out interval correlation analysis on the internal field data, generating a spatial distribution function, and calibrating a phase resonance point to obtain a frequency characteristic spectrum. Performing field region classification and interactive coupling evaluation according to the frequency characteristic spectrum, deducing a node link structure, performing internal and external field interactive tensor projection and constraint embedding processing based on the node link structure, constructing a composite field model, generating a dielectric frequency dispersion curve through dielectric characteristic inversion, and performing modeling based on frequency dispersion curve data to obtain an effective dielectric constant model. According to the invention, the more accurate construction method of the carbon fiber composite material effective dielectric constant model is realized.

The invention relates to a transverse isotropic hard formation horizontal shear wave velocity inversion method and device. The method comprises the following steps: acquiring waveform data measured by a target interval array acoustic logging dipole mode; based on the waveform data, using a weighted spectrum coherence analysis method to calculate and obtain a bending wave actual measurement frequency dispersion curve; according to the bending wave actual measurement frequency dispersion curve, calculating to obtain bending wave time difference probability density; according to the bending wave time difference probability density, calculating to obtain a stratum vertical shear wave speed; establishing an objective function of transverse isotropic stratum horizontal shear wave velocity inversion based on a frequency dispersion equation of the transverse isotropic stratum and the stratum vertical shear wave velocity; and according to the objective function, inversion is carried out to obtain the stratum horizontal shear wave velocity. According to the method, the target function of horizontal shear wave velocity inversion is reduced from two dimensions to one dimension, and the stability and efficiency of inversion are remarkably improved.

The invention relates to an anisotropic elastic medium Rayleigh surface wave frequency dispersion curve inversion method, which comprises the steps of collecting near-earth surface wave exploration seismic data, obtaining a Rayleigh surface wave frequency dispersion energy diagram based on a phase shift method, and extracting a frequency dispersion curve from the frequency dispersion energy diagram based on a convolutional neural network artificial intelligence method; constructing a near-surface anisotropic elastic parameter initial model; calculating to obtain a theoretical Rayleigh surface wave dispersion curve by using a Rayleigh surface wave dispersion curve forward modeling method according to the current elastic parameter model; designing a loss function according to the observed Rayleigh surface wave dispersion curve and the theoretically calculated Rayleigh surface wave dispersion curve, and calculating and judging whether the loss function reaches a set threshold value or converges to a minimum value; if yes, outputting a current near-surface shear wave velocity model; if the conditions are not met, updating the shear wave velocity model by adopting a quasi-Newton method; and outputting the near-surface shear wave velocity model and the sensitive function of the Rayleigh surface wave frequency dispersion curve to the anisotropic elastic parameter after the loss function meets the condition.

The invention relates to the technical field of underwater detection, and discloses an underwater comprehensive detection system. The system collects multi-dimensional acoustic data including sound wave reflection intensity, propagation time delay and frequency dispersion characteristics of a target water area through an underwater sonar array; dividing the detection area into a plurality of layered units according to a water attenuation coefficient and a substrate reflection characteristic of the acoustic data, and extracting an environment intrinsic parameter of each layered unit; constructing an acoustic propagation path model based on the environmental intrinsic parameters, and generating adaptive filtering parameters in combination with a preset noise suppression strategy; calling sonar array hardware configuration data, matching filtering parameters with an array beam forming mode, and calculating a detection sensitivity threshold value of each layered unit; and integrating the sensitivity threshold and the acoustic data, generating a three-dimensional acoustic characteristic spectrum of the target water area, and marking the space coordinates and confidence level of the abnormal area. The system can improve the comprehensiveness and accuracy of underwater detection, and meets the requirement of high-precision detection.

