4260 results about "Electromagnetics fields" patented technology

The invention provides an unmanned aerial vehicle multi-dimensional information fusion method and system based on acousto-optic-electric composite detection. According to the method, acoustic frequency band signals, visible light image sequences and electromagnetic field intensity change data are collected, acoustic characteristic flow, optical characteristic flow and electrical characteristic flow are generated, and based on the time deviation between a low-frequency vibration mode and transient electromagnetic pulses, multi-channel dynamic calibration is carried out on an image distortion area in the optical characteristic flow. The method comprises the following steps: acquiring an acoustic feature flow, an optical feature flow and an electrical feature flow, correcting space-time coordinate parameters of the acoustic feature flow, the optical feature flow and the electrical feature flow, generating a calibration feature flow, carrying out anti-interference fusion processing on the calibration feature flow, extracting multi-dimensional coupling features, inputting the multi-dimensional coupling features into an unmanned aerial vehicle flight path planning model, and generating a three-dimensional space situation model; according to the invention, the physical space-time consistency alignment and noise suppression of the multi-modal data are realized, and the obstacle positioning precision and the dynamic trajectory prediction real-time performance are significantly improved.

The invention provides a fan system multi-physics field coupling simulation and modeling method and device, and the method comprises the steps: building a coupling simulation frame of an electromagnetic field, a temperature field, a flow field and a structural mechanical field through multi-physics field collaborative modeling, employing a finite volume method FVM and multi-body dynamics MBS for collaborative solving, and precisely simulating the dynamic response of a fan under a complex working condition. And real-time simulation and verification: combining an S CADA system and a machine learning algorithm to realize online calibration and dynamic verification of a multi-physics field model, and supporting fan structure stability prediction under extreme conditions of typhoon, turbulence and the like. A multi-physics field coupling simulation software environment is developed, the functions of wake effect analysis, fan array layout optimization and the like are provided, the construction cost of an offshore wind field is reduced, and the power generation efficiency is improved.

The invention discloses a power transmission line connection fitting fault detection method based on acoustics and electromagnetic induction, and belongs to the technical field of intelligent inspection and nondestructive detection of power transmission lines. A multi-mode sensor is carried by an unmanned aerial vehicle, ultrasonic wave, vibration, images and power frequency electromagnetic field data are synchronously collected, and a multi-dimensional original data set is constructed. Signal quality is improved by adopting wavelet noise reduction, beam forming and sound image fusion technologies, and flight vibration and electromagnetic interference are effectively suppressed by combining an adaptive filtering algorithm and a physical shielding structure. And acoustic, image and electromagnetic characteristics are extracted and normalized and fused, a dynamic threshold reference library is established, and intelligent grading discrimination of abnormity, defects and faults is realized through multi-stage early warning logic. A detection result automatically generates a report and is mapped to a three-dimensional line model, and operation and maintenance system linkage is supported. According to the method, synchronous identification of surface and internal defects is realized, the anti-interference capability is high, the detection accuracy is high, the inspection efficiency and safety are remarkably improved, and the method is suitable for intelligent operation and maintenance of the high-voltage transmission line.

The invention relates to the technical field of electromagnetic environment detection, and discloses a multi-mode electromagnetic environment detection system and method. The system acquires multi-modal data such as electromagnetic field intensity and spectrum distribution through a multi-modal sensor array to generate a data set, and realizes interference source identification and dynamic adjustment of detection parameters through nonlinear signal processing, depth feature extraction based on a convolutional neural network, topology analysis of a graph neural network and adaptive optimization of reinforcement learning. And an electromagnetic field simulation module is also arranged to simulate electromagnetic wave propagation and early warn abnormal radiation, and an abnormal mode library is constructed to identify potential interference types. The system can comprehensively and accurately detect an electromagnetic environment, efficiently position an interference source, adaptively adjust detection parameters, improve detection accuracy, real-time performance and system stability, and effectively meet complex electromagnetic environment monitoring requirements.

