11278 results about "High voltage" patented technology

The invention provides a device for generating shock waves. The device may comprise an elongated tube and a conductive sheath circumferentially mounted around the elongated tube. The device may further comprise first and second insulated wires extending along the outer surface of the elongated tube. A portion of the first insulated wire is removed to form a first inner electrode, which is adjacent to a first side edge of the conductive sheath. A portion of the second insulated wire is removed to form a second inner electrode, which is adjacent to a second side edge of the conductive sheath. Responsive to a high voltage being applied across the first inner electrode and the second inner electrode, a first shock wave is created across the first side edge and the first inner electrode, and a second shock wave is created across the second side edge and the second inner electrode.

The invention relates to the technical field of circuit breakers, in particular to a circuit breaker fault diagnosis method and system for switching an alternating current filter in an extra-high voltage converter station, and the method comprises the following steps: S1, synchronously collecting multiple parameters: synchronously collecting vibration acceleration signals, opening and closing coil current waveforms, arc light intensity and environment temperature and humidity parameters; s2, time sequence feature extraction: performing time-frequency domain decomposition on the vibration acceleration signal to obtain a mechanical action time sequence spectrum; s3, operation mode classification: determining the operation mode of the circuit breaker; s4, three-dimensional fault matrix construction: generating a three-dimensional fault matrix including spatial distribution characteristics; s5, dynamic threshold analysis: generating a diagnosis threshold interval dynamically adjusted along with the environmental parameters; and S6, comprehensive diagnosis output: outputting a mechanical jam grade, a contact ablation degree and an insulation deterioration early warning signal. According to the invention, the mechanical, electromagnetic and insulation characteristics of the circuit breaker can be reflected more comprehensively, and reliable guarantee is provided for safe and stable operation of a high-voltage power grid.

The invention discloses a pre-twisted damper fatigue life prediction method for an extra-high voltage ground wire, and particularly relates to the technical field of power transmission line vibration prevention. Collecting multi-source vibration and environment data, and constructing a vibration characteristic time sequence; amplitude, frequency and strain energy are extracted based on the multi-frequency vibration response, and a multi-frequency collaborative vibration model is established; obtaining a damper structure and material parameters, establishing a finite element model, coupling the finite element model with a vibration model, and simulating local stress response; a Rainflow counting method and a Miner damage criterion are adopted to construct a fatigue damage factor distribution matrix; predicting the residual fatigue life of the damper based on the damage evolution trend, and evaluating the replacement opportunity; according to the method, accurate fatigue life prediction and optimal replacement strategy recommendation of the pre-twisted damper under complex working conditions can be realized, and the method has high precision, high adaptability and engineering practicability.

Systems and apparatus are provided for a high-power microwave sensor using an unmanned aerial vehicle. The unmanned aerial vehicle may include a central body, at least one electric motor, and a barometric pressure feedthrough. The central body may include a first enclosure housing a plurality of low voltage components, a voltage feedthrough connector, and a second enclosure housing a plurality of high voltage components. The low voltage components may include a first signal processing system, a first radio transceiver, a flight controller, a second signal processing system, a second radio transceiver, and a navigation system. The high voltage components may include a plurality of electronic speed controllers, a power distribution module, an input power interface, and a plurality of high power filters. The components of each enclosure may be segregated such that the high voltage components do not create electromagnetic interference with the low voltage components.

The invention relates to the field of temperature monitoring, and discloses a high-voltage passive induction temperature monitoring system, which comprises a plurality of temperature sensors, the plurality of temperature sensors are arranged in different cabinets and channels in a machine room; a control unit; the control unit is used for sending a detection instruction to each temperature sensor and receiving a feedback temperature signal; the control unit generates a temperature change curve of each monitoring point according to the received temperature signals; the control unit constructs a three-dimensional temperature distribution model of the whole machine room based on the temperature change curve of each monitoring point, identifies a potential hot spot area based on the three-dimensional temperature distribution model and predicts the temperature change trend of the potential hot spot area; a refrigeration unit; the refrigeration unit is used for adjusting the temperature of the located area; the refrigeration unit is communicated with the control unit; wherein the control unit adjusts the power of each refrigeration unit based on the identified potential hot spot areas.