The invention provides an airfield pavement detection method based on an earthquake background noise imaging technology, and relates to the technical field of airfield pavement detection. Comprising the following steps: acquiring seismic background noise data of an airport pavement to be measured; preprocessing the seismic background noise data to obtain preprocessed noise data; carrying out cross-correlation calculation on the preprocessed noise data and carrying out empirical Green function extraction; according to the empirical Green function, a surface wave group velocity frequency dispersion curve is extracted by adopting spatial autocorrelation and multiple filtering methods; inverting shear wave velocity distribution of each layer of the pavement based on the surface wave group velocity dispersion curve, and constructing a three-dimensional velocity model; determining a shear wave velocity distribution diagram according to the three-dimensional velocity model; and determining a detection result of the airfield pavement to be detected according to the transverse wave velocity distribution diagram. According to the invention, the problems of low detection precision and poor real-time performance of a common detection technology in the prior art are solved.

The invention discloses a thin plate residual stress detection method and system based on a thickness resonance mode, and relates to the technical field of stress detection, and the method comprises the steps: obtaining a frequency dispersion curve of a to-be-detected thin plate, and determining the theoretical thickness resonance frequency of the S1 thickness resonance mode according to the frequency dispersion curve; carrying out a stress coefficient calibration experiment on the to-be-tested thin plate, and determining experimental Lamb wave A-scanning data of different stresses; determining a stress-thickness resonance normalized amplitude curve associated with a theoretical thickness resonance frequency according to the resonance wave time domain signal of the A-scan data of each experimental Lamb wave; exciting a Lamb wave signal to a preset excitation point of the thin plate to be measured, and determining corresponding actually measured Lamb wave A-scan data; and determining the residual stress of the to-be-measured thin plate by adopting a stress-thickness resonance normalized amplitude curve based on an actually measured thickness resonance normalized amplitude determined by actually measured Lamb wave A-scanning data. The residual stress of the thin plate is measured by using the characteristic that the amplitude in the S1 thickness resonance mode is gradually increased along with the change of the stress value, and the detection efficiency is improved.

The invention discloses a non-destructive testing stress evaluation method based on a nonlinear ultrasonic Lamb wave static component, and belongs to the technical field of stress detection, and the method comprises the following steps: S1, constructing a Rayleigh-Lamb equation introducing an elastomer nonlinear theory, and further determining a Lamb wave frequency dispersion curve of a to-be-detected plate, the excitation frequency and the excitation mode of the excitation source are determined according to the Lamb wave frequency dispersion curve; s2, exciting lamb waves for determining excitation frequency and excitation mode at one end of the stress detection area of the plate to be detected, and receiving and extracting corresponding signals through the other end of the stress detection area; s3, inverting the phase of the extracted signal, and exciting and receiving the inverted signal again; and S4, processing the received signal, and calculating an ultrasonic nonlinear coefficient as an evaluation parameter of the stress state of the plate to be detected. According to the invention, the selection of the fundamental wave frequency and mode is more flexible, the related parameters of the high-attenuation material can be measured, and the early damage and stress state in the material can be effectively evaluated.

The invention discloses an aviation composite material-oriented ultrasonic guided wave damage rapid imaging method, which relates to the field of nondestructive testing, and comprises the following steps: calculating a frequency dispersion curve according to material parameters of a carbon fiber composite material plate, and obtaining an ultrasonic optimal excitation angle and an ultrasonic guided wave propagation mode; scanning and collecting two groups of ultrasonic guided wave signals in the orthogonal direction in sequence; decomposing the guided wave signal, and obtaining a reconstructed ultrasonic guided wave signal after extracting a target component according to the size of an energy entropy value; calculating time-frequency information and energy of the signal, and estimating the damage probability in the scanning path by combining a damage index; embedding the expansion kernel convolution and the double probability distribution function into the damage index curve to respectively realize the reinforcement of the damage index and the sharpening of the edge; and expanding the two groups of damage index curves in the orthogonal direction into a two-dimensional damage matrix, and imaging according to a composite path cross imaging method, thereby finally realizing damage positioning imaging of the carbon fiber composite material plate.

