653 results about "Wave field" patented technology

The invention discloses a multi-agent-based gas insulated switchgear fault diagnosis method and system, and relates to the technical field of intelligent operation and maintenance of power equipment, and the method comprises the steps: obtaining signal data of target equipment, carrying out the feature extraction of the signal data, and constructing a multi-modal feature matrix; time delay features of acoustic and electromagnetic signals are extracted from the multi-modal feature matrix, a GIS propagation model is established, and the space coordinate position of a liberated power source is solved through a wave field inversion algorithm; combining the space coordinate position and the multi-modal feature matrix into a complete fusion feature vector, inputting the fusion feature vector into a dynamic Bayesian model, and outputting a fault type label and a corresponding confidence coefficient; migrating the dynamic Bayesian model based on a migration learning mechanism, and dynamically updating a classification threshold value; inputting the diagnosis history sequence into a time sequence prediction model, and predicting a future operation state; through multi-modal fusion and intelligent reasoning, GIS fault accurate positioning and prediction are realized, and the problems of low precision and poor adaptability of traditional diagnosis are solved.

The invention provides a multi-physics field cooperative regulation and control method in coal mine rock burst prevention and control, and relates to the technical field of coal mine rock burst prevention and control, and the method comprises the steps: synchronously collecting stress field, fracture field and vibration wave field data in real time through a distributed optical fiber sensor network and a micro-seismic monitoring system, and constructing a dynamically updated three-dimensional geomechanical model; based on an adaptive Kalman filtering algorithm, noise reduction multi-source data are fused, a dynamic stress concentration factor and an energy accumulation critical index are extracted, and a rock burst risk probability model is established; a multi-objective optimization algorithm is adopted to generate graded regulation and control instructions of grouting reinforcement, mining speed adjustment and pressure relief drilling, and the graded regulation and control instructions are executed in real time; and iteratively optimizing the model weight by using a transfer learning algorithm in combination with a historical case library to form a closed-loop feedback adaptive prevention and control system. According to the method, the analysis precision of rock mass fracture evolution under complex geological conditions is improved through multi-physics field collaborative perception and dynamic modeling, and risk quantification and real-time regulation and control are realized through multi-algorithm coupling analysis.

The invention discloses an extreme sea condition parameter identification system based on deep learning, and relates to the technical field of ship navigation auxiliary equipment, in particular to a self-adaptive sea condition identification device which is used for acquiring image data and inertial measurement data of a current sea condition; the wave field visual depth estimation module is used for extracting visible light image features and infrared image features of a wave area from image data of the current sea condition, fusing the extracted visible light image features and infrared image features, using an encoder-decoder architecture and fusing an energy function to obtain a pixel-level wave height field, and outputting the pixel-level wave height field. The three-dimensional reconstruction of the wave surface is realized; the multi-modal data fusion module uses a filter dynamic model and a cost function to eliminate space-time asynchronous errors between inertial measurement data and visual perception data, performs multi-modal data fusion, and outputs wave field real-time parameterization information. According to the invention, the sea condition parameter real-time high-precision identification capability of the autonomous unmanned ship or the offshore carrying platform can be improved.

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 discloses an intelligent analysis system for ultrasonic phased array detection data of a welding seam, and relates to the technical field of nondestructive testing, and the intelligent analysis system is characterized in that a four-dimensional wave field tensor is constructed by collecting full-waveform ultrasonic data under multi-channel, multi-path and multi-angle conditions; extracting reflected signals which keep time coherence in a discontinuous path, and generating a high-dimensional coherence feature matrix; inputting the features into a self-supervised contrast learning model to obtain a defect semantic embedding vector; recognizing a suspected weak defect area based on the distribution density and the boundary change trend, and performing reverse beam focusing in combination with original data to obtain a defect three-dimensional positioning map; the shape bifurcation index and the boundary stability are calculated through topological analysis, and intelligent discrimination of artifacts and microcrack defects is achieved; the method does not need label data, has high automation and robustness, and is suitable for weak defect identification of complex structure welding seams.

