580 results about "Seismic wave" patented technology

The invention discloses a coal seam passive source seismic survey system and method based on deep learning, and relates to the technical field of coal mining safety monitoring and early warning, and the method comprises the following steps: S1, collecting the passive source seismic data of a coal seam area; s2, deep fusion features are extracted; s3, constructing a semi-supervised self-attention prediction network model; s4, extracting coal seam structure prediction parameters; s5, the corrected coal seam structure parameters are extracted; s6, constructing a fast seismic wave forward model, and calculating and outputting an initial model of the coal seam underground structure; s7, constructing a Transform optimization network, and extracting a depth feature vector; and S8, constructing a coal seam structure inversion model, and training iteration by using the improved batch depth Bayesian optimization algorithm. The method overcomes the limitation of manual analysis and slow response in a traditional coal seam seismic survey method, and provides an efficient and accurate solution for safe production of a coal mine.

The invention discloses a fault co-seismic sliding surface inversion method and system based on Beidou and artificial intelligence. The method comprises the steps of collecting Beidou data and seismic waveform data of a target area in real time, and performing preprocessing to extract co-seismic displacement and waveform features; fusing the Beidou deformation features and the seismic wave features to form a multi-modal feature vector; a fault prediction model is constructed based on a graph neural network, forward modeling and historical earthquake example data training are utilized, and multi-modal features are input to obtain preliminary fault sliding distribution prediction; rapid optimization under physical constraint is carried out through the elastic dislocation model, and a final fault sliding model conforming to the geophysical law is obtained; finally, uncertainty quantification is carried out, and a visual product of the dynamic process including sliding distribution, seismic moments and fault deformation is generated. According to the system, full-process automatic processing is achieved through cooperation of all the units, the inversion speed, precision and physical credibility are improved, and reliable support is provided for earthquake emergency response and disaster assessment.

The invention relates to the technical field of tunnel construction, and discloses a coal mine goaf karst tunnel construction method which comprises the following steps: S1, performing three-dimensional scanning on the axis and the periphery of a tunnel by adopting a high-frequency geological radar in combination with aerial survey of an unmanned aerial vehicle, and accurately positioning the boundary of a goaf, the development form of a karst cave and filler distribution; and S2, integrating a seismic wave reflection method, drilling and coring data and a geological sketch result, constructing a three-dimensional geological model, and dynamically predicting a potential water inrush and mud inrush risk area. According to the method, a high-frequency geological radar is combined with aerial survey of an unmanned aerial vehicle, three-dimensional scanning is conducted on the axis and the periphery of a tunnel, geological radar data, a point cloud model and tunnel design BIM are integrated, the boundary of a goaf (the error is smaller than or equal to 0.3 m) and the karst cave form are marked, and the collapse risk level is predicted based on rock mass mechanical parameters (compressive strength and fracture density) and hydrological data (seepage paths). Therefore, the method has the advantages of advanced detection, multi-source data fusion and the like, and the resolution of geological forecast is improved.

A 3D inversion method of DC method using seismic data constraints is disclosed, comprising processing of seismic data and inversion processing of resistivity data; by utilizing seismic wave interval velocity information to constrain the high-density electrical inversion, which can play a complementary role to a certain extent, it is beneficial to supplement the resolution of resistivity inversion with 3D seismic image information, reflect a boundary of subsurface electrical anomalous body, and further characterizes the boundary characteristics of anomalous body through comprehensive geological-geophysical analysis. Seismic data constraints are applied to 3D resistivity inversion, performing numerical simulation and inversion of electrical data under undulating terrain using the finite volume method and Gauss-Newton inversion method. Furthermore, the seismic anisotropic velocity tensor constraint is introduced for inversion to mitigate the non-uniqueness inherent in single-method inversion, yielding a more accurate 3D subsurface electrical structure and improving the resolution of longitudinal boundaries.

The invention relates to a transient electromagnetic and seismic wave multi-mode joint inversion imaging method based on physical information Transform, and belongs to the crossing field of geophysical exploration and artificial intelligence. Comprising the following steps: carrying out anomaly detection, interpolation, filtering and normalization preprocessing on transient electromagnetic and seismic wave original data; extracting features representing electrical property, elasticity and cross physical significance; serializing the spatial data through a gridding and alternating fusion strategy, and constructing an enhanced code fusing absolute and relative positions and physical attributes; a physically constrained encoder-decoder architecture is designed to carry out multi-scale forward modeling-inversion; and quantizing the uncertainty of an inversion result by adopting a Bayesian Monte Carlo method, and generating a confidence map. According to the method, through physical rule driving and multi-modal depth complementary fusion, the fine recognition capability and interpretation reliability of hidden disaster-causing geologic bodies such as underground goaf and collapse columns are effectively improved while the physical consistency of data is kept.

