7183 results about "Electromagnetics fields" patented technology

The invention provides a circuit board fault diagnosis method and system based on artificial intelligence, and relates to the technical field of circuit board fault diagnosis, and the method comprises the steps: constructing a three-dimensional electromagnetic field simulation model of a circuit board, setting a plurality of virtual sensing probes in the three-dimensional electromagnetic field simulation model, and generating an electromagnetic field distortion distribution diagram; dividing a fault sensitive area of the circuit board based on the electromagnetic field distortion distribution diagram, outputting a performance degradation rate of each functional area of the circuit board, and generating a fault risk assessment matrix according to the performance degradation rate; performing function reconstruction on the circuit board according to the fault risk assessment matrix, establishing a dynamic fault-tolerant mechanism of the circuit board, generating a task load distribution strategy based on the dynamic fault-tolerant mechanism, and deploying the task load distribution strategy to a field programmable gate array of the circuit board. And self-repairing the circuit board by adjusting the logic structure of the field programmable gate array, verifying the repairing effect and outputting a diagnosis report.

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.

Pulsed electromagnetic field systems include planar microcoil arrays integrated into clothing. The planar microcoil arrays are connected to a neuromodulation controller and configured to generate an electrical current and transmit that electrical current, in accordance with a particular stimulation protocol, to each of the planar microcoil arrays.

The invention provides an electromagnetic-assisted nickel-based alloy laser melting deposition crack inhibition method and system, relates to the technical field of automatic control, constructs an intelligent control system, carries out deep fusion and real-time prediction on multi-source heterogeneous sensing data, generates a prediction result, sets a reward function and an action-value network, and improves the performance of the nickel-based alloy laser melting deposition crack inhibition system. Solving to obtain an optimization control strategy and analyzing and outputting the optimization control strategy; and constructing a three-dimensional electromagnetic field distribution matrix. In combination with real-time feedback of the shape of the molten pool, the molten pool is stimulated to flow directionally and oscillate non-linearly according to the resonance effect, oscillation parameters are obtained, thermodynamic behaviors corresponding to the molten pool are predicted according to the oscillation parameters, and a thermodynamic prediction result is fed back to the central control unit; the method comprises the following steps: detecting the surface appearance of a part, extracting defect characteristic parameter vectors, inverting defect influence factors, generating a dynamic regulation and control curve, dispersing the dynamic regulation and control curve into multi-dimensional control instruction vectors, updating a preset regulation and control model, outputting optimized regulation and control model parameters, and carrying out crack suppression operation again.

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 provides an electromagnetic field composite powder feeding type plasma arc additive manufacturing formability regulation and control method and system, and relates to the technical field of plasma arc additive manufacturing. The flowing direction and speed of liquid metal in a molten pool in the deposition process are regulated and controlled through the target composite electromagnetic field, and the morphology and the internal organization structure of a deposition layer are controlled; in the process of regulating and controlling the liquid metal in the molten pool, process parameters and molten pool dynamic image data in the deposition process are collected in real time, and a pre-trained state recognition model is used for conducting self-adaptive adjustment on the process parameters of a subsequent deposition layer; and after deposition of each layer is completed, a laser scanning system is adopted for measuring the actual geometric size and surface appearance of the deposition layer, deposition manufacturing of the next layer is executed based on the optimized composite electromagnetic field control parameters, the corrected layered slicing data and the process path, and the execution is executed circularly till manufacturing of the whole workpiece is completed.

An inductive sensor system may comprise an upper rotor comprising an upper target having a first metallic pattern; a lower rotor comprising a lower target having a second metallic pattern; and a stationary circuit board positioned between the upper rotor and the lower rotor. The circuit board comprises one or more transmitter coil sets configured to generate electromagnetic field, and one or more receiver coil sets for sensing relative angular displacement movement between the upper rotor and the lower rotor. The one or more transmitter coil sets and the one or more receiver coil sets are circularly wound.

