423 results about "Electromagnetic response" patented technology

The invention relates to the technical field of motor control, in particular to a permanent magnet motor current control system based on predictive compensation, which comprises a thermal field identification module, a response offset identification module, a correction track generation module, an amplitude limiting interval decision module and a compensation instruction output module. According to the method, a dynamic prediction correction mechanism is established based on thermal field characteristics and a response error trend, real-time adjustment of a current track of the permanent magnet motor is realized, a three-dimensional space thermal load curved surface is constructed by means of a stator temperature rise curve, a permanent magnet temperature change rate and driving torque fluctuation, and transient influence of thermal working condition change on magnetic performance of the motor is reflected. A multi-dimensional prediction compensation path is integrally constructed through interaction among multiple thermal field parameters, electromagnetic response variables and time sequence feature points, the response precision and control stability of the permanent magnet motor under the dynamic working condition are improved, the magnetic performance attenuation influence caused by thermal drift is reduced, and meanwhile the tracking consistency under current track disturbance is improved.

The invention discloses a transient electromagnetic three-dimensional dike leakage hidden danger detection method based on unmanned aerial vehicle carrying, and the method comprises the steps: S1, scanning a detection region range, obtaining dike terrain remote sensing image and point cloud image data, and setting a flight path of an unmanned aerial vehicle according to a preset detection region range; s2, performing task flight, and transmitting transient electromagnetic pulse signals with different frequencies to the underground of the dike through a transmitting coil according to a transmitting current frequency range; s3, a receiving coil is used for synchronously collecting secondary electromagnetic response signals generated by underground medium induction, discretization sampling is conducted on the collected signals according to the sampling time interval, and a sampling data sequence is obtained; s4, constructing a three-dimensional resistivity model of the dike underground medium through a three-dimensional inversion algorithm; and S5, through the constructed three-dimensional resistivity model, multi-dimensional features of the leakage hidden danger are extracted, and an area with the leakage hidden danger in the dike is identified. The leakage hidden danger area can be rapidly identified, and the detection efficiency and precision are improved.

The invention discloses a semiconductor packaging device electromagnetic compatibility comprehensive test method and system, and belongs to the technical field of electromagnetic compatibility testing. The method comprises the following steps: collecting structure parameters, packaging topology and predefined function states of a to-be-tested packaging device, and constructing a polymorphic working model; establishing a disturbance injection control model according to each state and configuring disturbance source parameters; implementing dynamic disturbance injection and acquiring response data in a real working state of the device; performing time domain and frequency domain conjoint analysis on the response data, constructing an electromagnetic response dynamic feature sequence, inputting the electromagnetic response dynamic feature sequence into a machine learning model, extracting multi-dimensional coupling features and predicting tolerance; calculating performance indexes such as an interference tolerance score and a coupling strength index based on model output indexes, comparing the performance indexes with a standard, and evaluating a compatible risk level in a full state; the method realizes quantitative evaluation of the EMC performance of the packaging device with high reduction degree and multi-state coverage, and has the advantages of comprehensive test, accurate prediction, explainable attribution and the like.

The invention provides a servo motor real-time adaptive control method and system based on artificial intelligence, and the method comprises the steps: injecting a tiny excitation signal into a servo motor, collecting temperature and electromagnetic response data under different working conditions, and constructing a multi-dimensional information data set; performing real-time reasoning on the relationship between the temperature gradient and the magnetic path characteristics by using deep transfer learning to obtain multi-dimensional parameter deviation vectors such as stator flux linkage unbalance degree, permanent magnet flux weakening degree and torque coefficient change; generating a multi-scale compensation strategy through a physical enhancement reinforcement learning method and the multi-dimensional parameter deviation vector; and carrying out Lie group transformation processing on the control law under a differential geometric framework, and realizing accurate compensation on the temperature gradient effect through a dual-channel-dual-time scale framework. According to the method, heterogeneous sensing and multi-dimensional compensation strategies are adopted, the problem that the control precision of a traditional method is insufficient under the complex temperature gradient condition is solved, and the high-precision motion control performance is maintained under the dynamic working condition that the temperature distribution of the motor is rapidly changed.