The invention relates to the technical field of aircraft structure detection, and discloses an aircraft structure crack intelligent identification method based on deep learning. The method comprises the following steps: acquiring original vibration response signals and electromagnetic field distribution data on the surface and inside of an aircraft structure in parallel through a multi-source sensor network; synchronously processing the data by using a multi-scale convolutional neural network, and extracting time-frequency domain abnormal fluctuation features and space magnetic field distortion features; constructing a cross-modal correlation model, analyzing a topological dependency relationship of the two types of features through a graph attention mechanism, and generating a fused damage sensitive feature vector; inputting the vector into a pre-trained deep belief network to obtain a probability distribution mapping relation for different crack types; and according to the mapping relation, carrying out adaptive weighted fusion on original multi-sensor data, inhibiting environmental noise and structural background interference, and separating and reconstructing an accurate three-dimensional morphology map of the target crack. According to the method, multi-source data information can be effectively fused to improve the accuracy of aircraft structure crack identification.

The invention discloses a data model dual-drive motor life prediction system and method. The system comprises an information acquisition module, a model fusion module, a model training module and a weight adjustment module. The information acquisition module is used for acquiring state data of different motors; the model fusion module is used for effectively fusing the data driving model and the physical information model; the model training module is used for training and optimizing the fused mechanism-data dual-drive model according to the motor state data provided by the information acquisition module; the weight adjusting module plays a key adjusting role in the whole model training process. The method not only depends on a data-driven model for prediction, but also combines a physical information model to make up for the problem that a pure data-driven method lacks interpretability. Multi-physical-field factors such as environmental stress, vibration impact, thermal management and an electromagnetic field are brought into modeling, so that the performance degradation of the motor is accurately described and evaluated, and the accuracy and physical interpretability of a prediction result are enhanced.

The invention relates to power transmission line unmanned aerial vehicle inspection, and discloses a power transmission line unmanned aerial vehicle inspection path dynamic planning system, which comprises a quantum high-precision positioning unit, an environment perception and electromagnetic field modeling unit, a dynamic path planning unit, an unmanned aerial vehicle flight control unit and a ground station task management unit. The quantum positioning unit fuses quantum inertial navigation, GNSS and quantum magnetometer data to improve the positioning precision under strong interference; the environment sensing unit obtains a three-dimensional environment and electromagnetic field distribution of the power transmission line; the path planning unit dynamically optimizes an inspection path based on positioning and environment information; the flight control unit performs accurate execution; and ground station management tasks and data analysis. The anti-interference positioning precision of the unmanned aerial vehicle is remarkably improved, accurate path planning and electromagnetic field avoidance are realized, the inspection risk is effectively reduced, and the efficiency, the safety and the adaptability are improved.

The invention discloses a system for testing an electromagnetic shielding coupler of a testing transformer based on intelligent sensing, and relates to the technical field of electrical equipment testing, and the system comprises a flexible distributed intelligent sensing array which is composed of a plurality of high-density miniature electromagnetic sensors and a temperature-vibration composite sensing unit, a non-uniform topological structure is embedded into a seam and an insulating interface area on the surface of the electromagnetic shielding coupler. According to the test system of the test transformer electromagnetic shielding coupler based on intelligent sensing, through dynamic electromagnetic field reconstruction of the flexible distributed intelligent sensing array and multi-band interference coupling modeling, the limitation of a traditional static test is broken through; and real-time capture and multi-dimensional decoupling of shielding effectiveness attenuation characteristics in a complex alternating electromagnetic environment are realized. Compared with a traditional method, the method has the advantages that the shielding effectiveness dynamic quantization error is reduced, and the engineering guidance value of test data is improved.

