224 results about "Electromagnetic response" patented technology

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.

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 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 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 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 an electromagnetic field simulation method under the coupling action of tidal waves and sea waves. The method comprises the steps that input parameters of the tidal waves and the sea waves are set; configuring environmental parameters and geomagnetic conditions; superposing the tidal wave velocity field and the sea wave disturbance velocity field to form a total velocity field; the tidal wave part and the sea wave part are linearly coupled in time and space to obtain a tidal wave-sea wave coupling field evolved along with a tidal phase; in the tidal wave-sea wave coupling field, electromagnetic response calculation is executed on each frequency-direction sampling point; general field synthesis and modulation effect analysis: introducing a tidal wave modulation factor to clearly reflect amplitude periodic change and spectrum reconstruction characteristics of an electromagnetic field signal along with a tidal phase; and outputting a time sequence, an amplitude spectrum and a spatial distribution result of the comprehensive electromagnetic field. According to the method, the authenticity and applicability of sea wave induction electromagnetic field simulation can be improved, and a new technical means is provided for electromagnetic noise recognition, sea wave parameter inversion and complex ocean dynamics process research.

An example method for improving a metasurface design may include providing a first wavefront; providing a library of metasurface elements, wherein each metasurface element has a variable phase response; creating a metasurface design by selecting metasurface elements via the library based on the first wavefront; simulating an electromagnetic response of the metasurface design; measuring a second wavefront based on the metasurface design; calculating an error between the first wavefront and the second wavefront; and generating a new phase profile by subtracting the error from the first wavefront and the second wavefront. Various other methods, systems, and computer-readable media are also disclosed.

The invention discloses an internal wave electromagnetic response numerical simulation method based on a layered ocean model. The method comprises the following steps: acquiring geomagnetic field parameters; calculating distribution characteristics of seawater conductivity along with depth, and dispersing the distribution characteristics into a layered ocean conductivity model; an internal wave mechanical model is constructed, internal wave velocity field distribution is established through characteristic parameters of internal waves, and dynamic input is provided for electromagnetic field response calculation; substituting the internal wave velocity field and the geomagnetic field into a Maxwell equation set, and constructing an internal wave induction electromagnetic field control equation; and applying tangential electric field continuity and normal current continuity conditions on a layered interface, and performing discrete and iterative solution on an equation by adopting a finite difference method to obtain distribution characteristics of the electric field and the magnetic field at different depths and frequencies. According to the method, the problem of insufficient precision caused by a uniform conductivity hypothesis is solved, and application limitation caused by an ideal geomagnetic field hypothesis is avoided, so that accurate simulation of internal wave induction electromagnetic response under a complex ocean condition can be realized.

The invention discloses a pre-phase-based one-bit beam reconfigurable metasurface antenna device, which comprises a pre-phase-based one-bit metasurface antenna unit which is designed by adopting a resonance scattering analysis method, two microstrip line paths with different lengths are switched through a single-pole double-throw switch, so that a 180-degree phase difference of a signal is obtained to realize 1-bit phase regulation and control, and the one-bit beam reconfigurable metasurface antenna device is obtained. Electromagnetic simulation software is utilized to optimize geometric parameters and output reflection electromagnetic response of the design model; the overall design of the reconfigurable antenna array panel is carried out based on the designed unit model, and the reconfigurable antenna array panel comprises a sub-panel composed of a plurality of low-cost microstrip antenna array units and a control panel connected with external feed equipment and a main panel.

A medical-device navigation system includes, in some embodiments, an electromagnetoresponsive (“EMR”) element, a magnetic interrogator, and a console. The magnetic interrogator generates an external magnetic field, transduces resonance-based responses of the EMR element thereto, and provides response data for the EMR element as an elongate portion of a medical device including the EMR element moves through the external magnetic field. The console instantiates medical-device navigation processes including a data-acquisition process, a triangulation process, and a plotting process for navigating the elongate portion of the medical device as it is advanced through the external magnetic field to a target location. The data-acquisition process acquires the response data from the magnetic interrogator over time, the triangulation process triangulates the EMR element with respect to magnetic sensors of the magnetic interrogator over time, and the plotting process plots a location of the EMR element on a display screen of the console over time.