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 a high-precision multi-channel phased array radio measurement calibration method and a high-precision multi-channel phased array radio measurement calibration system. The method comprises the following steps: carrying out electromagnetic characteristic modeling on N array element channels and an antenna housing of the multi-channel phased-array antenna to obtain a channel measurement model; carrying out electromagnetic field numerical calculation on the multi-channel phased-array antenna to obtain an initial error data matrix; mapping the initial error data matrix to a two-dimensional weight matrix, and performing optimal matching solution on the two-dimensional weight matrix to obtain a theoretical calibration coefficient matrix; connecting the standard gain antenna and the multi-channel phased-array antenna by adopting a vector network analyzer, and performing far-field scanning measurement on the multi-channel phased-array antenna to obtain actually measured amplitude-phase characteristic data; and performing weighted least square iterative calculation on the actually measured amplitude-phase characteristic data and the theoretical calibration coefficient matrix to obtain a target calibration compensation coefficient. According to the invention, accurate measurement of the amplitude-phase characteristics of the multi-channel phased-array antenna is realized, and the stability of the calibration process is improved.

The invention discloses a booster station monitoring operation and maintenance system, and relates to the technical field of data management. A plurality of heterogeneous intelligent sensors are deployed in a booster station to monitor the operation state of equipment in real time, an electromagnetic field sensor is utilized to sense the electromagnetic interference intensity, and when abnormal high-frequency pulses are detected, a data anomaly detection mode is triggered to detect the abnormal high-frequency pulses; calculating an error compensation value according to the abnormal degree, correcting abnormal data, ensuring the accuracy of the data, performing equipment state evaluation according to the recovered data, and if potential safety hazards are found, sending intelligent early warning to operation and maintenance personnel and providing suggestions for adjusting monitoring strategies or optimizing shielding measures; according to the invention, the anti-interference capability and accuracy of booster station monitoring data are effectively improved, the risk of operation and maintenance misjudgment caused by electromagnetic interference is reduced, the reliability of intelligent monitoring in an ultrahigh-voltage power transmission scene is enhanced, and a powerful guarantee is provided for safe and stable operation of a power system.

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 an unmanned aerial vehicle multi-mode mine inspection method and system, a medium and a program product, and the method comprises the steps: dividing an inspection target into a short-range object and a long-range object based on a preset inspection target classification list; constructing a three-dimensional grid inspection path according to the position information of the short-range object and the remote object, and setting a plurality of standby inspection entrance points in a detection area of the short-range object; acquiring real-time environment parameters, wherein the real-time environment parameters comprise illumination intensity, atmospheric visibility, electromagnetic field intensity and wind speed and wind direction; calculating the reachability score of each standby inspection entrance point based on the influence degree score of the real-time environment parameters on the unmanned aerial vehicle, and determining the standby inspection entrance point with the highest reachability score as the current inspection entrance point; and generating an inspection path according to the current inspection entrance point, and controlling the unmanned aerial vehicle to inspect according to the inspection path. According to the method, the integrity of the inspection data is improved, the accuracy of the safety evaluation data obtained based on the inspection data is improved, and the safety of a mine is further improved.

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 provides a detection method and system for an insulation detection function. Wherein in the operation state of the to-be-detected electrical equipment, the temperature change of the surface of the to-be-detected electrical equipment is monitored in real time through a non-contact sensor, and a dynamic thermogram is formed; according to a temperature fluctuation mode of a preset area in the dynamic thermogram, in combination with an environment temperature compensation algorithm, identifying a potential insulation defect area, and generating a preliminary insulation defect report; for the insulation defect area marked in the preliminary insulation defect report, simulating electromagnetic field distribution conditions of the insulation defect area under different working conditions by adopting an electromagnetic field analysis technology, evaluating the aging degree and damage risk of the insulation material, and obtaining an evaluation result; and integrating the preliminary insulation defect report and the evaluation result, calculating the probability that the insulation defect area develops into an actual fault through a fault prediction model, and outputting a final insulation performance detection report. According to the technical scheme provided by the invention, the operation efficiency and safety of the equipment are improved.