The invention provides a geological structure intelligent detection system and method for a deep special space, and relates to the technical field of geological exploration. The geological structure intelligent detection system and method for the deep special space comprises the steps that S1, a distributed sensor network is deployed in the deep special space, and seismic wave, electromagnetic field, sound wave, temperature and strain multi-physical field original detection data are synchronously collected; constructing a noise channel model based on a quantum computing principle, and modeling the original detection data; a quantum inspired adaptive filtering algorithm is applied, and noise characteristics are estimated in real time through variational optimization. Through synchronous acquisition of a distributed multi-physics field sensor network and an adaptive filtering technology of quantum inspiration, effective enhancement of weak characteristic signals is realized in a strong noise environment, and the signal-to-noise ratio and the target geological structure identification precision are significantly improved; and a neural network inversion model is combined with physical information constraint.

The invention discloses a stratigraphic water content layering inversion method based on a shallow seismic full waveform, and relates to the technical field of geophysical exploration data processing, and the method comprises the following steps: 1, under the same survey line condition, synchronously obtaining a seismic wave full waveform, complex impedance and an induced polarization frequency spectrum; 2, constructing a layered initial model containing a layer boundary line and an in-layer water content initial value; based on the layered initial model, executing dual-domain quantile alignment interface keeping iteration until convergence, and obtaining a final layer boundary line and an in-layer water content field; the double-domain quantile alignment interface maintaining iteration comprises the following steps: updating an in-layer moisture content field and a layer boundary line according to a seismic wave full waveform; and performing total variation regularization processing on the updated in-layer water content field to maintain the transition characteristic of the layer boundary line. According to the method, an efficient and reliable solution with actual guidance value is provided for mineral resource exploration, geological structure detection, groundwater survey and engineering geology evaluation.

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 a tunnel cross-sectional image analysis method based on image processing, and aims to solve the problems that a surface image is not clear in correspondence with a transient seismic wave method, a geological radar and a resistivity imaging section space, and anomalies at a certain distance in front are difficult to map to a tunnel face. According to the method, anisotropic reforming is carried out by adopting a Fourier neural operator, cross-modal Transform registration of a micro attention mask based on sector geometry, curve mileage and section polar coordinate position coding is combined, analytic geometry mapping and uncertainty propagation are matched, tunnel face structure traces and water seepage texture evidences are fused, and the tunnel face structure traces and the water seepage texture evidences are combined. The technical effects of accurate positioning of abnormity on the tunnel face, position confidence range estimation, risk grading early warning, stripe artifact suppression, abnormal boundary reservation and output of structured results of mileage stake numbers, azimuth angles, distance intervals and the like are achieved.

The invention discloses a seismic wave velocity model inversion method based on time-space coupling deep learning, and the method achieves a time-space coupling mechanism through a Fourier neural operator framework of a wavelet transform-attention mechanism, and supports the reconstruction of a spatial two-dimensional velocity model from a time sequence track of multiple seismic sources. Firstly, the local time-frequency representation of each seismic time-domain trajectory is extracted by adopting continuous wavelet transform, and then a wavelet time-frequency spectrogram is coded through a convolution feature extractor. Then, information from multiple sources is fused at each receiver point location through a multi-head attention mechanism, enhancing correlation between multiple sources. And finally, projecting the fused features into a two-dimensional Fourier neural operator to efficiently learn space mapping and reconstruct a bottom-layer velocity model based on sound velocity. According to the method, the time sequence characteristic and the spatial distribution characteristic of the seismic channel are fully utilized, the precision and robustness of an inversion result are improved, and a more reliable speed model is provided for geological structure interpretation and acoustic imaging.