The embodiment of the invention provides a full waveform inversion method based on surface wave dispersion inversion driving, a control device and a storage medium, and belongs to the technical field of seismic inversion. The full-waveform inversion method comprises the following steps: acquiring a Rayleigh surface wave observation signal through a preset detection point according to a three-station interference method; according to one-dimensional surface wave frequency dispersion inversion, through the obtained Rayleigh surface wave observation signal, obtaining a corresponding one-dimensional shear wave velocity representing a central area of the detection point pair; constructing a corresponding three-dimensional velocity model based on the one-dimensional shear wave velocity body; and performing full-waveform inversion on the three-dimensional velocity model to obtain a full-waveform inversion result of the region. According to the embodiment of the invention, aiming at passive source seismic signals, based on a three-station interference method, the high-signal-to-noise-ratio Rayleigh surface wave signals among the one-dimensional linear stations are extracted and enhanced, the surface wave signals are used as the input of the whole inversion process, the inversion result is not influenced by background noise quality, and the precision is higher.

The invention relates to the technical field of electrical engineering and intelligent fault diagnosis, and discloses a water pump motor fault diagnosis method and system based on current harmonic characteristics, and the method comprises the steps: collecting stator current, rotating speed and load signals; generating an alpha-beta current component through Clark transformation, constructing an analytic signal, extracting an instantaneous phase, and calculating an instantaneous frequency; a mapping relation is established in combination with the rotating speed, and the current signals are resampled to eliminate frequency dispersion; obtaining a high-resolution harmonic energy distribution diagram by adopting multi-scale synchronous compression wavelet transform; and extracting an energy concentration ratio, a peak offset and a bandwidth expansion coefficient in the characteristic frequency band, inputting the energy concentration ratio, the peak offset and the bandwidth expansion coefficient into the pre-trained multi-layer perceptron classifier, and outputting a fault type. According to the method, through high-precision time-frequency focusing and multi-dimensional feature fusion, the fault recognition accuracy and robustness are remarkably improved, and online diagnosis of multiple typical faults can be achieved only through current signals.

The invention provides an ocean internal wave data acquisition method, medium and system, and belongs to the technical field of ocean hydrological observation.The ocean internal wave data acquisition method comprises the steps that an acoustic Doppler flow velocity profiler is used for acquiring water body movement data, a temperature-salinity-depth profiler is used for acquiring seawater parameters, and meanwhile a satellite altimeter and drifting buoy data are combined. Performing time-frequency analysis on the water body motion data, and obtaining internal wave candidate data by using band-pass filtering; and constructing an internal wave mathematical equation set comprising a hydromechanics basic equation, buoyancy frequency, a frequency dispersion relation and the like, and verifying and screening out effective data. And inputting the effective data into a pre-trained classification model to determine an internal wave type, finally extracting a key waveform segment through a preset extraction equation set, and generating and outputting internal wave characteristic waveform data. According to the method, multi-source observation data and a mathematical physical model are combined, identification, classification and feature extraction of the ocean internal waves are realized, and the problem that a data acquisition method capable of effectively extracting effective signals of the ocean internal waves and accurately identifying the features of the internal waves is lacked at present is solved.

The present invention discloses a method and a system for enhancing an ultrasonic guided wave signal based on multi-modal recognition and fusion. The method includes: solving an ultrasonic guided wave frequency dispersion curve of a detected structure, selecting target detection modes, and setting the strongest energy mode as the main mode; forming a frequency dispersion dictionary and obtaining sub-signals, then converting their abscissa axes from time to signal source distances; grouping sub-signals with similar source distances, classifying them as single modal or main mode conversion sub-signals, and removing interference signals; and resampling the classified sub-signals at a uniform frequency, extracting half-wave envelope signals, and superposing them within each source group to obtain an enhanced target signal

The invention relates to the technical field of oil and gas geophysical exploration, and particularly discloses a tight sandstone gas reservoir fluid mobility gradient attribute prediction method and system.The method comprises the steps that a reflection coefficient expression containing a fluid mobility item is constructed, and a formula for calculating fluid mobility through frequency dispersion attributes is deduced; constructing a fluid mobility gradient attribute related to the frequency and the incident angle of the seismic wave; the method comprises the following steps: establishing a double-pore rock physical model, generating a synthetic seismic record, applying frequency variation AVO inversion to the synthetic seismic record, and extracting a bulk modulus dispersion attribute and a shear modulus dispersion attribute; and calculating the fluid fluidity changing along with the frequency and the incident angle, and calculating the gradient attribute of the fluid fluidity based on a gradient attribute calculation formula and the fluid fluidity. According to the method, seismic wave frequency dispersion and attenuation response caused by permeability and gas saturation are fully utilized, the seismic gradient attribute of the fluid fluidity and the calculation method are constructed, and high-precision prediction of the fluid fluidity by applying seismic signal elasticity and frequency dispersion rock physical information is realized.