The present invention discloses a radar scattering field simulation method for a three-dimensional moving target group combined with a neural network, and belongs to the field of electromagnetic simulation technology. The method of the present invention converts the electromagnetic response of a three-dimensional moving target group into the response of the target when it is distributed at different positions, and extracts the three-dimensional numerical Green's function of the randomly distributed target group in the solution domain by changing the spatial distribution of the target group; the three-dimensional numerical Green's function is split into scattering terms and coupling terms, and the artificial neural network is trained separately; when training the artificial neural network, according to the characteristics of the moving target group, its position distribution and scattering terms / coupling terms are input into the artificial neural network as the main features; the scattering terms and coupling terms output by the artificial neural network model are combined into numerical Green's function terms, which can be applied to integral equations to achieve fast and accurate solution of the scattering field of the three-dimensional moving target group.

The invention provides a digital twinning application-oriented electrical equipment electromagnetic heat flow coupling rapid calculation method, and belongs to the technical field of electrical digital data processing.The method comprises the steps that firstly, a three-dimensional model of electrical equipment is acquired and preprocessed, and a full-order electromagnetic heat flow coupling calculation model is established and verified through a temperature rise test; generating an experimental point matrix by using a Latin hypercube sampling method, and constructing a current temperature power density relational data set; performing regional division on the power density field by applying a K-means clustering algorithm, and constructing an electromagnetic response surface model through a radial basis function; establishing a heat flow field order reduction model based on an intrinsic orthogonal decomposition technology, and extracting a dominant mode primary function; bidirectional coupling of an electromagnetic field and a heat flow field reduced-order model is achieved, an improved Lagrange multiplier method and a fixed point iteration method are adopted for processing the nonlinear coupling problem, finally, a software development kit supporting an open platform communication unified architecture protocol is packaged, and the electromagnetic heat flow coupling rapid calculation capacity needed by digital twinning application is achieved.

The invention discloses an intelligent optimization driving electromagnetic information metasurface multi-dimensional dynamic regulation and control system, solves the problem that the function solidification of an existing metasurface is difficult to dynamically adjust, and belongs to the crossing field of electromagnetic metamaterials and intelligent control technologies. The method comprises the steps that a sensor network collects environment multi-dimensional information of a programmable metasurface unit in real time; the controller processes the environment multi-dimensional information to obtain a multi-dimensional sensing result; the multi-dimensional interaction layer inputs design parameters, the intelligent decision-making layer combines the design parameters and a multi-dimensional perception result to construct a target joint optimization model, reverse design is carried out on the super-surface array coding sequence, and a display array coding pattern and a three-dimensional radiation pattern / two-dimensional radiation pattern are obtained according to the designed super-surface array coding sequence; displaying on the multi-dimensional interaction layer; and the controller performs real-time electromagnetic response reconstruction and 1-bit or 2-bit phase modulation on the programmable metasurface unit through the field programmable gate array according to the designed metasurface array coding sequence.

The invention discloses an underground anti-seepage structure leakage monitoring method and system based on discrete time, and relates to leakage detection. The method comprises the following steps: collecting transient electromagnetic response data generated by an excitation signal; according to the initial conductivity parameter and the electrode position parameter of the monitoring area, establishing a three-dimensional geophysical model of the monitoring area through a full waveform inversion algorithm; obtaining electromagnetic abnormal data by using a finite element forward modeling algorithm; according to the temperature data, a distributed temperature field analysis method is adopted to calculate the space gradient and the time change rate of the temperature, and temperature abnormal data are obtained; according to the pressure data and time sequence change characteristics of the pressure data, determining pressure abnormal data; fusing the electromagnetic abnormal data, the temperature abnormal data and the pressure abnormal data by using a Bayesian algorithm to obtain fused data; and inputting the fusion data into a pre-trained machine learning model to obtain a leakage detection result. Aiming at the low dynamic leakage monitoring precision of the underground anti-seepage structure, the dynamic monitoring precision is improved.