The invention discloses a vacuum circuit breaker state online monitoring method and system based on digital twinning, and relates to the field of intelligent operation and maintenance of high-voltage power equipment. According to the method, various sensors are arranged at key parts of the vacuum circuit breaker, breaking current, shielding case potential and vibration signals are collected in real time, and a digital twinborn model is constructed by combining multi-source data preprocessing, three-dimensional modeling, behavior rule definition and fault simulation analysis; and on-line identification and trend prediction of electrical wear, vacuum degree deterioration and mechanical abnormity are realized. The system has the functions of real-time monitoring, three-dimensional visualization, model self-learning and intelligent early warning, can be widely applied to intelligent monitoring and state evaluation of circuit breaker equipment in a power system, and remarkably improves the operation safety and operation and maintenance efficiency of the equipment.

The invention relates to an extra-high voltage converter transformer OLTC fault diagnosis method fusing multi-feature information and RIME-CNN-BiLSTM-SAM, and belongs to the technical field of intelligent monitoring of power systems. The method comprises the following steps: firstly, constructing a vibration signal fault data set based on an OLTC mechanical fault simulation experiment; secondly, decomposing an OLTC vibration signal into a plurality of intrinsic mode components by adopting REMD, and preferably selecting components containing rich fault feature information based on a correlation coefficient; then, the multi-scale permutation entropy of IMFs is calculated, time / frequency statistical analysis and the multi-scale permutation entropy are combined, OLTC multi-dimensional vibration characteristic parameters are integrally and locally concerned, and principal component analysis is introduced to carry out characteristic fusion and dimension reduction of OLTC vibration information; and finally, optimizing the hyper-parameters of the CNN-BiLSTM-SAM fault diagnosis model by using the RIME, and realizing the construction of the converter transformer OLTC intelligent fault diagnosis model. The method has a remarkable effect in the aspect of extracting OLTC fault feature information, the fault type recognition rate is superior to that of an existing method, and the effectiveness of the method in converter transformer OLTC fault diagnosis is verified.

A refuse vehicle includes a cab, a refuse compartment, a chassis, a high voltage power distribution unit (HVPDU) including a battery, a plurality of cables and a manual service disconnect. The manual service disconnect is accessed via a through hole of a wheel well of the refuse vehicle. The refuse vehicle further includes a platform removably coupled to the chassis and the HVPDU and configured to enclose the high voltage power distribution unit.

The invention discloses a high-temperature-resistant, high-voltage-resistant and anti-breakdown capacitor base film and a preparation method thereof. The high-temperature-resistant, high-voltage-resistant and anti-breakdown capacitor base film is prepared from the following raw materials in parts by weight: 100 parts of polypropylene; 17 to 36 parts of polyvinylidene fluoride; 3-12 parts of enhanced and improved talcum powder; 1-6.5 parts of modified barium titanate; 1-6 parts of a cross-linking agent; 2-10 parts of a compatilizer; and 0.05-2 parts of an initiator. The capacitor base film is high in mechanical strength, and has excellent high temperature resistance, thermo-oxidative aging resistance, high voltage resistance and anti-breakdown performance; the enhanced and improved talcum powder is constructed by taking expanded layer modified talc as a carrier and titanium dioxide-carbon dot composite particles as a loading component and grafting and coating the organic matter, so that the defects of the talcum powder can be overcome, and the improvement effect of the talcum powder on heat resistance, high-voltage resistance and breakdown resistance can be fully exerted; meanwhile, the system can be endowed with excellent thermo-oxidative aging resistance.

The invention relates to the technical field of image processing, in particular to a high-voltage electrical equipment surface defect identification method based on image processing. The method comprises the following steps: analyzing the gradient of pixel points in a to-be-analyzed image of a to-be-detected area on the surface of the high-voltage electrical equipment to obtain the weight of each pixel point; weighting the gray value of each pixel point in the to-be-analyzed image subjected to Laplacian filtering by using the weight of each pixel point of the to-be-analyzed image to obtain a first feature map; calculating a local standard deviation of each pixel point in the to-be-analyzed image so as to obtain a first parameter and a second parameter; constructing two Gaussian kernels based on the first parameter and the second parameter to filter the to-be-analyzed image to obtain a second feature map; fusing the first feature map and the second feature map of the to-be-analyzed image to obtain a defect saliency map of the to-be-analyzed image; and recognizing a surface defect area of the high-voltage electrical equipment based on the defect saliency map of each to-be-analyzed image. According to the invention, the accuracy of high-voltage electrical equipment surface defect identification can be improved.

