447 results about "Wave field" patented technology

The invention discloses a road cavity volume calculation method and device based on a three-dimensional FK migration algorithm, equipment and a medium, and relates to the technical field of road cavity detection, and the method comprises the steps: obtaining three-dimensional ground penetrating radar data, and carrying out the preprocessing of the data, and obtaining target radar data; converting the target radar data to a frequency wavenumber domain to obtain frequency wavenumber domain radar data; establishing a road hierarchical velocity model, and performing hierarchical wave field extrapolation and double weight correction based on the frequency wave number domain radar data and the road hierarchical velocity model to obtain corrected wave field data; performing sparse constraint optimization imaging processing on the corrected wave field data to obtain a target imaging result; and carrying out boundary extraction processing on the target imaging result to obtain a three-dimensional cavity boundary point set, and carrying out voxelization processing based on the three-dimensional cavity boundary point set to obtain a road cavity volume. According to the invention, high-precision restoration of the shape of the road cavity and automatic extraction of the volume can be realized in three-dimensional GPR imaging.

The invention provides an electromagnetic ultrasonic bolt stress detection system based on a space-time complementation algorithm, and the system comprises the steps: carrying out the multi-channel ultrasonic signal collection of a to-be-detected bolt, and obtaining a multi-channel echo signal group; performing time-varying attenuation compensation and adaptive entropy weight denoising on the multi-channel echo signal group to obtain a denoised echo signal group; extracting echo time-domain features from the de-noised echo signal group, performing segmented time-frequency feature extraction on the de-noised echo signal group based on a short-time sliding window to obtain echo time-frequency features, and fusing the echo time-domain features and the echo time-frequency features into ultrasonic time-frequency features; performing wave field reconstruction on the de-noised echo signal group to obtain a spatial ultrasonic energy diagram, and extracting ultrasonic spatial features of the spatial ultrasonic energy diagram based on a self-attention map convolutional network; performing correlation detection and space-time complementary modeling on the ultrasonic time-frequency features and the ultrasonic space features to obtain ultrasonic space-time joint features, and performing stress analysis on the ultrasonic space-time joint features to obtain bolt stress data.

The invention belongs to the technical field of photovoltaic power generation, and particularly relates to a floating type photovoltaic array power generation performance evaluation method, which comprises the steps of constructing an offshore area environment model; a Boussinesq model is adopted to calculate a real near-shore wave field; constructing a matching surface on the outer side of the array, extracting wave field time domain information, and converting the wave field time domain information into a frequency domain component; solving the six-degree-of-freedom motion response of the array through a boundary element method by taking the component as a boundary condition; calculating the dynamic attitude of the assembly, the solar incident angle, the out-of-plane irradiance, the working temperature and the instantaneous output power in real time based on the motion response; and finally evaluating the wave-induced power generation loss. According to the method, the Boussinesq model and the boundary element method are coupled in a domain nested mode, balance is achieved between calculation efficiency and precision, key environmental factors such as non-constant water depth, topographic relief and shoreline effect are synchronously considered, 'hydrodynamic force-light receiving-power generation 'chain coupling is achieved for the first time, and reliable support is provided for engineering design and performance evaluation of a near-shore floating type photovoltaic array.

The invention discloses a deep rock mass fracture imaging method and system based on micro-seismic monitoring, and belongs to the technical field of geophysical exploration, and the method comprises the steps: collecting multi-channel micro-seismic event waveform data, obtaining a main seismic phase direct waveform and a scattering tail waveform through wave field separation, and carrying out the imaging of a deep rock mass fracture. Determining a three-dimensional space coordinate and an energy distribution form of the seismic source through joint inversion, carrying out clustering analysis, and constructing an initial three-dimensional space distribution form; each seismic source is regarded as an active excitation source, a scattering tail wave waveform is regarded as a reflection signal, scatterer three-dimensional point cloud data is generated through reverse time migration processing, analysis is carried out in combination with an initial three-dimensional space distribution form, and an enhanced fracture structure is formed; and finally, through topology analysis and orientation clustering, discrete scatterers are eliminated, and a fracture development map is generated. According to the method, a technical path of combining a main seismic phase direct wave inversion seismic source and a scattering tail wave inversion scatterer is adopted, high-precision and high-fidelity imaging of a deep rock mass movable fracture can be realized, and physical activity is revealed.