The invention discloses a sea water area karst cave group transient electromagnetic collaborative investigation data processing method and system, and the method comprises the steps: transmitting a wide frequency spectrum excitation signal to the seabed through a shipborne transient electromagnetic transmitting system, and synchronously collecting a secondary field attenuation signal responded by a seabed medium through a pull-type receiving array, meanwhile, a distributed sensor network is arranged at a preset seabed node to collect background noise base data; performing motion attitude compensation on the secondary field attenuation signal to generate transient electromagnetic response data; constructing an adaptive filter based on the background noise base data, performing noise suppression processing on the transient electromagnetic response data, and outputting noise suppression data; and performing space-time alignment on the noise suppression data of the towed array and the seabed node data to form a three-dimensional space sampling data set. According to the method, high-precision fusion of deep and shallow detection data and quantitative evaluation of the stability of the karst cave are realized, and the detection reliability and the engineering risk early warning capability of the complex ocean karst area are remarkably improved.

The invention discloses a three-dimensional moving target group radar scattering field simulation method combined with a neural network, and belongs to the technical field of electromagnetic simulation. The method comprises the following steps of: converting electromagnetic response of a three-dimensional moving target group into response of targets distributed at different positions, and extracting a three-dimensional numerical green function of a randomly distributed target group in a solution domain by changing spatial distribution of the target group; splitting the three-dimensional numerical green function into a scattering term and a coupling term, and training an artificial neural network respectively; when the artificial neural network is trained, position distribution and scattering terms / coupling terms of the moving target group are used as main characteristics to be input into the artificial neural network according to the characteristics of the moving target group; scattering terms and coupling terms output by the artificial neural network model are combined into numerical Green function terms which can be suitable for integral equations, and rapid and accurate solving of a three-dimensional moving target group scattering field is achieved.

The invention relates to a multi-modal multifunctional composite metasurface design method and device and a medium, and the method comprises the steps: carrying out the parameterized sampling of the key size of a unit structure through Latin hypercube sampling, and generating a training sample set; electromagnetic simulation is carried out on the sampled structure to obtain two-state electromagnetic response data, and a mixed variable database is obtained; according to the target response, generating a plurality of groups of candidate structures through a generator in the improved conditional variation auto-encoder generative adversarial network, screening the candidate structures through a predictor, calculating a prediction comprehensive error, and selecting a preset number of candidate structures with the minimum prediction comprehensive error to perform full-wave simulation verification; and obtaining a simulation double-state response, calculating a simulation comprehensive error, and judging the current candidate structure according to a preset comprehensive error threshold value. Compared with the prior art, the method has the advantages of multi-state collaboration, low calculation cost, high degree of freedom and the like.

The invention relates to the field of geophysics and artificial intelligence, and particularly discloses a physical information guided deep learning geoelectric model electromagnetic forward modeling method, which comprises the following steps: S1, preparing neural network input data; s2, building a full-connection deep neural network; s3, adding a physical information constraint, and adding a Helmholtz equation satisfied by an electromagnetic field of the geoelectric model and a boundary condition as the physical information constraint into a loss function; s4, carrying out network training, solving a partial derivative of network output to input by using automatic differential, and obtaining a trained full-connection deep neural network; and S5, result prediction is carried out, the space coordinates of any point are input into the training network with the stored neural network model parameters, and the electromagnetic response of the point in the geoelectric model is obtained. According to the method, the electromagnetic response at any position in the geoelectric model is solved, and an intelligent scheme is provided for calculation of the electromagnetic response in electromagnetic exploration.

The invention discloses a method and a system for constructing a multi-level geologic structure model based on electromagnetic detection, and the method comprises the steps: transmitting electromagnetic signals with different frequencies at all measurement points through an electromagnetic detector, carrying out the resistivity inversion through apparent resistance and impedance phase, obtaining a geologic electrical structure, dividing non-uniform and uniform electrical geology based on electromagnetic static displacement, and obtaining a multi-level geologic structure model. Analyzing an orthogonal component magnetic field to obtain an electromagnetic response parameter and a polarization ellipse parameter; determining an electric field diffusion curve; obtaining an electric field distribution model through finite difference method inversion; deducing underground geological spatial form and distribution law; and finally, calculating an electromagnetic response curved surface to obtain a two-dimensional profile curve, and performing three-dimensional reconstruction to obtain a multi-level geologic structure model. The method not only can improve the precision and reliability of the structure model, but also has good interpretability, and can be directly applied to a construction system of a multilevel geological structure model based on electromagnetic detection.

