74 results about "Fast evaluation" patented technology

The invention provides a method for rapidly evaluating the residual strength of a damaged composite stiffened wallboard structure, which is applied to the evaluation of the residual strength of a composite stiffened wallboard in an undetectable area in an actual aircraft structure under possible accidental source damage, and comprises the following steps: (1) damage identification based on a piezoelectric sensing system; (2) carrying out damage equivalence on a damage identification result; (3) constructing a residual intensity database; (4) training a neural network model of the residual intensity database; and (5) quickly evaluating the residual strength of the actual damaged wallboard based on the sensing system and the neural network model. After a flight task of a flight product is completed, on the premise that database construction and model training are completed in the earlier stage of the ground, the method can greatly shorten the evaluation period of the residual strength performance of the composite material stiffened wall plate, and therefore the method serves for identifying the re-flight capacity of an aircraft.

The invention discloses a method and a system for rapidly evaluating aerodynamic performance of an automobile body appearance. The method specifically comprises the following steps: generating a geometric curved surface sample of an automobile body surface by adopting a parameterized design method; carrying out fluid numerical analysis on a vehicle body external flow field; an encoder for vehicle body appearance surface geometry is established, and the geometric structure of the vehicle body surface is recognized; establishing a prediction model based on a multi-scale map neural network, and performing geometric data memory, transmission and updating on the flow field of the vehicle body appearance surface; and outputting vehicle body aerodynamic characteristic parameters (a resistance coefficient, a lift coefficient and a lateral force coefficient) and an error level. Compared with the prior art, the neural network algorithm is ingeniously designed, rapid prediction of the aerodynamic characteristic parameters of the automobile body is achieved, the method can be used for rapid performance evaluation in the automobile body development process, the design efficiency is improved, and the development cost is reduced.

The invention provides an AI Agent automatic optimization method. The method comprises the steps of constructing a multi-dimensional performance evaluation system, defining Agent performance indexes, establishing a quantitative evaluation model, carrying out weighted summation calculation to generate a comprehensive performance score, and positioning a performance short board. A multi-dimensional optimization target is generated, a strategy candidate set is generated based on a domain knowledge graph and historical optimization cases, and the optimization target is converted into a reward function of reinforcement learning based on reinforcement learning and human feedback; simulating training by utilizing a strategy candidate set, quickly evaluating the expected income of each strategy through Monte Carlo tree search, and screening out an optimal candidate strategy; and the ambiguity or high-risk strategy receives expert scores or correction suggestions, and converts the scores or correction suggestions into feedback reward optimization strategy sorting. According to the method, optimization efficiency and iteration speed are improved, optimization accuracy and adaptability are enhanced, manual intervention is reduced through the domain knowledge graph and a man-machine cooperation mechanism, high-risk strategies are avoided, and optimization safety and reliability are guaranteed.

The invention discloses a crane main beam non-probability reliability assessment method based on a convex set model, and the method comprises the steps: collecting the working condition and key section multi-source data of a crane, and carrying out the time alignment, missing measurement compensation and time-frequency feature extraction; selecting a parameter vector influencing the safety of the main beam, and constructing a combined convex set uncertain domain consisting of an interval box, an ellipsoid set and polyhedron linear constraints; based on a finite element and radial basis function substitution model, main beam key section response mapping is established, the proportion of equivalent stress and deflection relative to an allowable value is obtained, and an overall limit criterion is formed; executing worst case search in the uncertain domain, and calculating an opposite number of a maximum value of a limit criterion as a non-probability reliability index; and reliability indexes are further calculated and summarized at the section layer and the main beam layer, and the reliable state grading of the main beam is realized according to a preset threshold value. The method does not need to depend on probability distribution hypothesis, and rapid assessment of the safety of the crane girder can be realized under small sample and multi-source uncertain conditions.

The invention discloses a deep-water explosion container dynamic response prediction method, and relates to the technical field of deep-water structure safety protection, a deep learning prediction model is established, material characteristic parameters and external load parameters are taken as inputs, container dynamic response indexes are taken as outputs, model training, verification and testing are carried out by using a sample set, and a deep-water explosion container dynamic response prediction model is obtained. And a deep-water explosion container dynamic response prediction model capable of rapidly predicting the dynamic response of the container is obtained. According to the method, a high-quality training data set is constructed through numerical simulation, so that the physical authenticity and prediction precision of a machine learning model are ensured; and the trained model can realize rapid prediction of dynamic response, so that the problem that the precision and the efficiency are difficult to balance in the existing method is effectively solved, and the requirements of rapid evaluation and real-time early warning in engineering are met. The data set contains the explosion load parameters and the deepwater environment parameters, the defect that the application range of a traditional empirical formula is narrow is overcome, and the engineering application cost is reduced.