The invention provides a cable fault diagnosis method and system based on multi-modal composite fusion. The method comprises the following steps: synchronously acquiring and performing time-space alignment on distributed acoustic, temperature and high-frequency pulse signals along a cable path; the acoustic signal is decoupled into an internal event channel and an external interference channel by time domain polarization analysis. And calculating the acoustic nonlinear index of the candidate event in the internal channel, dynamically correcting the judgment threshold value of the candidate event by using the real-time temperature signal, and performing cross-modal correlation verification with the high-frequency pulse signal so as to confirm that the candidate event is an electrical discharge event. And if the judgment result is true, an acoustic wave field data array of the event is extracted, and a passive synthetic aperture focusing algorithm is applied to reconstruct a two-dimensional morphological acoustic image of the fault source. And finally, integrating all information to generate a comprehensive diagnosis report. The technical problem that a traditional distributed sensing method can only provide one-dimensional fault positioning and cannot perform high-confidence qualitative and multi-dimensional morphological representation on the fault is solved.

The invention relates to the technical field of data processing, and discloses a wind turbine generator optimization design method based on tidal current-wave-sediment coupling simulation. The method comprises the following steps: carrying out adaptive time step adjustment on marine environment data through a physical process intensity discrimination algorithm to obtain tidal current field, wave field and sediment transportation data; carrying out fluid-solid coupling calculation on the structural parameters of the wind turbine generator to obtain structural vibration response and ocean load distribution data, and predicting pile foundation scouring depth distribution; carrying out time-varying coefficient correction on the pile foundation bearing capacity parameters to obtain dynamic bearing capacity evaluation data; inputting a multi-objective optimization algorithm to obtain a Pareto optimal solution set; and obtaining a wind turbine generator optimization design scheme through engineering feasibility verification and screening. The technical problems that in existing offshore wind turbine generator design, tidal current-wave-sediment coupling simulation space-time scales are not matched, the pile foundation scouring prediction precision is insufficient, bearing capacity evaluation lacks time-varying characteristic consideration, and the multi-target optimization design capacity is insufficient are solved.

The invention discloses a microseismic signal denoising method fusing multi-scale features and global-local attention. The method comprises the following steps: constructing a large-scale pure microseismic signal data set based on elastic wave field simulation; carrying out noise-containing sample set generation and data standardization preprocessing in combination with real environment noise; carrying out scientific division and preparation on the noisy / pure sample pair; an MSF-GLANet layered coding and decoding network framework based on the U-Net + + topology is constructed; constructing a composite loss function which takes the Charbonier loss as a core, and combining a multi-level depth supervision strategy; performing initialization and iterative training based on a composite loss function on the MSF-GLANet network by using the training set; the model performance is monitored in real time through the verification set, and the optimal model weight is stored; a real environment microseismic signal to be denoised is preprocessed and then input into the trained model for reasoning; and performing element-by-element addition reconstruction on a residual signal predicted by the network through a residual connection mechanism to realize high-fidelity recovery of a de-noised signal.