The invention relates to the technical field of semiconductors, and provides a chip testing method and device based on multi-physics field simulation, and the method comprises the steps: collecting the multi-physics field response data of a chip, carrying out the feature splitting and classification processing, obtaining a thermal response feature vector, an electromagnetic response feature matrix and a stress distribution sequence, and generating a thermal response map; and carrying out correlation calculation on the electromagnetic response characteristic matrix based on the thermal response map to obtain a discriminative risk grade value and an error weighting factor, then carrying out risk trend fitting analysis on the stress distribution sequence, and generating a chip performance stability evaluation index and a test adaptability score under multi-physics field interference. The chip performance stability evaluation index and the test adaptability score under the multi-physics field interference are generated by using the collected multi-physics field response data, so that comprehensive evaluation of the performance of the chip under the multi-physics field effect is realized, and the problem that the accuracy of the test result is insufficient when the chip is in a complex environment in which multiple physics fields act at the same time is solved.

The invention relates to an aluminum pipe local conduction regulation and control method, system and device based on dynamic electromagnetic field modulation and a medium, and the method comprises the steps: driving an electromagnetic coupling array to scan a target conduction region of an aluminum pipe, so as to construct a three-dimensional dynamic electromagnetic model; analyzing and generating a multi-band excitation parameter combination in a bandwidth constraint range according to the target conductivity gradient parameter; the method comprises the following steps: driving an electromagnetic coupling array by a multi-band excitation parameter combination, collecting an electromagnetic response spectrum of a target conductive area in real time, extracting an eddy current characteristic component set, calculating an obtained phase compensation amount, and dynamically adjusting an excitation phase difference and a power ratio of the electromagnetic coupling array to form a controllable standing wave interference field; and solving the Lyapunov function gradient difference between the node distribution characteristics of the standing wave interference field and the predicted value of the three-dimensional dynamic electromagnetic model so as to iteratively update the multi-band excitation parameter combination. According to the invention, high-precision dynamic regulation and control of the conductivity gradient of the aluminum tube are realized, the energy consumption is effectively reduced, and the stability of a standing wave interference field is enhanced.

The invention discloses an antenna structure parameter optimization method based on image translation, and the method comprises the following steps: S1, selecting a to-be-optimized structure parameter according to a basic structure of a target antenna, and determining a target electromagnetic response performance parameter; s2, performing sample generation on the selected structure parameter vector through an LHS algorithm to obtain electromagnetic response data corresponding to the structure parameter; s3, performing image data conversion on the structure parameters and the electromagnetic response data to form a data set, and training an image translation network through the data set; s4, performing image translation on the target electromagnetic response image by using the trained image translation network to obtain a corresponding structure parameter image; and S5, performing parameter extraction on the structure parameter image to obtain structure parameters of the target antenna, and completing antenna design. The method solves the problems that in the prior art, the requirement for priori knowledge of engineers is high, calculation cost and time cost are high, accuracy is insufficient, and generalization of different antenna design tasks is poor.

The invention discloses a fast air-ground transient electromagnetic inversion method based on FiLM-U-net, and belongs to the field of electromagnetic signal data processing, and the method comprises the steps: obtaining geological data and air-ground transient electromagnetic detection data, carrying out the preprocessing, and constructing a data set; dividing a training set, a verification set and a test set; the method comprises the following steps: constructing a FiLM-U-net network model in combination with a FiLM structure and a U-net structure; adopting the training set to select a proper training strategy to train the FiLM-U-net network model, and adopting the test set to evaluate the inversion effect of the model; and the trained FiLM-U-net network model is used to carry out inversion on ground-air transient electromagnetic measured data, transmit-receive positions and ground-air transient electromagnetic response are inputted, and an underground model resistivity value is outputted. According to the invention, the space information can be effectively utilized to carry out efficient and rapid inversion on the ground-air transient electromagnetic signal.