The invention discloses an arc suppression coil grounding fault positioning method based on a transformer substation line protection device, particularly relates to the technical field of system fault measurement, and is used for solving the problem of insufficient positioning precision caused by neglecting the nonlinear characteristic of a fault point arc channel in an existing fault positioning method. A specific frequency current signal is injected into a fault phase, the phase relation between fundamental wave and harmonic wave components in current collected by a line protection device is analyzed to obtain a phase coherence coefficient, a fault line distribution parameter model is established to obtain theoretical reference information, and a spatial gradient sequence is generated by calculating actual measurement and theoretical spatial entropy values. Identifying a line section corresponding to the abnormal abrupt change point, and finally determining a grounding fault point according to the spatial position of the line section with significant difference. The method can effectively overcome the influence of nonlinear attenuation and frequency dispersion effect on the positioning precision, and achieves the precise measurement and positioning of a single-phase grounding fault.

The invention provides a surface wave information-based near-surface formation longitudinal wave velocity inversion method. The surface wave information-based near-surface formation longitudinal wave velocity inversion method comprises the following steps of: 1, extracting surface wave frequency dispersion data through a phase shift method; 2, according to the frequency dispersion curve, direct inversion is carried out to obtain the near-surface shear wave speed and thickness; step 3, calculating a W-D curve and a W / D-D curve; and 4, adding the W-D data and the W / D-D data into an objective function, and carrying out longitudinal wave velocity direct inversion. According to the near-surface formation longitudinal wave velocity inversion method based on the surface wave information, direct inversion of the near-surface formation longitudinal wave velocity can be achieved, information such as the transverse wave velocity, the formation thickness, the longitudinal wave velocity and the Poisson's ratio is obtained in the inversion process, and powerful research basis and support are provided for application of the surface wave information in oil exploration and engineering exploration.

The invention discloses a cable fault detection method based on a data transmission current differential signal, and relates to the technical field of cable fault point positioning, and the method comprises the steps: obtaining a cable channel fault feature vector through calculating the time delay domain feature and frequency domain envelope distortion degree of an enhanced differential signal at a head end and a tail end; and inputting the cable channel fault feature vector into the trained baseline model to identify whether the to-be-detected cable has a fault, when identifying that the to-be-detected cable has a fault, carrying out joint time-frequency analysis on the enhanced differential signals at the head end and the tail end, obtaining sudden change features at the head end and the tail end, solving relative time delay data of the sudden change features at the head end and the tail end on a time-frequency plane, and determining the fault of the to-be-detected cable. And calculating the accurate position of the fault point of the to-be-detected cable in combination with a frequency variation propagation model. According to the method, the positioning deviation caused by the frequency dispersion characteristic of the cable is effectively corrected through a double-end cooperative detection method, and the accuracy of fault positioning is improved.

The invention discloses a frequency dispersion curve automatic extraction method based on deep learning and a related device, and relates to the technical field of geophysics and underground structure exploration, and the method comprises the steps: obtaining station pair data; performing cross-correlation processing on the station pair data to obtain a plurality of pieces of cross-correlation data; performing data processing on each piece of cross-correlation data to obtain processed cross-correlation data; according to the processed cross-correlation data, a tau-p conversion technology is adopted to obtain a frequency dispersion energy diagram; performing image recognition on the frequency dispersion energy diagram based on a deep learning model to obtain a frequency dispersion curve; the frequency dispersion curve is used for displaying the change rule of the frequency dispersion characteristic along with the periodic change speed; the deep learning model adopts an encoder-decoder framework, and the depth learning model adopts an encoder-decoder framework; in the deep learning model, a pooling layer is replaced by convolution with the step length being two, and up-sampling is carried out by adopting transposed convolution. Based on the method provided by the invention, the frequency dispersion curve can be efficiently and accurately extracted.