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 provides a karst cave group detection method and device in shield construction, and the method achieves the comprehensive detection of karst caves through a transient electromagnetic and sound wave array composite wave field detection mode, and improves the detection accuracy and detection efficiency of the karst cave group. And feature extraction is performed on the composite wave field detection data through a cross-physical coupling model, a karst cave probability model is established, and quantitative evaluation of a karst cave detection result is realized. When the karst cave possibly exists in the construction direction of the shield tunneling machine, the distribution prediction direction of the karst cave is further determined, and the shield tunneling machine is prevented from entering the karst cave area blindly in the tunneling process. Through the multi-source sensing array carried on the shield tunneling machine, equipment parameters during operation of the shield tunneling machine are collected in real time, potential construction anomalies can be found easily, and the accuracy and timeliness of karst cave detection are improved. Combined analysis is carried out on the composite wave field detection data and the operation parameters of the shield tunneling machine through the risk assessment model, a karst cave risk prediction value is determined, and the accuracy of karst cave risk assessment is improved.

Disclosed are methods, systems, and computer programs for dynamically generating a development plan for a resource site. The methods for example, include receiving seismic data associated with a subsurface of the resource site. The seismic data may be associated with a propagated wavefield within the subsurface of the resource site and can include at least structural geological data associated with the resource site. The methods also include directionally determining a plurality of rate of change data based on the propagated wavefield within the subsurface. The methods further include executing an averaging operation using the plurality of rate of change data and thereby generate an impedance model. The impedance model may be used to generate a development plan which is then used for energy development operations at the resource site.

The invention discloses a delta-beach bar composite sand body prediction method, which comprises the following steps of S1, acquiring geological background data of a target work area, and dividing delta and beach bar deposition to obtain a beach bar deposition thickness; s2, carrying out source and sink system analysis, establishing a sediment transport channel path, and obtaining a sand body transport path plane distribution diagram; s3, the ancient landform, ancient wind field features and ancient wave field features of the target work area in the deposition period are restored, the ancient landform height and the distance to the source area of the underwater ancient protrusion are obtained according to the ancient landform, and the features include the ancient wind direction, the ancient wind path, the ancient water depth and the ancient wave height; s4, determining a favorable development zone, a favorable development layer section and a favorable development target zone of the delta-beach bar composite sand body; and S5, obtaining distribution characteristics of the delta-beach bar composite sand body of the target work area according to the favorable development zone, the favorable development layer section and the favorable development target area. According to the method, the delta-beach bar composite sand body can be accurately predicted, and technical support is provided for oil exploration and development.

The invention discloses a least square reverse time migration method and device for a three-dimensional anisotropic medium, and the method comprises the steps: building a forward equation of the three-dimensional anisotropic medium for a seismic block to be subjected to reverse time migration, and obtaining a background wave field under the three-dimensional anisotropic medium through regional forward modeling; determining a three-dimensional anisotropic medium adjoint wave field by using a pre-established wave equation of the adjoint wave field; according to the adjoint wave field and the background wave field, determining an initial gradient by using a pre-established least square reverse time migration cross-correlation equation, and obtaining a migration result according to the initial gradient; and updating an imaging result through a conjugate gradient method according to the offset result to obtain a reflected wave record.

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 discloses an ultrasonic imaging method for a complex-surface multilayer anisotropic composite material. The method comprises the steps that an acoustic propagation model is established according to profile characteristics of the composite material, acoustic anisotropy characteristics changing along with the appearance and a preset ultrasonic detection mode, and the acoustic propagation model comprises medium attribute information of all spatial positions of the composite material and position and geometric information of an ultrasonic excitation unit and an ultrasonic receiving unit; for the acoustic propagation model, performing excitation in the preset ultrasonic detection mode, and obtaining an excitation signal waveform and a received acquisition signal waveform; and on the basis of the excitation signal waveform and the acquisition signal waveform, positive wave field information and reverse wave field information are calculated, and then a self-defined target is used for reverse time migration imaging to obtain an imaging result. According to the invention, full-depth synchronous focusing imaging in an anisotropic and complex molded surface coupling scene can be realized, and the imaging effect is improved.