The invention discloses a coal mine tunneling roadway advanced geological exploration and ground stress inversion method, particularly relates to the technical field of seismic signal processing in geophysical exploration, and is used for solving the problems of geological exploration signal distortion and insufficient stress inversion precision caused by strong noise interference of tunneling equipment in the prior art. Rock mass vibration signals are collected through an optical fiber sensor arranged on a roadway wall, equipment noise characteristics are identified through spectral analysis, a quantitative mapping relation between working condition parameters and noise characteristics is established, a noise reference time period is determined according to the quantitative mapping relation, a spatial coherence characteristic template is constructed, high-coherence noise components are inhibited through template comparison, and the noise reference time period is determined according to the spatial coherence characteristic template. Finally, the geological structure and stress field distribution in front of the working face are inverted based on the purified seismic wave signals, a stress concentration area and a disaster risk area are identified, the signal-to-noise ratio of the seismic signals in the strong noise environment and the reliability of the geological inversion result are effectively improved, and accurate technical support is provided for safe mining of a coal mine.

The invention relates to a geological radar advanced forecasting system for TBM shield construction and a detection method, which are characterized in that a transmitting antenna and a receiving antenna are arranged in a tool bit gap of a TBM shield machine, rotation of a tool bit is not affected, measurement can be carried out when the tool bit rotates, and a three-dimensional structure section right in front of the tool bit is further acquired; a method of forming obvious reflection based on geological body physical property dielectric constant difference is adopted, the TBM shield tunneling advancing direction is detected and imaged, a geological structure image is obtained, then geological information such as faults, rich water, cavities and boulders is provided, the influence of geological difference is small, and testing is more accurate compared with a seismic wave method; the receiving antenna and the transmitting antenna are arranged in the tool bit gap of the TBM, the receiving antenna and the transmitting antenna are not affected by the blade, rotation of the tool bit is not affected, and stability and accuracy of rotation measurement of the whole set of forecasting system can be guaranteed.

The invention provides a method for analyzing anti-seismic performance of a steel reinforced concrete frame structure in a construction process, which comprises the following steps: S1, establishing a time-varying calculation model of the steel reinforced concrete frame structure in the construction process, the time-varying calculation model being used for simulating structural incompleteness and boundary condition change in a construction stage; s2, analyzing the anti-seismic performance of the steel reinforced concrete frame structure in the construction process by adopting a time-history analysis method, wherein the time-history analysis is based on a seismic wave acceleration time-history curve; s3, according to the time history analysis result, determining an earthquake response change rule of the steel reinforced concrete frame structure in the construction process; and S4, according to the earthquake response change rule, a measure for improving the anti-seismic safety of the steel reinforced concrete frame structure in the construction process is determined.

The invention discloses a method for automatically inverting seismic slip distribution based on deep learning. The method comprises the following steps: collecting random slip distribution corresponding to different seismic events and synthesized three-component seismic HR-GNSS waveform data, and preprocessing to obtain a sample group; building a SlipNet neural network based on a Transform-CNN model, and carrying out the training through the sample group; and inputting to-be-processed three-component seismic HR-GNSS waveform data into the trained SlipNet neural network, and generating a corresponding inverted seismic fracture area binary distribution matrix and an inverted seismic fracture slippage distribution matrix. The method solves the problem that a traditional seismic slip inversion method is low in calculation efficiency and lacks physical constraints due to single dependence on seismic waves or deformation data, and is difficult to meet the requirements of complex seismic source characterization. The method can be applied to three-component seismic HR-GNSS waveform data of large earthquakes of different types and different magnitudes.

The invention relates to a three-component high-dimensional seismic data reconstruction method and device based on vector tensor reduced rank, a medium and equipment, and the method comprises the steps: firstly, placing three-component high-dimensional seismic data at three imaginary part positions of a quaternion array in a time domain through employing a quaternion tool, and setting a real part of the quaternion array to be 0 value; and realizing vector joint representation of the quaternion-based three-component seismic data. Quaternion representation can protect the nonlinear orthogonal relation of three component seismic data in the space direction, and vector field structural characteristics of seismic waves are kept. And secondly, transforming a time domain quaternion array into a frequency domain by using quaternion Fourier transform, extracting a spatial high-dimensional quaternion array corresponding to each frequency domain slice, and performing missing data restoration and reconstruction on the high-dimensional quaternion array by using a tensor reduced-rank reconstruction technology based on a quaternion parallel matrix decomposition algorithm. According to the method, the memory occupation amount is remarkably reduced, the calculation amount is small, the calculation cost is low, and the reconstruction calculation efficiency is high.