The invention discloses a self-adaptive impedance matching method for a high-frequency signal transmission connector of a new energy vehicle, and relates to the technical field of signal processing, and the method comprises the steps: 1, obtaining the physical parameters of the high-frequency signal transmission connector of the new energy vehicle; calculating an electromagnetic field feature vector, and calculating a transmission line distribution vector of the high-frequency signal transmission connector; 2, calculating a propagation constant of a high-frequency signal transmission connector of the new energy vehicle; calculating the characteristic impedance of a high-frequency signal transmission connector of the new energy vehicle; 3, calculating a reflection coefficient; calculating an impedance error; step 4, calculating a compensation parameter vector, and generating a control signal by using an adaptive control theory according to the compensation parameter vector; and calculating the impedance matching degree according to the control signal. According to the invention, impedance change in a complex environment can be accurately dealt with, signal reflection and energy loss are significantly reduced, and transmission efficiency and signal integrity are improved.

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 belongs to the technical field of thermal circuit model construction, and particularly relates to a high-voltage power cable intermediate connection thermal circuit fault modeling analysis method and device, and the method comprises the steps: building a high-voltage power cable intermediate connection thermal circuit fault circuit model through analyzing a cable intermediate connection temperature inversion principle; the method comprises the following steps: establishing a geometric model for multi-physics field analysis of the intermediate connection of the high-voltage power cable by utilizing Comsol finite element simulation software, setting material parameters of each component, and setting field domain parameters; an electromagnetic field module is added, boundary conditions of electromagnetic field analysis are set, and a cable intermediate connection electromagnetic field simulation model is obtained; adding a solid heat transfer module to obtain a solid temperature field simulation model; obtaining an electromagnetic-thermal coupling model, and solving to obtain the temperature, current and loss of the cable middle connection wire core and the outer surface in different insulation states. According to the method, the cable intermediate connection fault problem can be found and predicted, and the reliability and the safety of the power cable are improved.

The present disclosure belongs to the field of geophysical exploration, and discloses a method, a system, a medium, a device and a terminal for predicting the probing depth of transient electromagnetic. Based on the existing published resistivity model database, the transient electromagnetic field in layered medium is calculated, and the probing depth is calculated based on Jacobian matrix to establish a training data set. The simulated induced electromotive force is used as the input of the neural network, and the calculated probing depth is used as the output of the network. A rapid mapping between observation data and probing depth is established by using residual neural network.

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 integrated circuit packaging quality evaluation method and system based on a nondestructive testing technology, and relates to the technical field of integrated circuits, and the method comprises the steps: obtaining a three-dimensional fluorescence response signal of a packaging structure through a two-photon excitation microscopic system, and building a stress distribution characteristic graph and a stress gradient grading graph through the analysis of the spatial distribution of the fluorescence signal; a quantum state nitrogen vacancy probe array is arranged in the stress abnormal area, electromagnetic field response signals of the quantum state nitrogen vacancy probe array under the stress effect are collected, and accurate mapping of a stress field and an electromagnetic field of the packaging structure is achieved; based on the obtained multi-physical field data, establishing a thermal electromagnetic coupling equation set, and calculating an interaction relationship among the physical fields; by analyzing evolution characteristics of each detection area under the multi-field coupling effect, a stability evaluation system including a mechanical failure risk and an electromagnetic failure risk is established, and accurate evaluation of the quality grade of the packaging structure is realized.

The invention relates to the field of data signal processing, in particular to a network algorithm cable terminal discharge early warning method, device and system based on dual-channel waveform identification. The method comprises the following steps of: firstly, acquiring a periodic ultrasonic signal and an ultrahigh frequency electromagnetic field signal generated by discharging of a cable terminal, converting the two signals into a corresponding time-frequency diagram by utilizing short-time Fourier transform, and performing normalization processing to serve as input of a subsequent network; a dual-channel high-order feature extraction network formed by cascading a ConvNeXt backbone network and a convolution block attention module is constructed, and is used for extracting time-frequency diagram detail fault features of ultrasonic signals and high-frequency electromagnetic field signals. And finally, by constructing an adaptive feature fusion network, fusing the fault features of the two channels, and obtaining cross-channel fault joint features by using an adaptive weight coefficient vector, thereby outputting a diagnosis result, and realizing accurate evaluation of a defect state of an adjacent cable terminal.