The invention discloses a while-drilling transient electromagnetic remote detection system and method based on ground electrical source excitation. The system comprises a ground grounding electrical source transmitting module, an underground while-drilling three-component receiving module and a data fusion processing module. The underground while-drilling three-component receiving module can perform full-time three-component magnetic field signal acquisition and keep the spatial consistency of measured data; according to the mining area geologic structure, terrain and interference source distribution, emission source parameters, underground drilling positions and a ground well observation network are designed, a ground electric line source continuously excites a transient electromagnetic field, and the ground well observation network and a while-drilling three-component receiving system conduct full-time collection on electromagnetic response and synchronously transmit the electromagnetic response to a ground work station through optical fibers. And the workstation performs terrain static correction and signal preprocessing on the received signal, and realizes accurate detection of the Ordovician limestone aquifer, integrity evaluation of the grouting curtain and dynamic monitoring of the mining-induced fissure zone by fusing ground-roadway-drilling multi-source data.

A power transmission tower grounding resistance non-contact measurement method based on the electromagnetic coupling principle comprises the following steps that transmitting and receiving electromagnetic coupling coils are arranged around an iron tower grounding body, and geometric calibration and spatial positioning of a measurement area are completed by combining grounding grid structure parameters and soil conduction characteristics; injecting a high-frequency alternating-current excitation signal into the transmitting coil, and synchronously acquiring the amplitude and phase response of the induced voltage at a receiving coil end; carrying out filtering processing on the induction signal by adopting a time-frequency analysis and phase decoupling algorithm, and solving a function relationship between electromagnetic response and grounding impedance by combining a coupling equivalent model; based on experimental calibration data and scene parameters, a nonlinear mapping model of induction response and grounding resistance is constructed, and real-time inversion calculation is carried out by combining a solving result obtained in the third step. According to the invention, the real-time accurate measurement of the grounding resistance under the conditions of no power failure and no wire breakage is realized, and the safety, the operation convenience and the anti-interference capability in a complex environment in the measurement process are obviously improved.

The invention provides a metal pipeline defect detection method based on a time-frequency domain electromagnetic method, which comprises the following steps of: (1) establishing a time-frequency domain dual-mode electromagnetic sensor test system with parallel time-frequency domain coils, and respectively measuring and acquiring electromagnetic response parameters through two modes; (2) measuring by a frequency domain method to obtain a function relationship of the depth dn of the near-surface small-size defect with respect to the surface size r of the small-size defect and an induced voltage difference value Ufd; (3) measuring by a time domain method to obtain a function relationship between the attenuation rate k and the thickness D; and (4) performing detection optimization on different types of defects through data fusion of a time domain method and a frequency domain method.

The invention relates to the technical field of electromagnetic metasurfaces and bionic computing, and discloses a bionic information processing method and system based on an electromagnetic metasurface. The method comprises the following steps: S1, mapping DNA sequence information into a multi-dimensional coding state of the bionic metasurface information processing unit in an electromagnetic adjustable parameter space; s2, realizing co-evolution of the multi-dimensional coding state in space, frequency, phase and amplitude dimensions by dynamically regulating and controlling electromagnetic response parameters of the bionic metasurface information processing unit; and S3, using propagation and interference of electromagnetic waves in the diffraction neural network and a near-field coupling effect between the bionic metasurface information processing units to complete copying, logical operation and information read-write operation of the DNA sequence information. The functions of DNA coding, copying, logic calculation, information reading and writing and the like are uniformly mapped into the programmable electromagnetic metasurface platform, and cooperative processing of information in the aspects of space, electromagnetism and algorithm is achieved.