The invention belongs to the technical field of geotechnical engineering disaster prevention and reduction and earthquake engineering tests, and relates to a vibration table test method considering time-varying deterioration of anti-seismic performance of an anchored rock slope. The method comprises the following steps: firstly, constructing a dynamic performance time-varying deterioration model based on an anchoring system interface bonding force and a free section steel bar yield resistance attenuation rule; physical equivalent simulation of interface degradation and component yield resistance reduction is realized by regulating and controlling the proportion of rock mass similar materials and utilizing a graded rigidity anchoring system. The core of the method is that before a vibration table applies seismic waves, attenuation of the anchoring performance of a supporting structure is actively simulated in advance, so that a real evolution path that the bearing capacity of an anchoring system is reduced firstly, slope stress redistribution and accumulated damage are caused, and then sudden seismic loads are suffered is reproduced; the limitation that only the static low bearing capacity is simply simulated in a traditional test is broken through. According to the method, space-time coupling of static time-varying degradation accumulation and transient earthquake dynamic action is effectively achieved, the problems of interface degradation simulation distortion and the like are solved, and a reliable test method is provided for dynamic stability evaluation and reinforcement design of a long-term service anchoring slope.

The invention discloses a joint imaging method and device for DAS-VSP data and ground seismic data, and the method comprises the steps: collecting the ground seismic data, and collecting the DAS-VSP data; performing wave field separation on the DAS-VSP data of the left well and the right well to obtain first seismic wave field information; obtaining second seismic wave field information by adopting a Marchenko iterative algorithm and the ground seismic data; screening same seismic source data from the ground seismic data, the first seismic wave field information and the second seismic wave field information; and performing normalization adjustment on the same-source data to obtain same-source three-dimensional exploration seismic data, performing Kirchhoff prestack migration processing on the same-source three-dimensional exploration seismic data, outputting a migration result, and respectively processing the DAS-VSP data and the ground seismic data to obtain a detection point which is located in the ground surface and the wells on the two sides, and a detection point which is located in the ground surface and the wells on the two sides. Omnibearing three-dimensional exploration data on an underground virtual calibration surface is used for prestack depth migration, and exploration imaging precision is improved.

The invention discloses a tunnel rock mass water burst and mud burst prediction method and system based on an XGBoost-RF fusion algorithm, and belongs to the technical field of geological disaster prediction. The method comprises the following steps: firstly, preprocessing seismic wave data, and extracting various geological response characteristics including longitudinal wave velocity, wave velocity variation coefficient, Poisson's ratio and the like; then respectively training an XGBoost model and a random forest model, and carrying out probability fusion through a soft voting strategy; and finally, outputting a risk level classification result based on the weighted probability. The core innovation of the invention lies in that the feature fine recognition capability of the XGBoost model and the anti-noise characteristic of the random forest model are effectively combined through algorithm fusion, and the probability calibration and weight optimization mechanism is adopted, so that the recognition precision of middle and high risk categories is remarkably improved. Experiments show that according to the method, the average recall rate of key categories on a test set reaches 0.9925, the overall accuracy rate is 0.990, and the problems that a traditional method is high in high-risk geologic body missed judgment rate and insufficient in generalization ability are effectively solved.

The invention discloses a geothermal resource assessment method and system based on big data analysis, and is applied to the technical field of digital analysis. The method comprises the following steps of obtaining multi-source heterogeneous data of historical drilling engineering, performing data preprocessing and feature engineering, and establishing a drilling success probability intelligent prediction-risk quantification model; in combination with geospatial information and environmental multi-source data, identifying an earth surface thermal anomaly region as a target region to perform geothermal potential assessment, and completing preliminary grading assessment of the target region; integrating seismic active band high-frequency monitoring data, inverting deep structure features by using a seismic wave velocity tomography technology, and performing multi-mode correlation matching with a target region; the coupling model realizes accurate evaluation and grading screening of a target region; and constructing a geothermal target area digital twinborn model fused with geologic and geophysical constraints, and realizing dynamic evaluation and productivity prediction of geothermal resources. Automatic geothermal resource evaluation is achieved, and efficient development and reasonable utilization of geothermal resources are promoted.

The invention relates to the technical field of geological disaster early warning, in particular to a risk grading method for tunnel seismic wave data and geological information fusion, which comprises the following steps: S1, collecting tunnel multi-temporal seismic wave amplitude, frequency response and propagation delay information, identifying an abnormal response event, extracting a spatial propagation path of the abnormal response event in combination with a tunnel structure, generating a seismic wave evoked response event chain set; s2, geological information such as a drilling profile, a geological structure line and lithologic distribution is fused, and a structure chain type conduction diagram is output; and S3, counting the activeness, the derivation direction and the time sequence trend of the structural unit in the conduction diagram, calculating a trend activation factor, and generating a risk level map with predictability and evolution ability. According to the method, the earthquake response event chain and the structure conduction network are constructed, the multi-source geological information is fused, and the trend activation factor is introduced, so that the dynamic, accurate and predictable grading evaluation of the tunnel structure risk is realized.