The invention relates to the technical field of unmanned aerial vehicle application, and discloses a multi-mode electromagnetic field distribution surveying and mapping unmanned aerial vehicle system and an application method thereof. The system comprises a dynamic adjustment module, a multi-band acquisition module, a hybrid positioning module, a three-dimensional modeling module and a multi-modal fusion module. The dynamic adjusting module adjusts the distance between the electromagnetic sensor and the rotor wing according to the rotor wing electromagnetic interference suppression rule; the multi-band acquisition module acquires and processes electromagnetic signals; the hybrid positioning module integrates TDOA and AOA algorithms to position the radiation source; the three-dimensional modeling module generates a three-dimensional electromagnetic field intensity distribution diagram; the multi-modal fusion module fuses the visible light image and the electromagnetic data. The system can also evaluate the risk of the radiation source and plan a flight path. The application method comprises the steps of distance adjustment, data acquisition and processing, radiation source positioning, model construction and the like. According to the method, rotor interference is effectively suppressed, the positioning precision is improved, multi-modal data fusion is realized, and the method has a wide application prospect in the fields of electric power inspection, urban electromagnetic environment evaluation and the like.

The invention discloses a dam termite cave positioning method based on transient electromagnetism carried by an unmanned aerial vehicle. The method comprises the following steps: constructing an unmanned aerial vehicle transient electromagnetic detection system; preprocessing the received secondary induction electromagnetic field signal, and obtaining a comprehensive electromagnetic signal according to the response difference of the multi-frequency signal; inputting the integrated electromagnetic signals into a pre-trained deep learning neural network model, identifying characteristic signals related to termite acupoints in the integrated electromagnetic signals, and outputting position coordinates of suspected termite acupoints; a dam surface thermal imaging image obtained by a thermal imaging module is combined for secondary verification, and termite cave position information is transmitted to a ground control terminal in real time through a communication module carried by the unmanned aerial vehicle. According to the invention, efficient, accurate and lossless positioning of the termite cave of the dam is realized, underground electromagnetic signals and surface heat distribution information of the dam are rapidly obtained, and accurate termite cave position coordinates are output.

The invention provides an electromagnetic field prediction method and device and electronic equipment, and relates to the technical field of electromagnetic field solving. The method comprises the following steps: acquiring historical electromagnetic original data in a field-line coupling scene, preprocessing the historical electromagnetic original data, inputting the preprocessed historical electromagnetic original data into an LSTM-PINN model, and outputting a physical field quantity mapping result; wherein the physical field quantity comprises an electric field component and a magnetic field component; setting a weighted loss function, and performing optimization training on the LSTM-PINN model based on a physical field quantity mapping result and an error of a real physical field quantity corresponding to historical electromagnetic original data to obtain a trained electromagnetic field prediction model; wherein the weighted loss function comprises a data loss function, a physical residual loss function, an initial condition loss function and a boundary condition loss function; and inputting real-time electromagnetic original data into the trained electromagnetic field prediction model to obtain a spatio-temporal distribution electromagnetic field prediction result. The method can effectively extract the spatial distribution features and the time sequence features at the same time, and is suitable for a complex field-line coupling problem.

The invention provides a keyword-based file information identification method and system, and the method comprises the steps: obtaining existing files, building a file database based on the existing files, carrying out the clustering of the existing files in the file database according to the obtained preset industry term data, and obtaining a first clustering result of keywords; the method comprises the following steps: acquiring a correlation score of an existing file and a query keyword based on a BM25 model, performing optimization clustering on a first clustering result of the keyword based on the correlation score, acquiring a second clustering result of the keyword, constructing a keyword semantic association magnetic field according to the second clustering result of the keyword in combination with an electromagnetic field simulation mode, and acquiring historical query data of a user. A personalized dynamic weight is established based on historical query data of the user, a third clustering result of the keywords is obtained according to the personalized dynamic weight and the keyword semantic association magnetic field, and a corresponding existing file is recognized and matched in the file database for the user based on the third clustering result of the keywords. Through the method, the accuracy of querying the matched document file by the user can be improved.