The invention relates to the technical field of automatic welding, and discloses a special-shaped curved surface steel structure self-adaptive welding control system which comprises a three-dimensional visual scanning unit, a welding robot, an acoustic feedforward sensing unit, a molten pool state diagnosis unit and a central control and calculation unit. The acoustic feed-forward sensing unit collects sound wave field data of a to-be-welded area in front of a welding gun, the molten pool state diagnosis unit obtains real-time temperature and component information of a molten pool through spectral analysis, a model correction module in the central control and calculation unit dynamically corrects an acoustic elastic coefficient according to the real-time temperature and component information, and a stress field reconstruction module calculates a stress field of the to-be-welded area based on the coefficient and the wave field data. The method comprises the steps that a feedforward stress field distribution diagram is reconstructed, an instruction generation module analyzes the gradient and amplitude of a stress field, a welding path avoiding a high stress gradient area and a compensation stress amplitude and a parameter regulation and control instruction are generated, and feedforward self-adaptive control is achieved. The welding joint quality is improved.

The invention provides a tunnel contour high-precision explosion control method based on lumpiness uniformity optimization, which comprises the following steps of: fusing multi-source geological data to construct an updatable model, and triggering encryption measurement and correction by deviation; training a depth model by using a historical multi-modal case, and generating an initial blasting parameter; multi-objective optimization is carried out with the minimum back break, the maximum block yield and the minimum unit consumption as objectives, and gradient charge changing along with the hole depth is obtained; simulating a crack and a wave field in digital twinning, optimizing a detonation sequence to form destructive interference on a contour surface, establishing an electronic detonator network for self-inspection, and then performing blasting; evaluating the radial deviation by point cloud alignment after explosion, calculating the particle size and the qualified rate by images, generating a thermodynamic / cloud picture, and carrying out early warning and shutdown when the threshold value is exceeded; and on the basis of monitoring feedback and reinforcement learning self-adaptive adjustment, contour and lumpiness closed-loop optimization is realized.

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 relates to the technical field of crossing of geophysical exploration and artificial intelligence, and discloses a three-dimensional VSP data reconstruction method based on a three-dimensional blind sidewalk time frequency-space multi-domain interpolation network model, and the method comprises the steps: obtaining a to-be-reconstructed three-dimensional VSP data volume containing an irregular missing sidewalk; inputting the three-dimensional VSP data volume into a trained three-dimensional space-time-frequency mixed domain convolutional network model; performing down-sampling on the input data through an encoder to extract initial spatial-temporal characteristics; inputting the initial spatiotemporal features into a residual spatiotemporal-frequency wavenumber domain joint convolution feature fusion module to obtain fusion features; and inputting the fusion features into a decoder, and reconstructing a complete three-dimensional VSP data volume through up-sampling operation. According to the invention, through joint learning of ground seismic data (providing a macrostructure) and illuminance data (providing a physical propagation path), a reconstruction result with a reasonable geologic structure and extremely high fidelity of wave field features can be generated.

The invention discloses a large-section tunnel blasting control method and system based on an energy dissipation mechanism, and the method comprises the steps: constructing a blasting region three-dimensional geomechanical model of rock mass mechanical parameters, and mapping the energy demand distribution of each point; based on the model, establishing a stress wave field propagation and interference prediction model for predicting a space-time stress field under any microsecond-level delay sequence; constructing a multi-target fitness function, and solving through intelligent optimization algorithms such as a non-dominated sorting genetic algorithm and the like to obtain an optimal microsecond-level delay sequence; the sequence is issued to a plurality of electronic detonators through a high-precision synchronization and safety protocol to execute detonation; and collecting actual blasting monitoring data, comparing the actual blasting monitoring data with a model prediction result, and carrying out adaptive correction on geologic model parameters by applying extended Kalman filtering. According to the method, the stress wave field interference is actively constructed to realize distribution of energy according to needs, multiple blasting targets are considered, and continuous optimization is performed through feedback, so that the blasting precision, safety and economical efficiency are improved.