The invention is suitable for the technical field of seismic analysis, and provides a cross-fault tunnel fault movement-seismic oscillation decoupling analysis method and device and a terminal. The method comprises the following steps: establishing a finite element model of a cross-fault tunnel-surrounding rock; based on the dual-objective optimization function of the seismic wave, determining the separation frequency of a fault movement component and a seismic oscillation component in the current seismic wave, and obtaining fault movement component data and seismic oscillation component data from the seismic wave in the simulation area; the fault movement component data and the seismic movement component data are converted into equivalent seismic loads; and applying the equivalent seismic load to the finite element model for finite element calculation, and determining the seismic response rule of the tunnel lining under the action of the seismic motion field and the fault displacement field. According to the method, the optimal separation frequency of the seismic oscillation component and the fault movement component is determined by using the dual-objective optimization function, so that the influence of different seismic wave components on the tunnel structure is researched, and a reference basis is provided for adopting targeted anti-seismic measures for tunnel seismic resistance.

A method for seismic fragility analysis of a shield tunnel considering surface surcharge effects includes the steps of: determining mechanical property parameters of tunnel materials and physical-mechanical parameters of soil layers; investigating case studies of surface surcharge to define surface surcharge scenarios; selecting seismic waves and performing one-dimensional equivalent linear site response analysis on soil conditions; establishing a dynamic finite element numerical model of a soil-tunnel system considering surface surcharge; defining ground motion intensity measures (IM), tunnel damage measures (DM), and damage states (DS); and establishing probabilistic seismic demand models for the tunnel under various surface surcharge effects. Based on key parameters, seismic fragility curves for tunnel structures under surface surcharge effects are established. Through a nonlinear incremental dynamic analysis method, this method establishes the finite element numerical model of the soil-tunnel system, allowing for quantitative assessment of tunnel seismic fragility and seismic performance under various surface surcharge effects.

The invention provides a seismic fault identification method and system based on multi-attribute collaboration and spectral domain graph enhancement, and relates to the technical field of seismic exploration, and the method comprises the steps: carrying out the all-directional dip angle and azimuth angle scanning of a seismic data volume, extracting multi-scale guide field information through combining structure tensor decomposition, and executing anisotropic diffusion filtering; calculating characteristic value distribution through a characteristic value coherence algorithm based on the filtering data volume, and determining the structural consistency difference of adjacent seismic traces to obtain a fracture coherence attribute data volume; carrying out azimuth gather sorting and pre-stack time migration processing on the seismic data volume, extracting seismic wave dynamic response characteristics, carrying out Fourier series expansion on the azimuth change rate to obtain a crack indication information data volume, splicing the data volume and executing multi-scale three-dimensional convolution solution, and constructing a spatial dependency graph through a spectral clustering algorithm; spectral domain enhancement features are obtained through spectral domain graph transformation and frequency selective filtering reconstruction, and morphological connectivity analysis is executed to obtain a crack prediction result.

The invention provides a three-dimensional scattering imaging method, device and equipment and a storage medium, and relates to the technical field of seismic wave imaging, and the method comprises the steps: collecting seismic wave data through a three-component detector, carrying out the polarization analysis, obtaining the actual path data of scattered waves, constructing a common scattering point gather of each preset underground scattering point, and obtaining a common scattering point gather of each preset underground scattering point; when the common scattering point gather is constructed, the amplitude is adaptively weighted according to the consistency of theoretical path data and actual path data of a seismic trace, and then imaging is performed based on the common scattering point gather to obtain an imaging result including the underground scatterer. According to the method, by introducing path consistency weighting, the common scattering point gather quality and the imaging precision are remarkably improved.