The invention relates to a charging pile gun state intelligent detection method and system, and the method comprises the steps: collecting a charging gun head electromagnetic signal, a gun handle temperature gradient and an interface contact surface mechanical strain signal in real time based on a multi-mode sensor array, constructing a space-time coupling data cube, separating the independent components of an electromagnetic field, a temperature field and a strain field, and obtaining a space-time coupling data cube; the multi-physical field coupling interference is eliminated; designing a dynamic cross compensation mechanism to correct mutual influence among sensor data; extracting multi-domain features and carrying out adversarial weight fusion to generate a comprehensive state representation vector; state scores are generated in combination with similarity matching of the dynamic reference library, and abnormal grade classification is achieved; according to the method, the problems of multi-field coupling interference separation, dynamic drift compensation and multi-dimensional feature joint modeling can be solved, the accuracy and real-time performance of poor contact of the charging gun, overheating early warning and mechanical deformation detection are improved, and a guarantee is provided for safe operation of charging facilities.

The invention relates to the technical field of simulation, and particularly discloses a real-time simulation method for detecting photoelectric tracking equipment, which comprises the following steps of: performing feature decoupling processing on photoelectric signals through a dual-channel adaptive neural network architecture, and constructing an equipment mathematical model by adopting a dynamic gating fusion mechanism based on a processing result; the method comprises the following steps: establishing a multi-physics field coupling simulation environment based on a heterogeneous computing architecture, introducing an equipment mathematical model, performing three-field co-evolution through light transmission modeling, electromagnetic field distribution calculation and target motion prediction, and generating a dynamic test scene containing space-time relevance; according to the method, a mode of combining mixed feature analysis and fuzzy reasoning is adopted, multi-dimensional performance indexes are extracted from simulation data, and multi-target dynamic optimization is carried out through a strategy of combining a quantum evolution algorithm and swarm intelligence optimization; by means of a digital twin platform and a hardware-in-loop interface, real-time verification and closed-loop optimization are achieved, and the response speed and tracking precision of photoelectric tracking equipment in a complex environment are greatly improved.

The invention discloses a cable sheath ring current fault positioning in-loop simulation method and system based on LABVIEW. The method comprises the following steps: collecting ring current data of cable sheath monitoring points in real time under the control of LABVIEW, and carrying out digital display and graphical display; decomposing circulation data to obtain a wavelet coefficient and calculating features, and inputting a classification model to obtain a fault type when the features are abnormal; calculating a compensation coefficient considering the influence of the electromagnetic field, and calculating the position of a fault point in combination with a double-end traveling wave method; the operation model switches a typical working condition simulation mode, prediction of a Bayesian reasoning correction model is carried out, and the full-life-cycle operation state of the cable is simulated; and performing fault early warning through the LSTM model and risk assessment. The method can effectively improve the cable operation and maintenance efficiency and reliability, and is widely applied to cable fault detection and guarantee of safe and stable operation of a power system.

The invention provides an intelligent eddy current nondestructive testing method and system based on a flexible GMR sensor array, and relates to the technical field of nondestructive testing. According to the invention, a GMR sensor array and a micro excitation coil array are integrated on a flexible substrate, and synchronous acquisition under multi-frequency and multi-phase excitation is realized by establishing a probe-workpiece unified space coordinate system and a time synchronization reference; performing temperature drift compensation, attitude correction and gap normalization processing on the original response tensor to generate a corrected response tensor; the intelligent inversion model based on the prior constraint of the electromagnetic field jointly identifies the conductivity, the thickness and the crack parameters, and outputs a defect parameter map and a confidence map; and a detection report containing the position, the size, the depth and the confidence coefficient is generated through spatial clustering and connectivity analysis, so that high-sensitivity and high-reliability nondestructive detection under a complex curved surface structure is realized.