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 relates to the technical field of electromagnetic compatibility, in particular to a power application environment electromagnetic interference analysis and evaluation method and system, and the method comprises the following steps: recording the position coordinates of a plurality of power devices based on power grid operation data, collecting the current and voltage data of the operation of the devices, and measuring the electromagnetic field intensity data of a plurality of positions of a power grid; an electromagnetic environment data set is generated. According to the method, the operation data and the electromagnetic field intensity of the power equipment are recorded, the understanding ability of the electromagnetic environment is enhanced, the shielding effect of various materials is accurately evaluated by combining the analysis of the shielding materials, the design and operation of the power equipment are optimized, and the electromagnetic sensitivity of the equipment is evaluated. According to the method, the dynamic distribution of the electromagnetic field is simulated and predicted, the electromagnetic field mode causing a fault is identified, and risk equipment predicted through real-time monitoring and data analysis is combined, so that the stability and safety of a power system are improved, the anti-interference capability is enhanced, and the operation efficiency and function safety of power facilities are improved.

The invention discloses a GIS field-electricity fusion real-time state sensing and early warning system and method. The system comprises a signal synchronous acquisition and measurement embedded device and an industrial personal computer, and a simulator, a position searcher and an early warning device are deployed in the industrial personal computer; when the embedded device monitors that the electromagnetic field signal in the GIS contains the partial discharge signal according to the strong correlation characteristics, obtaining a full time domain oscillogram containing a time domain oscillogram and a frequency domain oscillogram of the partial discharge signal; the simulator performs coarse positioning on the partial discharge source based on the full time domain oscillogram of GIS partial discharge, and performs simulation enhancement calculation by taking a coarse positioning result as an initial injection point to obtain simulation enhancement data of the partial discharge source; the position searcher carries out iterative search on the actually measured discharge intensity obtained through calculation according to the full-time-domain oscillogram and the simulation enhancement result, and the actual discharge position of the partial discharge source is obtained; the early warning device carries out early warning based on the time domain full waveform and early warning information including the actual discharge position of the partial discharge source.

The invention discloses a switch cabinet quality comprehensive evaluation system and method based on the Internet of Things technology, and particularly relates to the technical field of switch cabinets. Electromagnetic interference detection equipment is installed, the electromagnetic field intensity around a switch cabinet and the operation state of the equipment are monitored in real time, and electromagnetic field data and state data in different time periods are obtained; carrying out weighted calculation on the electromagnetic interference index to generate an overall electromagnetic interference index; the fuzzy logic is utilized to comprehensively analyze the electromagnetic interference index and the real-time state data of the switch cabinet, a health assessment report is generated, the health condition of the equipment is accurately displayed, the operation monitoring and maintenance optimization capability of the switch cabinet is effectively improved, potential faults can be predicted, and misjudgment can be reduced.

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 discloses a method and a device for calculating an electromagnetic-heat flow field under a turn-to-turn short circuit fault of a converter transformer. The method comprises the following steps: establishing a converter transformer multi-physical field numerical calculation theoretical model based on circuit-electromagnetic-heat flow coupling; based on the multi-physical field numerical calculation theoretical model, establishing a converter transformer electromagnetic-heat flow field model under the turn-to-turn short circuit fault; setting turn-to-turn short circuit faults at different positions in the electromagnetic-heat flow field model of the converter transformer; and performing winding current waveform, voltage waveform and electromagnetic field analysis and heat flow field analysis of the converter transformer under the set turn-to-turn short circuit fault.