The invention discloses a biological soft tissue crack quantitative detection method based on elastic wave dispersion characteristics, and the implementation process comprises the following steps: firstly, preparing a soft tissue sample, and applying initial stress to obtain a soft tissue sample strain geometric model and a material stress initial value; then applying low-frequency vibration to the surface of the soft tissue sample, tracking and positioning the vibration, establishing a constitutive relation model of the soft tissue and an increment form, and establishing an inversion model, thereby inverting detailed information such as crack length, angle, fracture mechanical parameters and the like from wave velocity change, and on the basis, determining the fracture velocity of the soft tissue sample. Finite element simulation software is used for conducting crack area local wave field simulation and wave scattering and fracture mechanical simulation on the platform, the accuracy and stability of an inversion result are verified, then after data marked correctly and wrongly are obtained, a reinforcement learning model is input to optimize the inversion result, and finally a crack form data set is obtained; and estimating whether the risk that the crack continues to expand exists or not.

The invention discloses a method for quantitatively evaluating the three-dimensional shape of a thinning defect in a plate under ultrasonic guided wave field undersampling scanning, belongs to the field of industrial nondestructive testing, and particularly relates to high-precision three-dimensional shape reconstruction and thickness loss quantification of a corrosion defect in a metal plate shell structure (such as aerospace skin, a pressure vessel wall, an oil pipeline and the like). According to the method, sparse sampling guided wave field reconstruction, full waveform inversion (FWI) and priori knowledge constraint are fused, Shannon sampling theorem limitation is broken through, efficient measurement of corrosion depth, contour and distribution under the conditions of a single excitation source and a limited view angle is achieved, and the method is suitable for rapid online detection in a complex industrial environment.

A reflective focusing-based depth-velocity modeling method, relating to the field of seismic exploration, comprising: determining an actual seismic record and an initial velocity model (S1); on the basis of a seismic observation system, performing forward simulation on the initial velocity model, and obtaining forward wave field data (S2); on the basis of the actual seismic record and the forward wave field data, calculating a focusing function of a reflected wave residual response, calculating a Green's function of the reflected wave residual response on the basis of the focusing function, and, on the basis of the Green's function and the forward wave field data, calculating a gradient of an objective function with respect to a longitudinal wave velocity (S3); determining an updated velocity model on the basis of the gradient of the objective function with respect to the longitudinal wave velocity and an update step size (S4); and on the basis of the actual seismic record and the updated velocity model, determining whether a termination condition has been met (S5), if so, using the finally obtained updated velocity model as a depth-velocity model, and if not, re-performing forward simulation and the following steps. Further related is a reflective focusing-based depth-velocity modeling apparatus.

The invention discloses a reflected wave travel time difference measurement method and system based on transverse constraint, and the method comprises the steps: carrying out the migration imaging of observed seismic data under a given speed model, obtaining an imaging result through the cross-correlation of a seismic source end wave field and a receiving end wave field, and obtaining the information of an underground reflection structure based on a multi-attribute Markov decision process. And then solving a background wave field and a primary reflection wave field in a given speed model and an underground reflection structure, and extracting a simulated seismic record at a detection point position. And calculating zero-offset travel time by using the depth of the reflection horizon, and executing transverse tracking in the reflection event direction by taking the travel time as a seed to obtain simulated travel time of each offset position. A local transverse constraint time window is constructed based on simulation travel time, cross-correlation operation is performed on observation data and simulation data in the time window, and a local extreme point is extracted. And finally, performing transverse tracking by taking the zero-offset travel time position as a starting point to obtain continuous and consistent reflected wave travel time difference, thereby realizing stable and accurate measurement of the reflected travel time.

The invention discloses a diffracted wave-based heterogeneous body prediction method, electronic equipment, a storage medium and a diffracted wave-based heterogeneous body prediction device. The method comprises the following steps: acquiring a diffracted wave three-dimensional seismic data volume, a horizon of a target interval and a comprehensive wavelet based on a full-wave-field three-dimensional seismic data volume; constructing a longitudinal wave velocity and density conversion relation based on the logging longitudinal wave velocity and the corresponding density, and further constructing a longitudinal wave velocity and longitudinal wave impedance conversion relation to convert the interval velocity of the full-wave-field three-dimensional seismic data volume into interval velocity low-frequency impedance; constructing a diffracted wave impedance inversion objective function based on the longitudinal wave diffraction coefficient and the comprehensive wavelet, and taking the interval velocity low-frequency impedance body as the background impedance of the inversion objective function; and solving the diffracted wave impedance inversion objective function based on an optimization algorithm, carrying out diffracted wave impedance inversion, and obtaining diffracted wave impedance to carry out heterogeneous body prediction. Quantitative prediction of the heterogeneous body is realized through the diffracted wave three-dimensional seismic data body, and the impedance inversion precision of the heterogeneous reservoir is improved.