The invention provides a self-adaptive efficient simulation method and system for electric propulsion plasma oscillation, and relates to the technical field of electric propulsion plasma oscillation simulation. According to the method, a high-precision electric propulsion plasma numerical simulation model is adopted to ensure the precision of a simulation result; according to the method, the calculation tasks of the simulation model are decomposed through various adjustment parameters, that is, all the calculation tasks are completed in a parallel calculation mode, and therefore the simulation efficiency can be effectively improved. Moreover, when the simulation model is subjected to simulation solving, the electromagnetic field solving model is solved by adopting a multi-grid method, and the simulation calculation efficiency can be further improved based on the solving mode. Besides, the target neural network model is utilized to process the simulation result so as to update all the adjustment parameters in the process, so that a plurality of adjustment parameters used in the simulation process are continuously and adaptively optimized, and the technical effect of considering the simulation efficiency and precision of the electric propulsion plasma oscillation simulation model is achieved.

The invention discloses a transistor high-power electromagnetic heat model optimization system based on deep learning, and relates to the technical field of electromagnetic heat. Comprising an input module, a deep learning module, a global optimization module, an online adaptive module and a real-time simulation module. The input module obtains various key parameters and constructs a high-dimensional input space; the deep learning module constructs a deep learning model by embedding a physical constraint and uncertainty quantization mechanism; the global optimization module is used for carrying out global search on design parameters, rapidly evaluating a target function by utilizing an agent model, and searching a Pareto optimal solution in a design parameter space; the online adaptive module is used for drift detection and updating; the real-time simulation module simulates an electromagnetic field and a thermal field in real time, and data exchange ensures timely synchronization of boundary data through dynamic scheduling and load balancing; all the modules cooperate with one another through data and feedback, and a complete, closed-loop and continuously self-adaptive updating optimization system is achieved.

The invention discloses an embankment hidden danger detection and early warning method and system based on electric field and electromagnetic field coupling, and the method comprises the following steps: obtaining and processing the resistivity and dielectric constant of an embankment dam body, constructing a joint inversion objective function based on a processing result, and carrying out the detection and early warning of the embankment hidden danger. A joint inversion model is established, a minimum joint inversion objective function is used for solving, a multi-physics field joint inversion result is obtained and used for delineating an abnormal area, a time-shifting resistivity monitoring network is arranged in the area for detection, the seepage velocity is obtained, soil mass mechanical parameters are defined, and the seepage velocity is calculated. And constructing an embankment hidden danger numerical model, using seepage velocities as boundary condition input, simulating embankment dam body stability safety coefficients under different seepage velocities, setting an early warning threshold value, and giving an alarm when the embankment dam body stability safety coefficients reach the early warning threshold value. Through coupling analysis of the earth electric field, the seepage velocity and the like, data multiplicity is effectively eliminated, the defect resolution is remarkably improved, and the misjudgment risk is greatly reduced.

The invention provides an electromagnetic compatibility test method and system for PCB design, a PCB comprises a schematic circuit diagram and a structural model, and the method comprises the following steps: extracting high-frequency signal characteristics in the schematic circuit diagram to obtain an electromagnetic simulation parameter set; performing multi-physical field coupling modeling according to the electromagnetic simulation parameter set and the structure model to obtain an electromagnetic field-circuit model; performing frequency-time domain hybrid excitation loading on the electromagnetic field-circuit model to obtain an electromagnetic noise distribution diagram; performing gradient descent optimization on layout parameters of the structure model according to the electromagnetic noise distribution diagram to obtain an anti-interference layout scheme; and performing multi-working-condition Monte Carlo simulation and residual error calibration on the anti-interference layout scheme to generate a correction guidance library.

The invention provides a 5G communication method and system based on environmental adaptation, and the method comprises the steps: fusing electromagnetic field intensity distribution, a terminal density thermodynamic diagram and obstacle reflection data through distributed sensing nodes, and generating a dynamic environment sensing matrix. Based on the matrix, establishing a beam pointing model of the motion trail of the user equipment cluster, dynamically adjusting the radiation direction of a beam main lobe, and creating a null region. And in combination with real-time channel multipath phase characteristics, non-uniform interval subcarrier distribution is reconstructed, and multipath phase compensation is carried out. A main lobe radiation direction and a subcarrier distribution mode are integrated into a physical layer structure, and the spatial multiplexing density of a time-frequency resource block is dynamically adjusted according to a service priority. And iteratively optimizing a collaborative matching threshold value of each parameter through closed-loop interaction of a forward channel response feature and a reverse control instruction. According to the invention, the anti-interference capability and the spectrum efficiency of the communication system are improved.