A modular electric power take-off (E-PTO) system for a refuse vehicle includes a modular housing. The modular E-PTO also includes a motor, an inverter, a battery, and a hydraulic pump positioned within the modular housing. The modular housing is removably coupled with a front of a waste receptacle or a hopper of the waste receptacle of a refuse vehicle.

The invention provides a fault positioning method and system based on multi-mode acousto-optic electric signal collaborative diagnosis, and the method comprises the steps: firstly collecting an acoustic signal sequence, an optical signal sequence and an electric signal sequence during the operation of high-voltage electrical equipment, and then carrying out the cross-mode signal level correlation processing of a multi-mode signal, and generating a multi-mode signal correlation level chain; extracting a dynamic association feature set based on the multi-modal signal association hierarchical chain, inputting the dynamic association feature set into the fault feature evolution model to generate a fault feature identification sequence and a feature space diffusion trajectory, and finally determining a fault initial region and a fault influence boundary range of the equipment according to the fault feature identification sequence and the feature space diffusion trajectory. Therefore, the accuracy and reliability of fault positioning of the high-voltage electrical equipment can be effectively improved.

The invention discloses a high-voltage circuit breaker arcing monitoring system and method, and relates to the technical field of power equipment operation state detection, and the method comprises the following steps: S1, synchronously collecting arcing spectral signals and electromagnetic interference vector data under a unified time reference, and carrying out primary differential processing to generate stable base plane signals; s2, inputting the stable base plane signal into the interference identification model, generating a multi-dimensional spectrogram through time-frequency mapping, extracting an interference time sequence boundary, and outputting an interference weight matrix; the arcing monitoring method based on spectrum and electromagnetic signal synchronous acquisition is constructed, interference identification, signal purification, energy analysis and control instruction generation are fused, parameter self-optimization is realized through closed-loop feedback, the arcing identification accuracy and the arc quenching response efficiency are effectively improved, and the arcing monitoring method is suitable for large-scale popularization and application. And the operation safety and the intelligent level of the circuit breaker in a strong interference environment are enhanced.

The invention relates to the technical field of power grid state monitoring, in particular to an intelligent monitoring and early warning method and system for a high-voltage power grid, and the method comprises the steps: collecting the multi-dimensional parameter data of a power grid node, and obtaining the multi-dimensional parameter data of the power grid node based on the relative deviation of the data of each dimension in a local window and the mean value of the data of each dimension in combination with the correlation coefficient of the data of each dimension; calculating parameter fluctuation attention at a target moment so as to correct parameter data of each dimension; processing the data points through a clustering algorithm to obtain a plurality of clusters, and selecting the cluster center of the cluster with the most data points as a power stability index; and calculating the relative deviation between the data point and the index, and generating a state early warning coefficient so as to estimate and evaluate the abnormality of the power grid node region and generate an early warning signal. According to the method, parameter fluctuation is accurately quantified by fusing the deviation degree and correlation of the multi-dimensional data of the local window, and a foundation is built for monitoring and early warning.

The invention discloses a high-voltage circuit for an electric flame stove. The high-voltage circuit comprises a PFC circuit, a high-frequency conversion circuit, a boosting transformer, an energy coupling circuit and a voltage doubling circuit which are electrically connected in sequence. According to the EMI filter circuit, common-mode interference and differential-mode interference are filtered out, and pure alternating current input is provided for a back-end PFC circuit; two chips are adopted in the PFC circuit, so that the PFC circuit 300 finally realizes the consistency of the current waveform and the voltage phase; in the other embodiment of the invention, double chips are adopted, so that'fault linkage protection 'is realized; stable discharging of multiple groups of positive and negative electrodes is achieved through multiple groups of single energy coupling capacitors and independent voltage doubling rectifier bridges which are connected in parallel.

The invention relates to the technical field of batteries, in particular to a lithium ion secondary battery. The lithium ion secondary battery comprises a negative plate and electrolyte, the negative plate comprises a negative current collector and a negative active layer located on at least one side surface of the negative current collector, the negative active layer comprises a first coating and a second coating which are arranged in the thickness direction of the negative plate, and the first coating is located between the negative current collector and the second coating; the second coating comprises first silicon carbon, and the sphericity degree of the first silicon carbon is 0.8-1; the silicon content of the first silicon carbon is 30%-60%; the average particle size of the first silicon carbon is R1, and R1 is more than 6 microns and less than or equal to 15 microns; the electrolyte comprises a fluorine-containing solvent and a nitrile compound, the fluorine-containing solvent comprises fluoroethylene carbonate and / or ethyl difluoroacetate, based on the total weight of the electrolyte, the content of the fluorine-containing solvent is w1, and w1 is larger than or equal to 30% and smaller than or equal to 70%; the content of the nitrile compound is w2, and 0.4% < = w2 < = 7%. The lithium ion secondary battery provided by the invention has good cycling stability and dynamic performance at high voltage and high temperature.