The invention provides a seismic trace gather far offset energy preserving processing method, which comprises the following steps of: 1, decompiling field seismic data, and performing first arrival picking and trace gather extraction processing; 2, performing high-order dynamic correction processing on the extracted gather data to improve the influence of conventional dynamic correction stretching on the far offset; step 3, performing space-time variation cutting on gather first arrival waves and interference waves by adopting control points; step 4, performing offset resolution improvement processing on the gather data, and further improving the frequency dispersion problem of the far-offset data; and step 5, carrying out deconvolution, superposition and migration processing on the far-offset information preserving gather to obtain far-offset energy preserving seismic result data. According to the seismic trace gather far-offset energy maintaining processing method, recovery and maintenance of far-offset energy in seismic trace gather data can be realized, the imaging quality of seismic data of middle and shallow layers is improved, and recovery and maintenance of far-offset information are realized.

The invention belongs to the technical field of surface wave frequency dispersion inversion, and particularly discloses a surface wave multi-modal frequency dispersion curve probability inversion method based on modal self-matching, which comprises the following steps of: dividing apparent frequency dispersion data points into two types, namely a basic modal data set and a higher modal data set; constructing a Bayesian equation for inverting multi-modal dispersion data in a non-likelihood inference method framework; establishing the similarity between the distance measurement quantized frequency dispersion data and the simulation sample, and appointing a method suitable for sampling; and representing the uncertainty of a multi-modal dispersion data inversion result (namely a shear wave velocity profile) based on the obtained posterior sample. According to the method, the uncertainty of the shear wave velocity profile obtained by inverting the Rayleigh wave multi-mode dispersion curve can be well quantified, the identifiability of the shear wave velocity profile is improved, and a wrong inversion result caused by misidentification of the mode is avoided by automatically matching the mode number.

The invention discloses a single-node water leakage position positioning method based on distance parameter inversion, and the method comprises the steps: firstly installing a noise sensor in an experiment pipeline, and repeatedly collecting signal data through changing the flow of fluid in the pipeline and simulating the position parameters of a leakage point from the noise sensor in a to-be-detected experiment pipeline operation state; decomposing and reconstructing a sound signal acquired by the sensor by using a self-adaptive variational mode decomposition method; analyzing the reconstructed collected sound data, constructing a low-frequency dispersion equation based on an elastic constitutive relation and a global matrix method, solving group velocity and phase velocity of modal waves in a low-frequency band range, namely waveguide invariants, and constructing a relation between a frequency wave number relation and a distance by utilizing the waveguide invariants; a distance parameter # imgabs0 # and a frequency dispersion parameter # imgabs1 # are introduced, frequency dispersion elimination transformation is established, the distance of a leakage point is calculated, and the defect that the detection range is small due to the fact that medium-high frequency signals are collected in acoustic emission detection is overcome.

The invention provides a processing method and device for ocean P guided wave removal and mode separation. The method comprises the following steps: determining a frequency dispersion energy spectrum corresponding to a marine seismic gather in a frequency-speed domain based on an original seismic record corresponding to the marine seismic gather in a time-space domain; and removing frequency dispersion energy except the specified P guided wave frequency dispersion mode in the frequency dispersion energy spectrum to obtain a target frequency dispersion energy spectrum. And inverting the target frequency dispersion energy spectrum to a time-space domain to obtain a target seismic record corresponding to the specified P guided wave frequency dispersion mode. And based on the original seismic record and the target seismic record, determining seismic data after the P guided wave frequency dispersion mode is removed. Wherein the extracted P guided wave seismic data is used for inversion of a frequency dispersion curve and a waveform so as to realize high-precision detection of a seabed longitudinal wave velocity structure or marine geological survey; the seismic data after the P guided wave frequency dispersion mode is removed is used for analyzing the influence of the P guided wave on the seismic signal and the amplitude spectrum of the seismic signal, and de-noised seismic data is provided for migration imaging of the reflected wave.