The invention discloses a multi-sensor fusion target scoring system high-precision positioning method, and relates to the technical field of target scoring positioning, and the method comprises the following steps: building a transient interference recognition channel based on the electromagnetic response of a shock wave sensor, obtaining the electromagnetic disturbance of the bullet hit front edge, and generating an interference time sequence; performing delay triggering on the image sensor according to the interference time sequence, and avoiding an interference peak value to form a safe exposure time period; performing charge pre-release on the image acquisition chain before safe exposure; carrying out synchronous compensation on the shock wave signal based on energy distribution of charge pre-release, so that the shock wave signal and image energy response are symmetrical and mutually stable in a time domain; and dynamic shielding control is carried out on a space coupling path between the two types of sensors by utilizing an energy balance region formed in the mutual stable state. Through energy symmetric compensation and dynamic shielding control of shock waves and image signals, time-space separation and synchronous mutual stability of the signals are achieved, and high precision and stability of target scoring positioning under high-energy shooting are ensured.

The invention discloses a building electrical circuit arc fault multi-dimensional detection and positioning method and system. The method comprises the following steps: injecting a low-amplitude broadband excitation signal into a key node of a power distribution loop through an electromagnetic excitation and sensing device, collecting a line response waveform and establishing a steady-state electromagnetic response baseline; performing self-correlation operation and spectral analysis based on the baseline, extracting formant frequency, energy distribution and bandwidth characteristics, and generating an electromagnetic modal characteristic fingerprint; through constructing a time-frequency coupling resonance matrix, formant frequency shift amount and energy gradient change are monitored in real time, and an abnormal resonance state of a line is identified. After abnormality is detected, establishing a spatial positioning equation according to multi-node phase distribution, and determining the position of an arc or a breakdown source by adopting a phase inversion algorithm; calculating a line stability coefficient by combining a positioning result and time sequence resonance data, and predicting an arc risk level; when the risk level exceeds a threshold value, an electromagnetic compensation module is activated, an opposite-phase suppression signal is generated and injected into an abnormal area, and active protection closed-loop control is achieved.

The invention provides a partial discharge detection system based on a Rydberg atom quantum coherence effect, and the system comprises an optical excitation module which is used for transmitting two-photon laser to excite hot atoms to enter a Rydberg state; the atomic gas chamber is used for accommodating hot atoms and is coupled with an electromagnetic field generated by the partial discharge signal, so that the hot atoms generate energy level response change under the action of the electromagnetic field; the detection light path module is used for detecting a change signal of light signal intensity in the atomic gas chamber and converting the change signal into an electromagnetic response characteristic of an electromagnetic field; the signal acquisition and processing module is used for receiving the electromagnetic response characteristics, demodulating and analyzing the electromagnetic response characteristics and extracting characteristic parameters of the partial discharge signals; and the control and calibration module is used for receiving the characteristic parameters of the partial discharge signal, performing calibration based on an energy level frequency shift rule of Rydberg atoms, and outputting electric field intensity subjected to quantization calibration. The system can realize high-sensitivity, anti-interference and traceable detection of weak partial discharge signals.

The invention discloses an overlying strata fracture electromagnetic imaging method and a grouting system, and particularly relates to the technical field of geological fracture imaging. The invention discloses an overlying strata fissure electromagnetic imaging method and a grouting system. The method comprises the steps that S1, magnetic source slurry containing permanent magnetic material particles is injected into a target overlying strata fissure area through the grouting system; s2, magnetizing the magnetic source slurry injected into the crack through an electromagnetic coil group arranged on the grouting system; s3, tracer slurry containing magnetic responsive nanoparticles is injected into the fissure area where the guiding magnetic field is formed through a grouting system; s4, in-hole electromagnetic detection equipment is adopted to scan the fracture area filled with the tracing slurry, and electromagnetic response data are obtained; and S5, processing and analyzing the electromagnetic response data. According to the overlying strata fissure electromagnetic imaging method and the grouting system provided by the invention, through a technical path of'pilot magnetism and post tracing ', the tracing slurry is actively guided to directionally migrate by utilizing the magnetic field, and high-precision filling and electromagnetic imaging of an overlying strata fissure network are realized.

The invention discloses a geological exploration method based on a time-frequency electromagnetic method, and the method comprises the following steps: obtaining time-domain and frequency-domain electromagnetic signal data, and obtaining time-frequency spectrum data through time-frequency conversion processing; the time-frequency spectrum data determines response characteristics in the dense stratum according to the signal attenuation degree; generating an excitation waveform according to the response characteristics to obtain a time-frequency electromagnetic response model; extracting propagation laws of different frequency components from the time-frequency electromagnetic response model, and adjusting the frequency priority based on high-frequency attenuation; performing compressed coding on the time-frequency spectrum data according to the adjusted frequency priority to obtain a compressed data packet, and transmitting the compressed data packet through a stable communication link; and decoding the transmitted data packet to obtain original time-frequency spectrum data, and verifying a signal penetration effect based on the time-frequency electromagnetic response model to judge the reservoir identification accuracy.