The invention discloses an elastic reverse time migration imaging method based on deviatoric stress characterization, and relates to the technical field of exploration geophysics. Deviatoric stress is introduced into a conventional elastic wave equation, and a speed-deviatoric stress elastic wave equation describing stress propagation characteristics is obtained through derivation; based on Hooke's law, P wave contribution in total partial strain is removed through partial strain decomposition, decoupling of P-S wave stress components is achieved, and correctness of amplitude, phase and physical unit of a decoupling wave field is guaranteed; and then a joint imaging condition with the average stress as a seismic source wave field and the multi-stress component as a receiving wave field is constructed, PP waves are subjected to normalization superposition through the average stress and the deviatoric stress, and PS waves are subjected to shear stress imaging. According to the method, the sensitivity to heterogeneity and local stress variation of underground media can be remarkably improved, P-S wave crosstalk and imaging noise are effectively eliminated, the imaging precision and resolution of a complex geologic structure are greatly improved, and a reliable technical means is provided for high-precision seismic exploration of complex oil and gas reservoirs.

The application discloses a method for suppressing ghost waves of a streamer based on frequency-slowness domain continuation and ghost wave parameter optimization. Considering that ghost wave parameters vary with time and space and affect the ghost wave removal effect, first, the marine seismic data is divided by using a sliding time window to reduce the influence of the time variation of the ghost wave parameters; the delay time and amplitude difference coefficient of the ghost wave and the primary wave are enumerated alternately; the data in the time window is continued by using a frequency-slowness domain wave field continuation operator, and then the original marine seismic data is added and subtracted by the continued record; the sum of the absolute values of the products of the new records obtained by operation is taken as the target, the optimal ghost wave delay time and amplitude difference coefficient are iteratively searched, and then the ghost wave is suppressed; after the data in each window is suppressed, all the window data are integrated into a complete record. The method can effectively suppress the ghost wave, widen the frequency band and improve the resolution of the seismic data.

This invention relates to a method for extracting guided wavenumbers in variable thickness structures, belonging to the field of nondestructive testing technology. It utilizes an excitation signal to generate guided wave signals on the surface of the object under test. Based on a set window function and a set window length, the two-dimensional wavefield signal obtained by sampling the guided wave signal is divided into multiple local wavefield signals. A short-space Fourier transform is then performed on each local wavefield signal to obtain the amplitude-frequency-wavenumber array corresponding to each local space. A frequency range is then selected by summing the amplitude-frequency-wavenumber arrays of each local space, using the center frequency of the excitation signal as the midpoint. The weighted average wavenumber of each frequency point within the selected frequency range is calculated using the amplitude corresponding to the wavenumber sequence at each frequency point as the weight. The mean of the sum of the weighted average wavenumbers at each frequency point is then used as the wavenumber corresponding to the center position of each local signal space, and these values ​​are sequentially spliced ​​to obtain the wavenumber curve of the guided wave signal. This method solves the problem in existing technologies where the obtained guided wavenumbers cannot accurately reflect the thickness changes of variable thickness structures.