The invention discloses a high-voltage power switch fault diagnosis method based on wavelet threshold correction and noise reduction. Acquiring a voltage signal of the high-voltage power switch by using a sensor, and performing synchronous sampling; a wavelet threshold value correction noise reduction method is adopted to carry out noise reduction processing on the collected signals, wavelet detail coefficients are calculated through multi-scale decomposition, a threshold value is adaptively corrected based on the peak sum ratio, and the noise removal effect is optimized; thirdly, performing normalization processing on the denoised signal, mapping the signal to a polar coordinate system, constructing a two-dimensional Gramer angle field containing an included angle cosine value and amplitude information, and realizing time sequence-space conversion of the signal; and finally, generating two-dimensional image data of the voltage signal of the high-voltage power switch, and providing feature input for subsequent state evaluation and fault detection. According to the method, wavelet transform and two-dimensional feature mapping are combined, noise interference can be effectively reduced, the signal distinguishability and the information retention capacity are improved, and the method is suitable for state monitoring and intelligent diagnosis of a power system.

The invention discloses a fault detonation simulation test method and platform for an extra-high voltage converter transformer network side bushing, and the method comprises the steps: providing a critical value calculation method for primary physical explosion and secondary chemical explosion of the extra-high voltage converter transformer network side bushing under different arc fault energy conditions; and the critical conditions of primary physical explosion and secondary chemical explosion can be accurately judged. According to the invention, the whole dynamic evolution process from rapid cracking of transformer oil and sudden pressure increase caused by converter transformer fault arc to superposition of physical explosion and explosion chemistry can be truly simulated, a grid-side bushing fault detonation critical discrimination method is provided, and technical parameters and theoretical support are provided for the explosion-proof and pressure-relief design of the converter transformer.

Presented are high-voltage (HV) electrical system architectures for vehicle-to-vehicle (V2V) charging of vehicle batteries, methods for making / using such systems, and vehicles equipped with such systems. An HV electrical system for a motor vehicle includes a main HV bus that electrically connects the vehicle's traction motor(s) to the vehicle's battery pack(s), and a charging inlet port that electrically mates with and receives direct-current (DC) power from DC fast-charging (DCFC) cables of a donor vehicle and a charging station. A DC-to-DC (DC-DC) converter is interposed between and electrically connects the charging inlet port to the main HV bus. The DC-DC converter is operable in a bypass mode, in which the DC-DC converter passes therethrough DC power received from the DCFC cable of the charging station, and a vehicle-to-vehicle (V2V) mode, in which the DC-DC converter modulates DC power received from the DCFC cable of the donor vehicle.

The invention relates to the technical field of power equipment inspection, in particular to a high-voltage electrical equipment inspection method and system based on microphone array measurement. The method comprises the following steps: acquiring array sound signal data, analyzing the array sound signal data, and determining sound signal feature information; obtaining a layered structure parameter set and an insulating medium parameter set of the target electrical equipment, performing targeted compensation and correction on the sound signal feature information according to the layered structure parameter set and the insulating medium parameter set, and determining abnormal voiceprint feature information; and generating abnormal component information according to the abnormal voiceprint feature information, and determining and outputting an abnormal detection report. According to the invention, non-contact real-time detection of the high-voltage electrical equipment in operation is realized, the adaptability of the detection process to the high-voltage electrical equipment which is internally provided with a multi-layer composite structure and is filled with an insulating medium is enhanced, and the positioning accuracy of a fault position in the equipment is improved.

The invention relates to the technical field of intelligent diagnosis of power equipment, and provides a multi-mode fusion extra-high voltage converter transformer fault diagnosis method and system, and the method comprises the steps: collecting a multi-mode signal from a sensor of an extra-high voltage converter transformer, and classifying the signal into a plurality of modes; performing intra-modal feature reinforcement learning on the multi-modal data by adopting a SimCLR framework to obtain a discriminative representation feature vector zm of each modal; inputting the zm into a Transform branch encoder of a corresponding mode, and obtaining context feature vector enhancement representation hm of each mode; mapping the hm of different modalities to the same dimension in a unified manner, and performing weighted attention fusion to obtain feature vectors zf of all modalities after fusion; and inputting a multi-layer perceptron classifier (MLP) to obtain a fault category prediction result of the extra-high voltage converter transformer. According to the method, the multi-mode signals are processed and fused in parallel, and the fault recognition capability of the model on the extra-high voltage converter transformer in the complex operation state is improved.