The invention discloses a photovoltaic buried cable fault positioning system based on a graph neural network, and the system comprises a multi-source signal collection module which is used for collecting electromagnetic response characteristics, and generating a multi-source signal sample set; the topological relation construction module is used for forming weighted directed topological relation data; the frequency domain mapping and fusion module is used for forming frequency domain-space joint feature input; the frequency domain self-evolution graph neural model module is used for executing feature propagation and aggregation of nodes and edges and outputting fault probability and uncertainty results; the space-time active detection module is used for selecting a cable section in an area with the maximum potential energy as an active detection target to form a self-tuning active detection closed loop; and the multi-source constraint correction module is used for outputting the type, the position and the confidence degree result of the buried cable fault. According to the invention, through the frequency domain self-evolution graph nervous system, accurate identification and positioning of the photovoltaic buried cable fault are realized.

The invention discloses a heat-shrinkable cable shielding layer damage detection method and equipment based on pulsed eddy current, and relates to the technical field of cable shielding layer damage detection.The method comprises the steps that a pulsed eddy current probe is arranged on the outer surface of a cable, preset pulse excitation is applied, an original transient electromagnetic response signal is collected, and a reference phase signal is constructed; performing synchronous phase-sensitive demodulation, and extracting an in-phase component and an orthogonal component to obtain a phase purification signal; based on the difference of the spatial statistical characteristics of the shielding layer response and the conductor response, performing spatial joint reconstruction on the phase purification signal to obtain a purification reconstruction signal; based on the purified reconstruction signal, extracting damage characteristics, performing cable shielding layer damage judgment, and positioning a damage area; the method effectively solves the problems that the electromagnetic response of the internal conductor and the response of the shielding layer are highly overlapped and are difficult to separate, and the damage characteristics are easily covered by noise and spatial fluctuation, so that the damage identification sensitivity and positioning precision of the shielding layer are insufficient in the existing pulsed eddy current detection.

The invention discloses a linear kick rapid opening and closing control method for an isolating switch, and particularly relates to the technical field of opening and closing control of high-voltage isolating switches. Collecting a linear displacement signal between the conductive arm and the static contact and an electromagnetic driving current change curve, and constructing a kick behavior data matrix; establishing a multi-dimensional state energy threshold model based on the peak acceleration and the zero crossing point; combining a real-time current response curve to complete kick prediction trajectory fitting; fast phase torque compensation is carried out according to the current phase deviation angle, and an active suppression control pulse sequence is generated to realize kick phase locking; a damping recovery coefficient is further calculated based on aftershock feedback, an electromagnetic response factor at the moment of operation is fused, a final control instruction sequence is generated and output to a driving unit, and accurate and high-speed switching-on and switching-off operation is achieved; the method has the advantages of fast control response, strong anti-disturbance capability, high adaptability and the like, and is suitable for accurate control of the isolation switch in various complex power scenes.

The embodiment of the invention provides a frequency selective surface agile design method and device based on a multi-scale convolutional neural network, a storage medium and electronic equipment, and relates to the field of frequency selective surface design, and the method comprises the steps: carrying out the electromagnetic simulation of a frequency selective surface structure, constructing a data set containing the corresponding relation between the geometric parameters and the electromagnetic response; based on the data set, adopting a multi-scale convolutional neural network to extract multi-scale features of the electromagnetic response of the frequency selective surface structure, performing feature fusion processing, and outputting to obtain an electromagnetic response prediction result; and performing iterative calculation on the electromagnetic response prediction result by using a particle swarm optimization algorithm until the electromagnetic response prediction result meets a given electromagnetic performance target of the frequency selective surface. According to the technical scheme, complex frequency selective surface multi-target design requirements of multiband, broadband, large-angle stability, multi-polarization and the like can be effectively met, and the limitation of a traditional method is broken through.

The invention discloses an intelligent design method for a dual-frequency wide-angle high-transmission metasurface, which comprises the following steps of: performing layered sampling on geometric structure parameters of a metasurface unit, performing equal-interval sampling on incident angles, performing full-wave electromagnetic simulation on a parameter sample group to obtain transmission electromagnetic response data, and constructing a database; a multi-layer perceptron neural network is used for learning a nonlinear mapping relation among geometric structure parameters, incident angles, frequencies and transmission coefficient amplitude values, and an independent test sample is used for evaluating the prediction precision and generalization ability of the trained multi-layer perceptron neural network under wide angles and dual frequency bands. A substitution model is constructed based on the trained multi-layer perceptron neural network, the substitution model is embedded into a global optimization process, structural parameters are iteratively optimized in combination with a heuristic search algorithm, an optimal design meeting a dual-band high-transmittance index is obtained, the precision and efficiency of metasurface design are remarkably improved, and the performance of the metasurface design is improved. While the wide-angle double-frequency high transmission performance is ensured, the design period is greatly shortened.