The invention relates to the technical field of geological prospecting, in particular to a cube prediction model prospecting method and system based on three-dimensional modeling, and the method comprises the following steps: based on the position information of a prospecting point, employing an electromagnetic imaging device, adjusting scanning parameters, collecting reflection electromagnetic waves at a plurality of positions of a target area, and calculating the position information of the prospecting point; and recording electromagnetic response data under various frequencies and intensities, and generating electromagnetic characteristic data. According to the method, by integrating electromagnetic imaging and geological data interpolation technologies, the underground structure is accurately evaluated and mapped, construction of a geological model is optimized, the utilization rate of data is improved, uncertainty and risks in mining are reduced, and by analyzing geometric morphology and texture features of an ore body, underground minerals are detected and distribution features are identified, so that the mining efficiency is improved. The method effectively guides the mineral exploitation strategy, optimizes the resource allocation, reduces the environmental damage and exploration cost, and enhances the scientificity and economic benefits of geological exploration through the deep analysis and model optimization of geological data.

The invention provides an active circuit electromagnetic response characteristic modeling analysis method and related equipment, and relates to the technical field of integrated circuits. According to the method, the to-be-analyzed active circuit is divided into the circuit component units mainly relating to nonlinear characteristic changes and the circuit carrier plate mainly relating to linear characteristics and only comprising unit connection wiring, and based on circuit component S parameter actual measurement operation in any strong field environment, complex nonlinear modeling errors are avoided, and the system reliability is improved. Meanwhile, on the basis of wiring S parameter simulation operation in a corresponding strong field environment, the high-frequency electromagnetic coupling effect of circuit connection wiring is accurately captured, the circuit modeling calculation amount is reduced, and then through cascading fusion analysis operation on wiring simulation S parameters and assembly actual measurement S parameters, the wiring simulation S parameters and the assembly actual measurement S parameters are analyzed; the rapid collaborative analysis of the wiring electromagnetic coupling response and the component nonlinear behavior is realized, so that the real electromagnetic response characteristic condition of the specified active circuit in the corresponding strong field environment can be rapidly and accurately reproduced, and the rapid iterative optimization effect of the active circuit design can be conveniently realized.

The invention provides an on-line intelligent monitoring system based on a coil, and relates to the technical field of data processing, and the system is used for calculating the comprehensive coupling degree between coil magnetic field change and current response according to monitoring data, obtaining a magnetic response correlation value, constructing a distribution matrix of coil magnetic field distribution characteristics, obtaining a coil local coupling map, and obtaining a current response correlation value. The method comprises the following steps: calculating the influence degree of temperature change on magnetic flux energy offset, obtaining a temperature drift correction value, identifying the relative offset trend of electromagnetic response and energy compensation, obtaining a phase offset, calculating the response self-stabilization degree of a coil in long-term operation, obtaining a dynamic balance factor, and identifying the dynamic characteristics of the coil in electromagnetic, temperature and space response dimensions. And judging whether the coil is in a response instability state or a normal operation state to obtain monitoring state result data. The state of the coil is monitored by identifying coupling characteristics of electrical parameters and temperature of the coil.

The invention discloses a machine learning-assisted metasurface loading and decoupling patch antenna design method, particularly relates to the technical field of antenna design, and solves the problem that in the prior art, a metasurface loading and decoupling patch antenna design method can only realize port decoupling but cannot realize directional diagram decoupling. And the design method needs complex theoretical analysis calculation and time-consuming parameter optimization. According to the technical scheme, a data set composed of a pixelated metasurface and electromagnetic response is used for training an agent model, and a parameter optimization algorithm is combined with the trained agent model to update parameters according to a cost function; according to the method, the problem of simultaneous decoupling of the port and the directional diagram can be solved, and complex theoretical analysis calculation and time-consuming parameter optimization can be avoided.