This application provides a multi-parameter Gaussian beam inversion imaging method, apparatus, and device for acoustic VTI media, belonging to the field of seismic data processing technology. Based on normal time-difference correction velocity parameters, non-elliptic parameters, and Thomsen parameters, the pressure wave field control equation in the acoustic VTI medium is parameterized to obtain a migration operator. Based on the migration operator, the acquired actual seismic data is migrated to obtain actual migration imaging results. Based on the migration operator, the difference between the forward-modeled seismic data containing and without point scatterers is migrated to obtain a point spread function. The point spread function is spatially convolved with the initial perturbation parameter model to obtain simulated migration imaging results. Based on the actual and simulated migration imaging results, a first model loss is determined. The initial perturbation parameter model is iterated with the goal of minimizing the first model loss, improving the stability of imaging and parameter estimation in weakly illuminated areas.

The invention belongs to the technical field of deep mineral resource development, and provides a rock mass catastrophe sound wave detection sensing method and system for deep solid resource mining, an observation system is arranged, a controllable seismic source is arranged in the middle of the observation system and used for exciting seismic waves, a sensor is arranged on a mining equipment tool bit and used for detecting a passive source, and a rock mass catastrophe sound wave detection sensing system is arranged in the middle of the observation system. The positions of the vibroseis and the sensor are adjustable, and a certain depth adjusting range is achieved; active detection is carried out on the underground medium by using the vibroseis; then carrying out passive source detection; the signals are processed by adopting a mutual drying method, the mutual influence among the sensors of the observation system is removed, and the data are enhanced by adopting a wave field superposition technology according to the signals processed by adopting the mutual drying method; and performing inversion processing on the enhanced signal data by adopting a reverse time migration imaging technology, and reconstructing an underground rock mass structure. The problem that rock catastrophe information cannot be obtained in time in a traditional method is solved.

Methods and seismic data processing apparatuses use a down-going annihilation operator to generate an image from seismic data acquired over a water-covered subsurface formation. The down-going annihilation operator is derived using a down-going wavefield and an estimated water-wave extracted from the seismic data. The down-going annihilation operator may be derived in plane-wave domain.

The application belongs to the technical field of marine environment expansion, and discloses a shipborne radar sea wave perception domain expansion method and system based on deep learning, which constructs a sea wave perception domain step-by-step expansion model, uses a sea wave perception domain expansion submodule to realize spatial feature modeling and limited range expansion of local observation data, and gradually deduces larger range sea wave field information through a step-by-step expansion and residual connection mode; meanwhile, a sea wave continuity constraint mechanism is introduced to apply continuity constraints at the junction of the expanded sea area and the original observation sea area, so that the overall wave field can maintain high accuracy and spatial continuity in a large range. Through the shipborne radar sea wave perception domain expansion method based on deep learning, the real-time perception ability of the shipborne radar to a large range of sea areas in the local environment can be significantly improved, the independent operation of the ship in the marine environment is supported, and the real-time sea wave perception ability of the ship navigation safety and the marine engineering application is significantly improved.

The invention relates to a stable Q compensation reverse time migration method for seismic exploration data, a medium and equipment, and belongs to the technical field of geophysical exploration data processing. According to the method, based on a fractional order Laplace viscous acoustic wave equation, a physically guided time-varying regularization compensation operator is constructed in a wavenumber domain, the energy amplitude of a previous time step length is introduced as a reference, an energy growth monitoring mechanism is established, and the energy growth is monitored. And designing a three-level adaptive constraint system: local energy growth constraint, high-frequency adaptive attenuation and boundary region stabilization processing, and realizing adjustment of excessive compensation and adaptive suppression of noise in the wave field continuation process. According to the method, amplitude attenuation and phase frequency dispersion caused by stratum absorption are effectively recovered, meanwhile, the stability of numerical calculation can be guaranteed, the precision and resolution of deep structure imaging are remarkably improved, and good numerical stability and anti-noise capacity are achieved.