The invention discloses a microwave photon beam forming network architecture based on a switch switching type optical adjustable true delay line and a phased array radar system thereof. According to the framework, microwave signals are modulated in an optical domain, and the characteristics of a plurality of adjustable delay paths in a single-channel switch switching type delay line are utilized, so that delay difference adjustment of multiple paths of optical signals is realized, the number of delay lines and delay units is greatly reduced, and meanwhile, high-precision and broadband beam-strabismus-free beam forming is supported; through two-stage or multi-stage delay configuration, the network can flexibly meet the broadband delay compensation requirements of different array antenna units, has low complexity and strong dynamic reconfigurable capability, is suitable for realization of a large-scale photonic integrated chip, reduces the number of delay lines by about 50%, does not generate frequency dispersion, and is suitable for large-scale photonic integrated chips. The system complexity, the cost and the power consumption can be remarkably reduced, and the method is particularly suitable for broadband phased array systems of millimeter waves, satellite communication, radar detection and the like.

The invention discloses a method and a device for inverting a high-order frequency dispersion curve of a seafloor node Schelt wave. The method comprises the following steps: determining the distance between reference points according to seismic data arrangement information, and setting a plurality of reference points on a target section where a seismic survey line is located; according to the maximum offset distance and the minimum offset distance, common receiving point sub-gathers are screened from a common receiving point Schelt channel set of each seabed node, sub-gathers are intercepted from the common receiving point sub-gathers according to the reference point position information and the maximum distance, and the sub-gathers with the length not smaller than the minimum length form the gathers of the reference points; determining a frequency dispersion energy spectrum of each sub-gather in the reference point gather to obtain a superposed frequency dispersion energy spectrum of the reference point; and picking up a high-order frequency dispersion curve by superposing a frequency dispersion energy spectrum, and carrying out seismic inversion modeling. According to the method, through screening of available trace gathers of reference points and determination and superposition of frequency dispersion energy spectrums, an energy-enhanced superposed frequency dispersion energy spectrum is obtained, so that high-resolution seismic modeling can be realized based on extracted high-order frequency dispersion curve inversion.

The invention provides a micro-motion exploration data processing method and system for automatic partitioning of a two-dimensional dense array, a medium, equipment and a product, and relates to the technical field of micro-motion exploration, and the method comprises the steps: obtaining the spatial position coordinates of stations in the two-dimensional array and the waveform data of the stations, and carrying out the batch preprocessing of the waveform data of the stations; based on the spatial position coordinates of the stations, performing k nearest neighbor rolling partition on the stations; carrying out frequency dispersion energy spectrum calculation on the stations in each partition based on the station waveform data after batch preprocessing, and picking up the frequency dispersion energy spectrum by adopting an automatic correction picking-up method; a data processing modular workflow for data import, data preprocessing, station partitioning and frequency dispersion calculation is established for modular processing. According to the method, the data processing efficiency and effect of two-dimensional dense array micro-motion exploration can be remarkably improved.

The invention discloses a seismic wave velocity change analysis method under a hydraulic fracturing condition, and belongs to the technical field of seismic wave propagation analysis. The method comprises the following steps: S1, acquiring data by using a plurality of seismic stations and removing transient signals by using a long and short window method; s2, calculating a cross-correlation function between the two stations; s3, extracting a tail wave signal and estimating relative velocity change by using mobile window cross-spectrum analysis; s4, extracting a group velocity frequency dispersion curve based on a cross-correlation function, and constructing a two-dimensional velocity model before and after fracturing; and S5, generating a speed image through inversion, and calculating a difference image to reveal speed change characteristics. According to the method, the tail wave sensitivity and the moving window cross-spectrum analysis are combined, the speed change and the anisotropy characteristics of the speed change are accurately quantified, the method is suitable for the complex geological environment, and a new interpretation framework is provided for the influence of hydraulic fracturing on the underground structure.

