241 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 discloses a shield tunnel active and passive source combined geological detection method and system. The method comprises the following steps: acquiring an active source seismic wave reflection signal and a passive source acoustic wave reflection signal; according to the active source seismic wave reflection signal, obtaining an active source geological detection imaging result by adopting a longitudinal and transverse wave combined imaging principle; according to the passive source sound wave reflection signal, a frequency dispersion extraction-shear wave velocity inversion method fusing spatial autocorrelation and a half-wavelength model is adopted to obtain a passive source geological exploration imaging result; and taking an active source geological detection imaging result as a main result, taking a passive source geological detection imaging result as an auxiliary result, and combining adaptive adjustment coefficients between the two results to obtain an unfavorable geological risk level of the to-be-detected area. Shield tunneling vibration noise with high energy and wide frequency band is introduced as a passive detection source, the detection depth and resolution are improved, and support is provided for accurate geological imaging.

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 discloses a stratigraphic structure scanning method based on a single-station six-component seismograph. The stratigraphic structure scanning method comprises the following steps: S1, selecting one or more measuring points in a target area; a single-station six-component seismograph is installed at each measuring point to acquire a passive source signal; s2, calculating horizontal components of translation and rotation according to passive source signal six-component data of the measuring point; s3, according to component data characteristics in the six-component data of the passive source signal of the measuring point and relation characteristics among the component data, extracting a phase velocity frequency dispersion curve at the measuring point, and obtaining a quantitative relation between the phase velocity and the frequency; s4, according to the phase velocity frequency dispersion curve and the quantitative relation, calculating relative velocities at different frequency points of the corresponding measuring points; s5, establishing a mapping relation between the relative speed and the depth according to the quantitative relation, and obtaining an underground structure of the corresponding measuring point; and S6, according to the underground structure of each measuring point of the target area, completing stratigraphic profile information drawing or underground three-dimensional structure inversion of the target area.

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 relates to the technical field of applied geophysics, in particular to a logging-while-drilling shear wave velocity processing method, device and equipment and a storage medium. The method comprises the following steps: dividing a parameter range and a step length, determining a stratum parameter combination, and taking the stratum parameter combination as a data set sample feature; constructing a frequency dispersion data set according to the obtained data set sample labels; performing data cleaning on the frequency dispersion data set, and correcting error samples in the data set; establishing a neural network, training a frequency dispersion data set, and verifying the feasibility of the model; an inversion objective function is established through a joint inversion method, the shear wave velocity is inversed by adopting a low frequency band, and the mud velocity is inversed by adopting a high frequency band; an optimization method is added, so that the number of forward calculation times in inversion is reduced, and the inversion efficiency is improved; and replacing the current depth point with the next depth point, and returning to execute the optimization method until the transverse wave velocity processing of the full depth section is completed. According to the method, the rapid frequency dispersion correction under the well logging while drilling is realized, the calculation efficiency is improved, and the calculation cost is saved.

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 discloses a frequency dispersion inversion method and apparatus, and a computing device. The method comprises the steps of obtaining target frequency dispersion data obtained based on acoustic logging data; inputting any group of candidate stratum parameter values in the candidate parameter space into an inversion model obtained by pre-training, obtaining candidate theoretical frequency dispersion data corresponding to the group of candidate stratum parameter values output by the inversion model, and calculating a fitting residual error corresponding to the group of candidate stratum parameter values in combination with the candidate theoretical frequency dispersion data and the target frequency dispersion data; identifying a target stratum parameter value corresponding to the target frequency dispersion data from the candidate stratum parameter values contained in the candidate parameter space according to fitting residual errors corresponding to the candidate stratum parameter values in the candidate parameter space; and inputting the target stratum parameter value into the inversion model, and obtaining target theoretical frequency dispersion data corresponding to the target frequency dispersion data output by the inversion model. By adopting the scheme, the frequency dispersion inversion efficiency can be greatly improved.

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 relates to a frequency dispersion curve inversion method based on a Bi-LSTM network, a medium and equipment, and belongs to the technical field of geophysical exploration data processing. According to the method, firstly, a Bi-LSTM network is constructed, two independent conventional LSTM networks in different directions are spliced together by the network to serve as a main body network unit, and respective outputs of the two networks are spliced to serve as final output, so that the network can simultaneously acquire previous text information at a past moment and following text information at a future moment; therefore, the method has a better effect when processing the sequence data. Besides, physical constraints are introduced in the training process, firstly, a real frequency dispersion curve serves as input, a shear wave speed model is predicted through a network, then the frequency dispersion curves are positively calculated through the shear wave speed model, and the difference of the two frequency dispersion curves is introduced into a loss function in a weight mode to serve as the physical constraints. And the prediction precision and stability of the network are improved.

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 discloses an ultrasonic guided wave mode separation method based on frequency dispersion compensation and blind source separation, and relates to the field of ultrasonic guided wave mode separation and the field of ultrasonic guided wave nondestructive testing. The method comprises the following steps: extracting frequency dispersion characteristic parameters of a Lamb wave modal from response Lamb waves with known propagation distances through a particle swarm optimization algorithm; performing single-mode frequency dispersion compensation on the two actually measured signals according to the extracted parameters to enable the two signals to return to the same distance; lamb wave signals with the same distance and different superposition conditions are processed through a JADE blind source separation method; and performing sequential compensation and separation on different modes to obtain single-mode signals and realize multi-mode signal separation. According to the invention, the frequency dispersion compensation method and the blind source separation method are combined and applied to the research on the multi-mode Lamb wave signal mode separation problem, and the complex multi-mode Lamb wave signals can be effectively separated.

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 multi-objective optimization synergistic orthotropic steel bridge deck slab damage acoustic emission positioning method. Comprising the steps that 1, acoustic emission signals of the orthotropic steel bridge deck in the working state are collected through acoustic emission sensors on the four vertexes of a rectangular area to be detected; 2, deducing a shortest path formula for transmitting the acoustic emission signals from potential damage sources at different positions to the acoustic emission sensor; 3, the arrival time of a first arrival mode of the acoustic emission signals is extracted according to the Akaike information criterion, a frequency dispersion curve of the acoustic emission signals is obtained, the characteristic frequencies and wave velocities of the first arrival mode and the A0 mode are determined respectively, and the arrival time of the A0 mode of the acoustic emission signals is determined; 4, establishing a multi-objective optimization model for orthotropic steel bridge deck damage positioning according to the determined multi-mode arrival time and wave velocity parameters; and 5, solving the multi-objective optimization model through a hierarchical sequence method by taking the first layer of the multi-objective optimization model as an important objective function, and evaluating the position of the damage. According to the invention, the damage position can be accurately identified.

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.