The invention discloses an insulator pollution flashover monitoring device and method, and relates to the technical field of online monitoring and fault diagnosis of high-voltage power equipment. The monitoring unit comprises a fixing piece, a hanging piece arranged on the fixing piece, a swing arm rotationally arranged on the fixing piece and detection assemblies arranged on the swing arm at intervals in the length direction of the swing arm; the visual acquisition module is arranged on the unmanned aerial vehicle; the hanging piece is detachably connected with the unmanned aerial vehicle, the fixing piece is used for being detachably and fixedly connected with an insulator, the swing arm is in driving connection with a driving piece, the driving piece can drive the swing arm to swing around a first axis, and the first axis is perpendicular to a second axis of the insulator to be detected. The detection environment of the electric field probe is less affected by the surrounding insulator chain, so that the obtained monitoring data is more representative, and the monitoring result is more accurate.

The invention relates to an ultra-high voltage line lightning resistance level evaluation method and device based on a tower head gap structure. The method comprises the following steps: constructing a simulation model according to line structure information and electrical parameters of an extra-high voltage line and tower structure information of a power transmission tower; inputting lightning current waveform parameters and lightning channel wave impedance parameters of the extra-high voltage line into the simulation model to obtain voltage distribution information and current propagation characteristic information of the extra-high voltage line under a lightning stroke condition; flashover criterion information is determined according to the insulator string discharge voltage characteristic information and the tower head air gap breakdown voltage characteristic information of the extra-high voltage line; and according to the voltage distribution information, the current propagation characteristic information and the flashover criterion information, determining a lightning resistance level evaluation result. By adopting the method, the influence of the breakdown characteristic of the tower head air gap, the complexity of the tower structure and the dynamic characteristic of lightning current propagation on the lightning resistance level evaluation can be comprehensively considered, and the accuracy of the lightning resistance level evaluation result of the extra-high voltage line is improved.

The invention relates to a power distribution network voltage partition control method and system based on a hierarchical K-means clustering algorithm, and belongs to the technical field of power distribution system voltage partition optimization. According to the technical scheme, power distribution network node parameters are collected in a self-adaptive partition mode, a node sensitivity coefficient and an eigenvector of an electrical distance are constructed, and then a K-means algorithm is used for fine region division; selecting a dominant node: solving a Jacobi matrix through load flow calculation, extracting a voltage sensitivity coefficient, and selecting a node with the maximum sensitivity as a dominant node in each partition; multi-objective optimization: constructing an optimization model with minimum network loss, minimum voltage deviation and highest voltage stability as objectives; and partition cooperative control: accessing wind power and photovoltaic power to the dominant node, adjusting reactive power output in real time according to an optimization result, and realizing partition autonomy and global cooperation. According to the invention, voltage fluctuation and out-of-limit are inhibited, system network loss is reduced, control efficiency and economy are improved, and the method is suitable for complex topology and high permeability scenes.

The invention belongs to the technical field of simulation analysis, and particularly relates to a medium-high voltage switch cabinet internal humidity inversion calculation method based on simulation analysis, which comprises the following steps: establishing a geometric model of a switch cabinet, importing the geometric model into finite element simulation software to obtain a simulation analysis model, adding each physical field and computational domain and boundary conditions thereof, and calculating the internal humidity of a medium-high voltage switch cabinet. All the physical fields are coupled, and mesh generation is carried out; performing numerical solution on the simulation analysis model by using a transient solver to obtain a temperature and humidity distribution condition in the switch cabinet; the simulation analysis model is optimized, a simulation data set is constructed, and a PINN is trained; based on the environment temperature and humidity and the operation current collected in the actual operation of the switch cabinet, the trained PINN is used for prediction, and the steady-state relative humidity of the current transformer is obtained. According to the invention, based on the limited boundary monitoring data, efficient and accurate reconstruction of the humidity field of the key area in the switch cabinet is realized, and a feasible path is provided for equipment state sensing and condensation risk early warning.