The invention discloses a full-waveform targeted detection method for a time domain electromagnetic induction-polarization effect. The method comprises the following steps: establishing a fractional order polarization model based on geological data; full-waveform numerical simulation of multiphase polarization medium three-dimensional electromagnetic response is carried out based on a time domain finite analysis method, full-waveform characteristics of an induction-polarization symbiotic effect are analyzed, and a targeted excitation relation is constructed; a time domain electromagnetic transmitter based on full-waveform current control realizes bipolar trapezoidal wave current transmission with linear ascending and descending and controllable slope, and respectively excites an induction effect and a polarization effect of an underground medium; and after the received full-waveform data is preprocessed, parameters such as polarizability, resistivity and the like are extracted, and imaging is carried out. The full-waveform target detection of the time domain electromagnetic induction-polarization effect is realized, the detection blind area is eliminated, and the purpose of improving the detection precision and efficiency of the time domain electromagnetic method is achieved.

The invention discloses a stratum parameter inversion method of an inversion neural network based on asymmetric down-sampling, and relates to a while-drilling azimuth electromagnetic wave data processing technology, and the method comprises the steps: enabling adjacent one-dimensional stratum samples to form a locally continuous two-dimensional stratum sample; carrying out nonlinear compression on R response and G response in the logging response data, and then standardizing to obtain preprocessed logging electromagnetic response data; the preprocessed logging electromagnetic response data serve as input data of an inversion neural network, the corresponding two-dimensional stratum samples serve as labels, and training of the inversion neural network is completed; the inversion neural network adopts a network topology structure of an encoder and a decoder, feature maps of the same size are fused through jump connection, feature maps of different sizes are subjected to horizontal single-dimension down-sampling and up-sampling through a down-sampling module based on maximum pooling and an up-sampling module based on transpose convolution, vertical dimension information is reserved, and the feature maps of different sizes are subjected to horizontal single-dimension down-sampling and up-sampling. And high-precision real-time stratum parameter inversion can be realized.

The invention discloses a magnetotelluric sounding measurement method for multidirectional aggregation observation, and the method comprises the steps: building a novel device layout: designing a reasonable measurement point layout scheme according to geological features and electromagnetic response distribution; processing data and establishing an unstructured grid: acquiring an electromagnetic field component, completing data acquisition, and inputting the processed electromagnetic field data into an unstructured grid model; impedance tensor calculation: on the basis of the unstructured grid, performing impedance calculation by utilizing multi-component electromagnetic field data and combining an interpolation idea, and constructing an extended impedance tensor of an electromagnetic field component to obtain an impedance value component; and three-dimensional inversion and visualization: performing three-dimensional inversion through a vector finite element method to obtain an inversion result. According to the method, richer observation data are provided for deep geologic structure inversion.

The invention discloses a knowledge-driven intelligent metasurface unit rapid design method based on double neural networks. Aiming at the problems that a traditional intelligent metasurface unit design process depends on a large amount of electromagnetic simulation and is complex in calculation and low in efficiency, the invention provides a dual-artificial neural network (ANN) proxy model optimization framework combined with physical knowledge guidance. The method comprises the following steps: firstly, respectively training two neural network models to predict the amplitude and phase response of a metasurface unit of a tuning element in different extreme working states; and then, according to the physical prior knowledge of monotonic change of tuning element parameter change on electromagnetic response, the maximum reflection loss and phase difference under any geometric parameter combination are quickly and accurately deduced, so that double-target optimization design assisted by the agent model is realized. By means of the method, the design efficiency and performance of the metasurface unit can be greatly improved, dependence on traditional full-wave electromagnetic simulation is remarkably reduced, and the effectiveness and superiority of the method are verified through simulation and experimental results.

The invention belongs to the technical field of electronic information, and discloses a multi-modal deep learning model construction method, medium, equipment and application for metasurface electromagnetic characteristic estimation, and the method comprises the steps: carrying out the binaryzation of metasurface patterns corresponding to all structure parameter vectors in a metasurface parameter space; constructing a multi-modal deep learning model MMN and initializing trainable parameters; calculating an accurate electromagnetic response corresponding to the structural parameter vector by using a finite element method, taking the structural parameter vector and the binarization matrix as input, taking the electromagnetic response as output, and pairing to form a training sample set; and training an MMN model by using a gradient descent method according to the loss function and the training sample set. The MMN model obtained by the invention can accurately estimate the electromagnetic characteristics of the metasurface, and the size of the required training sample set is 39% of the size of the sample set required by a single-mode model.