The invention belongs to the field of surface acoustic wave filter device manufacturing, and particularly relates to a high-consistency single crystal film surface acoustic wave filter and a preparation method thereof, and the preparation method comprises the following steps: spin-coating an anti-reflection film on the upper surface of a single crystal film substrate; spin-coating photoresist on the anti-reflection film and carrying out exposure treatment to obtain a first sample; dissolving the photoresist corresponding to the target metal film pattern through developing operation, and dissolving the anti-reflection film corresponding to the dissolved photoresist to obtain a second sample; and depositing a metal film on the upper surface of the second sample, and then stripping all the photoresist and the anti-reflection film to obtain the high-consistency single crystal film surface acoustic wave filter. According to the invention, the finger strip morphology of the single crystal thin film wafer and the frequency dispersibility in the filter sheet are improved through spin coating of the anti-reflection film.

The invention is suitable for the technical field of geophysical exploration, and provides a rock physics-driven time-frequency domain longitudinal wave velocity dispersion attribute prediction method, which comprises the following steps of: establishing a rock physics model; under the driving of the rock physical model, inverting the porosity of the microfractures in the well, calculating the skeleton elastic modulus of the rock containing the fractures, and predicting a frequency-dependent longitudinal wave velocity logging curve; constructing a time-frequency domain longitudinal wave velocity seismic inversion initial model; constructing a TF-AVO theoretical formula, developing a time-frequency domain longitudinal wave velocity seismic inversion method based on an L-BFGS algorithm, and performing longitudinal wave velocity inversion by taking the initial model as prior information; analyzing the relative change of the frequency-varying longitudinal wave speed under different frequencies, and quantitatively predicting the frequency dispersion attribute of the longitudinal wave speed; and on the basis of logging data, calibrating a longitudinal wave velocity dispersion attribute prediction result, and carrying out reservoir oil and gas detection. The method has higher precision and resolution, the stability and reliability of longitudinal wave velocity dispersion attribute prediction are remarkably improved, and the dependence on strong amplitude response is overcome.

The invention provides a far and near field wallboard leakage source full-field positioning method based on a linear acoustic array, belongs to the field of high-precision positioning, and solves the problems that a wallboard structure leakage source positioning scheme needs more sensor arrays and is inconvenient to use actually, and the calculation amount required for ensuring the precision of a positioning algorithm is large and is not beneficial to real-time monitoring. Comprising the following steps: step 1, determining a frequency dispersion curve according to a structure and a material of a detected wallboard, extracting a signal main frequency, and determining an angle threshold value according to an array structure and two selected sub-arrays; 2, calculating a positioning result difference value of the two sub-arrays, and comparing the positioning result difference value with a threshold value; 3, if the positioning result difference value is not larger than the threshold value, far-field positioning is carried out, far-field positioning is completed through the full array, and a far-field positioning result is output; 4, if the positioning result difference value is smaller than the threshold value, near-field positioning is carried out, and an improved 2Dmuic algorithm is adopted to process the full-array signals to obtain a near-field positioning result.

The invention relates to a physical condition embedded seismic surface wave intelligent inversion method and device and a medium, and the method comprises the steps: obtaining the seismic surface wave data of an active source or a passive source to be inverted, and carrying out the extraction through a frequency dispersion analysis method, and obtaining an observation frequency dispersion curve of the seismic surface wave data; constructing an initial shear wave velocity model, obtaining a theoretical frequency dispersion curve and a sensitivity matrix of the initial shear wave velocity model, and calculating physical condition embedding of the observation frequency dispersion curve based on the theoretical frequency dispersion curve and the sensitivity matrix of the theoretical frequency dispersion curve; based on an initial shear wave velocity model and physical condition embedding, an inversion model is used for iterative solution to obtain an inversion shear wave velocity model, and the device and the medium are used for implementing the method. Compared with the prior art, the method has the advantages that the problem that an initial model is easy to fall into a local minimum value due to manual selection is avoided, the inversion precision of the seismic surface waves is improved, the limitation of fixed input or output dimensions is eliminated, and the applicability of the inversion method in processing actual seismic surface wave data is remarkably improved.