The invention discloses a partial discharge mode identification method and device, and relates to the field of power equipment fault diagnosis, and the method comprises the steps: collecting a partial discharge signal of high-voltage electrical equipment; preprocessing the collected data to obtain a single pulse signal; the method comprises the following steps of: generating a time-frequency graph of a single pulse on the basis of a continuous wavelet transform (CWT) method, and carrying out spatial feature extraction on the generated time-frequency graph by using a multi-scale convolutional neural network (MCNN); the features extracted by the MCNN are input into a bidirectional long short-term memory neural network (BiLSTM), and the time sequence characteristics of the partial discharge features are obtained; an attention mechanism is used to focus key segments of a splicing sequence output by the BiLSTM, global features are extracted, and the accuracy of pattern recognition is improved. According to the invention, mode identification can be carried out according to the collected partial discharge signal, the partial discharge type is judged, related personnel are helped to make a targeted maintenance plan, and long-term reliable operation of electrical equipment is guaranteed.

The invention discloses a high-safety station explosion-proof transformer and a using method, and relates to the technical field of transformers. The explosion-proof transformer comprises a transformer body arranged in an explosion-proof shell, a plurality of cooling fins are arranged on the side portion of the transformer body, the explosion-proof transformer further comprises a pressure relief unit, the pressure relief unit comprises a plurality of pressure relief boxes arranged in the explosion-proof shell, and a pressure relief assembly is arranged in each pressure relief box; a pressure monitoring sensor for monitoring and releasing the internal pressure of the transformer main body is arranged in the pressure relief assembly, and an adjusting assembly and a heat dissipation assembly are arranged on each pressure relief box. The transformer has the advantages that multi-point pressure monitoring can be carried out on the interior of the transformer body, whether high voltage occurs in the transformer body or not is monitored in real time, targeted pressure relief and explosion prevention can be carried out on a high-voltage part after the high voltage is monitored, the heat dissipation range and the heat dissipation efficiency can be improved in a targeted mode according to the pressure relief condition, and the heat dissipation efficiency is improved. Synchronous explosion-proof treatment of the inside and the outside is realized, and the explosion-proof safety is higher.

The invention relates to the technical field of composite insulator detection, in particular to an autonomous recognition method and system for typical defects of an ultrahigh-voltage line composite insulator, and the method comprises the steps: collecting an inspection image of the ultrahigh-voltage line composite insulator; calculating a temperature rise characteristic coefficient by using the color characteristics in the visible light image and the infrared image and the relationship between the color characteristics and the environment humidity; calculating a defect identification coefficient in combination with the spatial characteristics of the temperature rise phenomenon of the composite insulator; and finally, detecting and identifying typical defects of the composite insulator by utilizing the defect identification coefficient. The invention aims to improve the recognition quality of the typical defects of the composite insulator of the ultrahigh-voltage line.

Lateral III-N devices such as AlGaN / GaN HEMTs can have structures which serve to improve performance and reduce current degradation. The III-N device can include a conductive substrate and a III-N material structure that includes a III-N buffer layer, a III-N channel layer and a III-N barrier layer where a compositional difference induces a 2DEG channel therein. The first portion is in ohmic contact with the 2DEG channel and the second portion extends over a top surface of the III-N barrier layer and is in direct contact with the top surface of the III-N barrier layer. The device further includes a drain-to-substrate pinch-off voltage and a maximum rated drain-to-source operating voltage which is greater than the drain-to-substrate pinch-off voltage, and the 2DEG channel is fully depleted of charge below the second portion of the drain electrode when the III-N device is biased at or above the maximum rated drain-to-source operating voltage.

The invention discloses a VR interaction method and system for virtual disassembly and assembly teaching of a three-electric system of a new energy automobile. The invention relates to the technical field of VR teaching. And loading a 3D model and a scene configuration file, updating a virtual scene in real time, constructing a scene topological structure, recording a component relationship, and initializing security rules and process configuration. Loading the 3D model and the scene configuration file by using an asynchronous loading technology based on a GPU (Graphics Processing Unit); updating the virtual scene in real time and prompting information; the father-son hierarchical relation of the components is recorded through the tree-shaped data structure, the disassembly and assembly process is controlled based on the constructed behavior tree, and it is ensured that students operate according to the correct sequence and steps. Safety rules and flow configuration are built in, for example, high-voltage electricity must be cut off firstly when the battery is disassembled and assembled, and safety accidents caused by misoperation are effectively avoided. And when the operation of the student is illegal, the state machine is triggered to roll back to the latest legal state, so that the student is helped to correct errors in time, and the smooth operation of the disassembly and assembly process is ensured.