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 a transformer substation positioning and navigation method and system integrating positioning and visual auxiliary positioning. The method comprises the following steps: establishing a background electromagnetic field distribution baseline graph associated with a three-dimensional reference map; electromagnetic field data of the transformer substation in an emergency response mode is collected through the unmanned aerial vehicle, and the abnormal field intensity of a space electromagnetic field and a fault source pointing vector pointing to a fault source are calculated; constructing a risk adaptive elliptical forbidden zone; calculating a passage cost index Cto of the unmanned aerial vehicle passing through each three-dimensional grid in the three-dimensional reference map by using the fault source pointing vector and the risk adaptive elliptical forbidden zone; and searching a path which is from the current position of the unmanned aerial vehicle to a preset target point, bypasses the risk adaptive elliptical forbidden zone, faces the fault source and has the lowest total passing cost index Cto by adopting a preset path search algorithm. According to the method, the risk self-adaptive elliptical forbidden zone is constructed and is used as the three-dimensional grid forbidden assignment processing, so that the dynamic global path avoidance of the sudden dangerous zone is realized.

The invention relates to the field of electric power material warehouse management and control, in particular to an electric power material digital intelligent professional warehouse management and control method, which comprises the following steps: acquiring electromagnetic spectrum data, identifying a central frequency point energy distribution diagram and an electromagnetic interference intensity level, constructing a three-dimensional electromagnetic field intensity distribution model of a professional warehouse, and dynamically adjusting the working mode of an RFID reader-writer; the method comprises the following steps: deploying a multi-modal check node in a storage area of a professional warehouse, and generating a composite check result through an infrared contour matching method and a UWB coordinate verification method when the confidence coefficient of electric power material data read by an RFID reader-writer is lower than a preset confidence coefficient threshold value; updating an electric power material inventory database according to a composite verification result, and performing electric power material inventory state analysis in real time through an edge computing node; the problems that inventory data distortion and material positioning deviation are caused by reduction of the accuracy rate of RFID in a strong electromagnetic environment, and inventory accuracy management of an electric power material warehouse is seriously restricted are solved.

The invention belongs to the technical field of geophysical monitoring, and relates to an electromagnetic interference detection method for earthquake monitoring, which comprises the following steps: deploying a multi-dimensional electromagnetic field sensing unit and an earthquake signal acquisition unit and realizing high-precision synchronization; synchronously acquiring multi-dimensional electromagnetic field and seismic physical signal data; performing multi-feature and noise feature extraction on the two; inputting the features into a pre-trained machine learning / deep learning model for identification, and outputting information such as interference type, intensity and azimuth angle; and carrying out influence evaluation and quality marking on the seismic data according to the output, and selectively inhibiting or compensating. Through the above scheme, multi-dimensional perception and characterization, high-precision synchronization and correlation analysis, intelligent identification and spatial positioning are realized, and the reliability and accuracy of earthquake monitoring data are significantly improved.

This invention provides an electromagnetic field detector, a system comprising the electromagnetic field detector, and a method of operating an electromagnetic field detector, the electromagnetic field detector comprising a first optical signal interface configured to receive, from one or more remote optical sources, a first optical signal; an electromagnetic field transmitter configured to transmit a local oscillator electromagnetic field generated from the first optical signal, the electromagnetic field transmitter comprising: a photocurrent generator configured to generate a photocurrent from the first optical signal; and an antenna interface configured to supply the photocurrent to an antenna to transmit the local oscillator electromagnetic field; a second optical signal interface configured to receive, from the one or more remote optical sources, a probe optical signal and a coupling optical signal; and a transmission medium configured to be excited by the probe optical signal and further excited by the coupling optical signal, wherein the probe optical