This invention discloses a filter physical perception optimization method based on residual attention and transposed convolution, comprising the following steps: constructing a filter characteristic prediction surrogate model based on residual self-attention mechanism and transposed convolution decoding to establish a nonlinear mapping relationship between filter geometric parameters and electromagnetic response parameters; training the filter characteristic prediction surrogate model using an S-parameter weighted mean square error loss function to obtain a trained filter characteristic prediction surrogate model; and using a physical perception-improved differential evolution algorithm, employing the trained filter characteristic prediction surrogate model as a predictor to find the optimal combination of geometric parameters that satisfies the filter design specifications in the solution space. This method is a filter optimization design method that balances high-precision prediction and high-efficiency optimization. This method can predict the S-parameters of microwave filters more accurately than traditional neural networks, effectively replacing time-consuming full-wave electromagnetic simulation.

The invention discloses a forward modeling simulation method for a multidirectional sea wave induction electromagnetic field. The method comprises the following steps: expressing energy distribution of different propagation directions and frequency components through a spectral function; setting external environment input required by forward modeling according to the seawater depth and geomagnetic field parameters of the research area; after parameter setting is completed, electromagnetic response calculation is carried out on each frequency-direction sampling point; component response is called on a preset frequency set and a preset direction set, linear superposition is carried out by adopting a frequency direction correspondence method, and a total electromagnetic field is obtained; and outputting time sequences and frequency spectrum results of the wind wave induction electromagnetic field, the surge induction electromagnetic field and the mixed wave induction electromagnetic field, thereby providing a reference basis for noise analysis, background interference suppression and target signal identification in electromagnetic detection. According to the method, the limitation of a traditional model is broken through, the electromagnetic interference characteristics under the complex sea condition are represented more truly, and reliable support is provided for noise suppression and target recognition in electromagnetic detection.

The embodiment of the invention provides an RIS cascade channel model simplification method and device based on cluster deletion, and relates to the technical field of wireless communication. The method comprises the following steps: generating a first multipath of a first channel from a transmitting end to a reconfigurable smart surface (Tx-RIS), and generating a second multipath of a second channel from the RIS to a receiving end (RIS-Rx); performing power normalization and arrangement processing on the first multipath and the second multipath respectively; respectively carrying out convolution operation on the first multipath and the second multipath according to the sorting sequence, and determining reserved multipath combination information; calculating RIS electromagnetic response according to the multipath combination information; and generating a channel impulse response of Tx-RIS-Rx according to the RIS electromagnetic response. According to the scheme provided by the invention, the cluster or multipath component with low power ratio is removed from the Tx-RIS and RIS-Rx sub-channels, so that the modeling complexity is effectively reduced and the modeling efficiency is improved on the premise of ensuring the statistical channel characteristics.

The invention relates to the technical field of geophysical exploration, and discloses a ground-air transient electromagnetic data fast inversion method based on a long and short term memory network, comprising the following steps: constructing a ground-air transient electromagnetic training data set, including generating resistivity and thickness parameters through a random stratified model, generating corresponding transient electromagnetic response data based on forward modeling simulation; preprocessing the training data set, wherein the preprocessing comprises normalization, time sequence remodeling and data set division; and constructing a CNN-BiLSTM-Attention hybrid neural network model, wherein the model comprises a CNN feature extraction module, a BiLSTM time sequence modeling module, an attention mechanism module and a Seq2Seq decoder module which are connected in sequence. According to the ground-air transient electromagnetic data rapid inversion method based on the long and short term memory network, reasoning is performed by using the trained network, the inversion time of a single measuring point can be shortened to a second level, a traditional several-day interpretation period is compressed to an hour level, and the response speed of geological disaster monitoring and exploration is greatly improved.