This invention discloses an elastic wave reverse-time migration imaging method guided by stratigraphic dip angle for wavefield separation, relating to the field of seismic exploration technology. The method includes: acquiring an initial velocity model, source wavefield data, and receiver wavefield data for the target geological area; determining multiple stratigraphic dip angles reflecting the trend of subsurface structural changes based on the initial velocity model, and accordingly determining multiple target spatial directions; sequentially resampling, interpolating, and performing Hilbert transform on each wavefield data along each target direction to obtain source wavefield components and receiver wavefield components consistent with each direction; for any subsurface point to be imaged, determining the target spatial direction based on the stratigraphic dip angle corresponding to its vertical position, selecting wavefield components consistent with that direction for zero-delay cross-correlation calculation, thereby obtaining the reverse-time migration imaging result for that point. This method possesses good engineering feasibility and scalability, can be seamlessly embedded into existing pre-stack elastic migration workflows, and is convenient for the promotion and application of two-dimensional / three-dimensional and heterogeneous parallel computing.

This application provides a wavefield decomposition method, apparatus, device, and medium based on wavefront phase direction, belonging to the field of geophysical exploration technology. The method includes: determining a wavefield decomposition operator based on the original wavefield and Thomsen parameters; the wavefield decomposition operator is a first-order pseudo-Helmholtz decomposition operator based on the wavefront phase direction; determining the wavenumber domain wavefield obtained after transforming the original wavefield to the wavenumber domain; performing computational processing based on the wavenumber domain wavefield and wavenumber, followed by inverse Fourier transform to obtain multiple intermediate quantities constituting an auxiliary wavefield; determining the auxiliary wavefield based on the multiple intermediate quantities and Thomsen parameters through an auxiliary wavefield expression; and performing wavefield decomposition based on anisotropic wavefield decomposition formula to achieve P-wave and S-wave separation, obtaining the P-wave and S-wave wavefields. This method not only achieves P-wave and S-wave vector wavefield separation and reduces imaging crosstalk noise, but also reduces computational load, balancing wavefield decomposition effect and computational efficiency.

The present application belongs to the technical field of photovoltaic power generation, and particularly relates to a floating photovoltaic array power generation performance evaluation method, comprising: constructing a near-shore sea area environment model; calculating a real near-shore wave field by using a Boussinesq model; constructing a matching surface on the outside of the array and extracting wave field time domain information, and converting the wave field time domain information into frequency domain components; taking the components as boundary conditions, and solving the six-degree-of-freedom motion response of the array by using a boundary element method; calculating the dynamic posture of the components, the solar incident angle, the out-of-plane irradiance, the working temperature and the instantaneous output power in real time based on the motion response; and finally evaluating the wave-induced power generation loss. The present application balances between the calculation efficiency and the accuracy by coupling the Boussinesq model and the boundary element method in a sub-domain nesting manner, simultaneously considers key environmental factors such as non-constant water depth, terrain undulation, shoreline effect and the like, and first realizes the chain coupling of "hydrodynamic force-light receiving-power generation", thereby providing reliable support for the engineering design and performance evaluation of the near-shore floating photovoltaic array.

The invention discloses a novel multi-component conversion multiple imaging method for a deep-sea rugged seabed structure, and relates to the technical field of geophysical exploration for petroleum, and the method comprises the steps: inputting a longitudinal and transverse wave velocity field, a seismic source wavelet, observation system parameters, and a rugged seabed elevation; constructing a non-uniform curved grid of the acoustic-viscoelasticity model; calculating an acoustic-viscoelastic primary wave field continuation operator of vector wave separation under the curved coordinate system; calculating an acoustic-viscoelastic primary wave adjoint wave field of vector wave separation under the curved coordinate system based on an adjoint state theory; calculating an acoustic-viscoelastic n-order multiple wave field continuation operator of vector wave separation under the curved coordinate system; and calculating an acoustic-viscoelastic n-order multiple accompanying wave field of vector wave separation under the curved coordinate system, and generating a multiple imaging result by applying an elastic multiple imaging condition of vector wave separation. According to the invention, full-path compensation and longitudinal and transverse wave vector imaging of multiple waves can be realized, the imaging range is expanded, and the information amount of imaging is increased.