The invention relates to the technical field of numerical simulation ship response, in particular to a ship hydrodynamic response numerical simulation method and system considering the effects of a complex wave field and an automatic mooring system. Firstly, ship radiation potential and hydrodynamic coefficients are obtained based on a three-dimensional potential flow theory and a boundary element method, and wave field information at a berth is obtained in combination with a Boussinesq wave theory; the time domain wave force is solved through the Haskind-Relation theory, and an automatic mooring numerical model integrated with a PD controller is established to calculate the automatic mooring force and torque; and finally, constructing a ship six-degree-of-freedom time domain motion equation based on the data, and solving by adopting a four-order Runge-Kutta method to obtain a time domain response result. The hybrid Boussinesq-Panel technology is adopted, the wave disturbance evaluation accuracy is improved, the blank that existing simulation does not consider an automatic mooring system sufficiently is filled up, arrangement, parameters and control strategies of the automatic mooring device can be flexibly adjusted and secondarily developed, applicability and flexibility are high, and the method is suitable for large-scale popularization and application. And reliable decision support can be provided for procurement and deployment of automatic mooring equipment of a port.

The invention belongs to the technical field of medical imaging, and provides a tissue stress measurement method and system based on a reverberation shear wave field, and the method comprises the steps: applying steady-state harmonic excitation, and obtaining the reverberation shear wave field of a target tissue; determining a stress direction according to the prior information of the target tissue, and constructing a stress direction vector; constructing an analytic operator, and extracting an intermediate characteristic quantity of the reverberation shear wave field; and according to the intermediate characteristic quantity, combining stress direction inversion to reconstruct spatial stress distribution. According to the method, a complex reverberation wave field is modeled into superposition of multi-direction propagation wavelets by utilizing anisotropic propagation characteristics of shear waves and combining a traveling wave expansion model, and characteristic quantities related to local stress and material parameters are directly extracted from the reverberation wave field by designing a wave field operator with physical significance; the three technical problems existing in a traditional shear wave elastic imaging technology are solved, the dependence of a traditional method on a single propagation direction and wave pattern controllability is broken through, and in-situ, in-vivo and non-invasive quantification is achieved.

The invention belongs to the field of ferrous metallurgy, and particularly relates to a method for improving the quality of a continuous casting billet through ultrasonic waves. According to the method, a multi-directional focused ultrasonic field and solidification front edge dynamic regulation and control combined mode is adopted, and electromagnetic stirring phase difference control and cooperative control of a secondary cooling section (fan-shaped section) auxiliary ultrasonic vibrator are combined at the same time. Wherein the composite action mode of the longitudinal standing wave field and the transverse traveling wave field of the multidirectional focused ultrasonic wave field and the solidification front edge dynamic regulation and control mode act on the casting blank, so that the equiaxed crystal rate can be remarkably increased, and the combination of ultrasonic waves and electromagnetic stirring is beneficial to reducing the segregation degree of the casting blank; and the addition of nano aluminum oxide and magnesium oxide mixed particles in the casting powder is beneficial to improving sound wave conduction so as to reduce subcutaneous bubbles. The isometric crystal rate of the finally obtained continuous casting billet is increased to 30%-55%; the center segregation index of the finally obtained continuous casting billet is reduced to 1.05 or below; and the number of subcutaneous bubbles per square meter is less than 0.5.

The invention discloses a scattered wave seismic acquisition and imaging method based on a full random observation system, which belongs to the technical field of seismic exploration and comprises a quasi-Monte Carlo random observation array design step, a scattered wave intelligent identification and enhancement step, a sparse wave field reconstruction step and a multi-target optimization imaging step. The limited equidistant property is ensured through the random observation array design based on a low-difference sequence, intelligent separation and enhancement of scattered waves are realized by using a physical constraint neural network, a sparse reconstruction problem is solved by using an alternating direction multiplier algorithm, a multi-target optimization imaging framework is constructed to realize high-resolution imaging, and high-resolution imaging is realized. The four core steps form a closed-loop cooperative system, sparse reconstruction quality evaluation feedback optimizes observation array design, imaging quality measurement feedback adjusts scattered wave identification parameters, and cooperative interaction is achieved.