This invention belongs to the technical field of digital design of Roots blower equipment, specifically involving a digital twin-based digital design method for the dynamic performance of blowers. This method includes constructing a parametric structural model of multiple components of the blower, establishing a multi-physics coupled model encompassing aerodynamics, structure, heat, electromagnetics, and acoustics, applying dynamic boundary conditions such as flow disturbances, inertial forces, and base disturbances, constructing a digital twin model synchronized with the physical blower state, performing a master-slave strongly coupled joint solution, extracting multi-field response indices and performing normalization analysis, and finally outputting optimized design parameters for the blower through a multi-objective optimization feedback mechanism. This invention enables multi-domain balanced design among the blower's structural performance, electromagnetic response, thermal stability, and acoustic characteristics, improving modeling accuracy and parameter optimization capabilities, and is suitable for the digital development of high-reliability Roots blower equipment under complex operating conditions.

This invention discloses a multi-channel electromagnetic induction detection method and system based on uniform magnetic field constraint. A uniform magnetic field is constructed within the detection area of ​​the structure under test. Electromagnetic induction response signals are acquired through multiple channels under the constraint of the uniform magnetic field, and the spatial coordinates of each acquisition channel are marked. The raw electromagnetic induction signals acquired by each channel are preprocessed, including noise reduction filtering, envelope extraction, and amplitude normalization. A deep learning model is then used to extract structural features from the preprocessed multi-channel electromagnetic response signals. Based on the spatial position information of each acquisition channel, magnetic field uniformity parameters, and response characteristics, a channel correlation weight matrix is ​​constructed to describe the spatial consistency and physical coupling relationships between channels. A multi-channel joint optimization model is constructed, and the equivalent electromagnetic parameter distribution inside the structure under test is reconstructed through iterative solution. This invention improves the reliability, repeatability, and engineering applicability of electromagnetic induction detection results.

The application discloses a kind of based on multi-objective optimization algorithm's metasurface reverse design dataset generation method, this method includes: determining the regular topological structure of metasurface, structure parameter and resistance lumped element value are as optimization variable, and population is constructed;Set multiple electromagnetic performance indexes with competitive relationship as optimization goal;Using NSGA-II algorithm to iterate optimization to population, in each iteration process, based on optimization goal to the non-dominated sorting and crowdedness calculation of current population individual, filter and generate next generation population;Collect the structure parameter, resistance lumped element value and electromagnetic response data corresponding to all or part of population individual generated in iteration process, construct the metasurface reverse design dataset for training metasurface reverse design network.The application generates data for multiple regular topological structure metasurfaces by setting multiple competitive performance goals, using NSGA-II algorithm, to improve the training efficiency of reverse design network.

The invention discloses a method for constructing a high-conductivity / heat-conductivity carbon material based on microwave induction, and belongs to the technical field of nano carbon material synthesis. According to the method, methane and auxiliary gas are introduced into a variable-frequency microwave vapor deposition system, and the microwave frequency is dynamically regulated and controlled within the range of 2.43-7.5 GHz, so that the methane cracking rate, plasma energy distribution and deposition kinetics are regulated; controllable deposition of multi-scale and multi-morphology composite carbon structures (carbon nanotubes, graphene-like and amorphous carbon) on the surface of a single substrate under the constant temperature condition is achieved, and therefore the microstructure and the electromagnetic response performance are optimized. According to the method, the frequency conversion microwave technology is introduced into a methane cracking deposition system for the first time, atomic-scale controllable deposition of the carbon material is achieved, complex temperature gradient control is avoided, and the obtained carbon-based material has high electric conductivity / heat conductivity, wide-frequency-band shielding effectiveness and excellent structural stability.

The application discloses a parameterized modeling method of coded supercell electromagnetic response combining a polynomial transfer function and deep neural network incremental learning, and realizes accurate prediction of electromagnetic response by constructing a deep neural network that fuses self-adaptive homogeneous processing to learn the corresponding relationship between polynomial transfer function coefficients and coded supercell structures. Simulation results show that the electromagnetic response parameter curve of the supercell in the test set predicted by using the parameterized modeling method highly fits the full-wave simulation result of the supercell, and the accuracy is better than that of other traditional methods.

The invention relates to the field of microwave device modeling, and discloses a microwave device neural network modeling method based on a convolutional auto-encoder and accompanying sensitivity analysis. On the basis of an auto-encoder framework, a convolution auto-encoder is adopted to extract transmission function parameters, and electromagnetic accompanying sensitivity analysis is combined to construct a novel artificial neural network agent model. In the model, the convolution auto-encoder captures local correlation characteristics of an input signal by using a convolution kernel to realize efficient compression and stable reconstruction of high-dimensional data, so that the problems of discontinuity and instability in a traditional method are solved. Meanwhile, electromagnetic accompanying sensitivity analysis is introduced, gradient information of electromagnetic response to geometric parameters is obtained with low calculation cost, the gradient information is fused into the neural network training process, and the precision and generalization ability of the model are remarkably improved.