The application discloses a land geophysical exploration method, an electronic device and a readable storage medium, and belongs to the technical field of land geophysical exploration. The land geophysical exploration method comprises the following steps: detecting a first seismic wave generated by vibration at a preset position of the underground or the ground and transmitted to the ground; detecting a second seismic wave transmitted by the vibration to the air above the ground; calculating a ground parameter in a set range of the preset position according to the first seismic wave and the second seismic wave; and calculating an underground velocity model and a density model according to the ground parameter. The second seismic wave transmitted to the air from the ground is detected by utilizing the characteristics that the sound speed and the density of the air are consistent under the same meteorological condition, so that the subsequent inversion algorithm is more accurate, and the underground velocity model and the density model are more accurate.

The methods may include obtaining a frequency-domain seismic wavefield associated to grid points and organized into slices. Each slice is organized into a sequence of overlapping windows. The methods may further include, for each slice, determining a value of a first intermediate function using the frequency-domain seismic wavefield for each grid point in a first overlapping window, determining a value of the first intermediate function using the frequency-domain seismic wavefield for each incremental grid point in each n-th overlapping window, where n is an integer greater than one, and determining a value of the first intermediate function by selecting the previously-determined value of the first intermediate function for each common grid point in each n-th overlapping window. The methods may still further include determining, using a second intermediate function, a Radon-transformed seismic wavefield using the value of the first intermediate function for the grid points. A non-transitory computer-readable memory and systems are also disclosed.

The invention belongs to the technical field of source vehicle corollary equipment, and particularly relates to a drop hammer source anti-secondary excitation device, which comprises an anti-secondary excitation body, the anti-secondary excitation body comprises a controller and a mounting plate, the mounting plate is provided with a mounting hole, the mounting plate is fixedly mounted on a source vehicle, and the controller is connected with the controller. A clamping assembly used for clamping a drop hammer is installed on the installation plate, a sound sensor used for detecting sound is installed on the installation plate, through the sound sensor and a controller, the clamping assembly is triggered to clamp the drop hammer, signal interference caused by secondary excitation of the drop hammer is blocked, and the accuracy and reliability of exploration data acquisition are ensured. Meanwhile, the workload and difficulty of subsequent seismic wave signal processing are greatly reduced, and the blank in the prior art is filled.

The application relates to the technical field of underwater detection, in particular to an underwater vehicle autonomous detection system and method based on seabed seismic wave signals. The system comprises a three-axis seismic wave signal acquisition module, a signal superposition amplification module, a signal filtering module, a signal envelope extraction module, an environmental noise integration module and a threshold comparison determination module. The acquisition module is orthogonally arranged to receive three-axis seismic wave signals and convert the signals into charge signals, the superposition amplification module completes signal conversion and superposition, the filtering module suppresses noise, the envelope extraction module extracts a detection value, the noise integration module obtains a noise integral value, the comparison module compares the two values, and when the detection value is greater than the integral value, an underwater vehicle existing signal is output. The application uses seabed seismic waves as a detection source, has strong anti-interference performance, works in a passive mode, is concealed and has low power consumption, can accurately capture weak seismic wave signals of the underwater vehicle, realizes autonomous detection of the underwater vehicle, and is suitable for long-term unattended deployment on the seabed.

The application discloses a large deformation whole process simulation method of earthquake landslide based on a grid isolation technology and relates to the technical field of geotechnical engineering.The application constructs a separated background grid and a multi-medium model containing a safety isolation zone based on a second-order convection particle domain interpolation material point method, carries out dynamic analysis on the earthquake landslide by using a strain-driven hardening-softening coupling constitutive mechanism, realizes flexible input of the earthquake wave at the isolation zone and anti-drifting of the base, and can accurately simulate the complete evolution process of the landslide from undrained shear cracking to large deformation friction accumulation.The application effectively eliminates wave reflection interference of the dynamic boundary and numerical drift of long-time integration, realizes real physical reproduction of the whole process of the earthquake landslide from cracking to friction accumulation, makes calculation of large deformation and permanent displacement of the slope under the action of the earthquake more accurate and stable, and lays a foundation for prediction and evaluation of the whole process of the landslide disaster evolution.

This invention belongs to the field of port engineering structural health monitoring and numerical simulation technology, specifically relating to a digital twin-based seismic stability assessment system and method for caisson wharves. The system includes a data acquisition and processing module, a model update module, and a performance evaluation and early warning module; the method includes data perception and feature extraction, parallel model calibration and update, coupled analysis, and intelligent early warning. This invention establishes a high-fidelity digital twin model that is synchronously updated with the physical entity and utilizes high-performance parallel computing technology to achieve real-time and accurate assessment and early warning of the stability of caisson wharves under combined seismic and wave effects.