The invention provides a fractured rock mass surrounding rock grouting quality evaluation method, and relates to the technical field of geotechnical engineering.The method comprises the following steps that permeability test data and acoustic velocity test data of fracture connectivity and mechanical states of a target surrounding rock area are obtained before grouting, and a characterization parameter data set of fractures before grouting is formed; synchronously acquiring three-dimensional point cloud data to calculate the volume of a fracture cavity; in the grouting process, electromagnetic field intensity data is collected to calculate the grouting filling rate, resistivity time sequence data is collected to calculate the cementation uniformity index, strain time sequence data is collected to calculate the strain gradient, and a grouting integrity index is formed through multi-feature fusion; after grouting, permeability and sound wave velocity data are obtained again, and the fracture characterization performance improvement rate is calculated; acquiring penetration test data to calculate a stone body strength parameter; and performing multivariate fusion on the grouting integrity index, the fracture characterization performance improvement rate and the stone body strength parameter to calculate a comprehensive quality score, and comparing the comprehensive quality score with a preset threshold value to perform grading evaluation.

The invention relates to the technical field of alloy coatings, and discloses a laser cladding high-entropy alloy coating and a preparation method thereof.The laser cladding high-entropy alloy coating is prepared from, by mass, 25%-45% of Fe, 15%-25% of Cr, 10%-20% of Ni, 5%-15% of Mn, 3%-10% of Al, 0%-5% of Ti, 1%-5% of a nanometer reinforcing phase and 0.1%-0.5% of a flow promoter. Lorentz force generated by an alternating electromagnetic field drives melt convection, so that the diffusion coefficient of segregation-prone elements such as Cr and Ni is increased, the ultrasonic cavitation effect is matched to crush dendritic crystals and promote dispersion of nanoparticles, the segregation index of the elements is reduced, a uniform nanocrystalline-amorphous composite structure is formed through the synergistic effect, and uniform distribution of elements in a molten pool is achieved.

The invention relates to the technical field of transformer simulation, in particular to a simulation system and method for a temperature rise field of a dry-type transformer. The method comprises the following steps: acquiring geometric parameters of an iron core lamination of the dry-type transformer to be simulated, spatial arrangement information of a winding and a positioning relation of an insulating component to form structural design data; the method comprises the following steps: constructing three-dimensional geometric modeling data based on structural design data, importing the three-dimensional geometric modeling data into a finite element electromagnetic simulation platform, setting a power-on condition of an excitation winding, and applying rated current or voltage, so as to obtain local magnetic flux density distribution data at each iron core lamination position in a whole operation period. According to the method, on the basis of three-dimensional structure data, three physical processes of an electromagnetic field, a thermal field and a fluid field are fused, a high-precision local heat source model and a dynamic temperature rise prediction model are constructed, and geometry-material-boundary all-parameter modeling is achieved from the whole structure of an iron core lamination, a winding and an insulation assembly.

The invention belongs to the technical field of medical imaging and digital twinning, and discloses a thoracic cavity whole organ system level lung four-dimensional EIT detection digital motif and a library building method, and the method comprises the following steps: S1) segmenting multiple organs such as double lungs, heart, sternum, rib and thoracic vertebra central axis skeleton, main bronchus and esophagus based on an individual CT image, and building a three-dimensional geometric model integrated with an EIT electrode array; s2) simulating breathing dynamic deformation by using a solid mechanical model; s3) establishing a coupling relationship between deformation and conductivity, and generating dynamic three-dimensional conductivity distribution; s4) solving an electromagnetic field positive problem, and generating a virtual EIT voltage database synchronous with respiration; the invention also covers pathological model integration and data enhancement strategies. According to the method, a high-fidelity, large-scale and diversified EIT virtual data set can be generated, core data support is provided for training and verifying an AI intelligent reconstruction algorithm, and a model foundation is laid for developing a lung function dynamic digital twinning system.