The invention belongs to the technical field of seismic data processing in geophysical exploration, and relates to a Marchenko multiple suppression method for correcting wave field mismatch based on Wasserstein distance, which comprises the following steps: acquiring a pulse reflection sequence through preprocessing and deconvolution; a pulse reflection sequence is input, and Marchenko iteration initialization is carried out; and remodeled Marchenko iteration for correcting the wave field mismatch based on the Wasserstein distance is carried out. According to the method, the optimal transmission theory is systematically introduced into the Marchenko multiple wave suppression field for the first time, the adaptive capacity of the Marchenko method to actual data noise, defect and amplitude distortion is remarkably improved while the advantage that the Marchenko method does not need a speed model is kept, and therefore higher-precision multiple wave suppression and more reliable primary wave recovery are achieved, and the method is suitable for popularization and application. The method is used for high-precision seismic imaging in a complex land exploration environment. The method has remarkable advantages in the aspects of constraint mechanism, error control and global feature protection.

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 embodiment of the specification discloses a self-adaptive variable grid forward modeling method for middle-deep dry hot rock mass. p , a transverse wave velocity V s and a medium density p model, pre-setting forward modeling parameters; performing self-adaptive variable grid processing on the velocity model, determining a mapping relationship between coordinate systems, and determining a wave equation under variable grid based on the mapping relationship; performing self-adaptive variable grid processing on the velocity model, determining a mapping relationship between coordinate systems, obtaining the underground medium longitudinal wave velocity, transverse wave velocity and density after variable grid, determining a wave equation under variable grid based on the mapping relationship, and generating final regular grid horizontal direction longitudinal wave field, horizontal direction transverse wave field, vertical direction longitudinal wave field and vertical direction transverse wave field information by using the mapping relationship reversely according to the wave field information in each direction at a specific moment after the variable grid, so that the memory occupation is small and the calculation speed is faster.

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 provides a three-dimensional wave field measurement analysis method and system based on a multi-view camera, and relates to the technical field of data measurement, and the method comprises the steps: collecting a wave field multi-angle image through the multi-view camera, building a space projection relation, obtaining a feature point set, and reconstructing an initial three-dimensional point cloud; extracting time-varying features by adopting a dynamic feature learning network; constructing a deformation constraint rule for correction according to a fluid mechanics equation; and finally calculating the three-dimensional characteristic parameters of the wave field. According to the invention, high-precision three-dimensional reconstruction of the wave field can be realized, the measurement accuracy is improved, and reliable technical support is provided for hydraulic engineering and marine environment monitoring.

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 an ultrasonic orthogonal fusion precise positioning generation method based on space vector synthesis, and the method comprises the following steps: S1, constructing a multi-array ultrasonic transmitting system based on an improved beam forming model, and outputting space vector synthesis wave field data; s2, orthogonally modulating the transmitted signal, executing a synchronous transmission operation, and generating an initial orthogonal fusion ultrasonic signal; s3, receiving an echo signal, constructing a positioning error fitness function, and calculating an initial estimation coordinate; s4, inputting the positioning error fitness into a grey wolf guidance optimization algorithm, and outputting an optimal transmission parameter group; s5, redistributing the optimal transmission parameter group, executing a second synchronous transmission operation, and generating an optimized orthogonal fusion ultrasonic signal; s6, calculating an updated estimated coordinate and a space error value; and S7, feeding back the spatial error value to the grey wolf guided optimization algorithm, and repeating the steps S4 to S7. According to the method, the positioning precision, the emission parameter self-adaption and the closed-loop optimization capability of the ultrasonic system in a complex environment are effectively improved.