The invention discloses a pile forming form and inter-pile soil compactness evaluation method based on vibro-replacement gravel pile construction data. The method comprises the steps of finding a pseudo-residual vibration working section according to a real-time construction depth-time curve, determining a key stage according to a real-time construction filling amount-time curve, finally finding a time node of downward insertion / upward pulling of a gravel pile by a vibroflot according to an amplitude change rule of a real-time construction current-time curve, calculating a transverse extrusion and expansion range after reinforcement, and finally determining a reinforcement result. And the pile forming form is estimated, and the average compactness of the soil between the piles of the reinforced field is calculated. According to the method, evaluation of the pile forming form and the compactness of the soil between the piles is achieved through on-site construction data, and the method has the advantages of being high in evaluation speed, high in accuracy and the like and is suitable for reinforcing effect evaluation of the vibro-replacement gravel pile treatment foundation with the down-inserting and up-pulling construction technology.

The invention relates to the technical field of power system dynamic safety analysis, and discloses a mechanism-data fusion new energy power system minimum inertia demand rapid evaluation method, which comprises the following steps: in an offline stage, establishing an expansion system frequency response model containing new energy; generating a plurality of sample scenes in a given disturbance power range and a new energy permeability range; a model minimum inertia demand and a simulation minimum inertia demand are obtained through expansion of a system frequency response model and stepping type time domain simulation calculation, a polynomial regression method and a polynomial regression equation are utilized, and the coefficient and order of the polynomial regression equation are determined by adopting an optimization algorithm; during online evaluation, real-time disturbance power and new energy permeability of a power grid are obtained; and obtaining a model minimum inertia demand and a corresponding minimum inertia demand deviation compensation value, and outputting a final system minimum inertia demand evaluation result. According to the method, the final evaluation result has the calculation efficiency of the extended SFR model and the evaluation precision of stepping simulation.

The invention discloses a rapid pressure pipeline flow evaluation system and method based on RTK and non-contact liquid level sensor integrated measurement. The system comprises an integrated portable inspection well water surface elevation acquisition device and a matched data processing module. The device integrates RTKGNSS positioning, non-contact liquid level measurement and inclination angle compensation functions, and the relative distance of the water surface of an inspection well and the absolute coordinates of the device can be rapidly obtained; and after receiving the data, the matched data processing module calculates the absolute elevation of the water surface, derives the hydraulic gradient of the pipeline in combination with input pipeline parameters, and evaluates the flow velocity and the flow through a hydraulic formula. The method is based on the system, and rapid evaluation is achieved through the steps of initialization, multi-well collection, elevation calculation, slope derivation and flow evaluation. Pipe bottom elevation is not needed, the system integration degree is high, deployment is fast, precision is high, and the method is suitable for fast investigation and temporary flow monitoring of the urban underground pressure pipe network.

The application discloses a kind of based on GC-IMS pure milk flavor sensory digitalization fast evaluation method, belong to food analysis and evaluation technical field.The pure milk sample to be measured is detected by headspace sampling using GC-IMS, and a fingerprint spectrum is obtained.The fingerprint spectrum data or characteristic volatile component data is input into the OPLS-DA model, and the preference degree of pure milk is evaluated according to the clustering result.The construction method of OPLS-DA model is as follows: different pure milk samples are selected, and CATA sensory evaluation method is used for sensory evaluation of pure milk samples.Different pure milk samples are detected by headspace sampling using GC-IMS, and a fingerprint spectrum is obtained.Partial least squares-discriminant analysis method is used for regression modeling using fingerprint spectrum data or characteristic volatile component data to obtain OPLS-DA model.The application uses GC-IMS to digitally and quickly evaluate the flavor of pure milk, which has high sensitivity, does not require sample enrichment and concentration, saves detection time, and avoids tedious pretreatment process.

The application relates to the technical field of trajectory planning, and proposes a fast evaluation search method, a system and a terminal device of an optimal trajectory. The fast evaluation search method comprises the following steps: sampling a plurality of state points in a pre-planning space, performing pre-collision detection on the state points to remove points in conflict with obstacles, and obtaining effective sampling points; performing cost evaluation on the effective sampling points, wherein the cost evaluation comprises heuristic cost based on historical planning trajectory information and static cost based on motion characteristics; based on the result of the cost evaluation, iteratively searching from an initial state point: calculating the trajectory cost of a neighborhood state point and updating a search path in a gradient direction until an optimal feasible trajectory is output. The application improves the search efficiency of the trajectory by pre-collision detection to screen out invalid sampling points and a gradient iterative search mechanism.

The present application belongs to the technical field of flexible robots, and relates to a structure optimization method of a fin ray effect gripper, comprising the following steps: step 1: a co-rotation modeling method is used to construct a force-deformation relationship model of the fin ray effect gripper as a fast evaluation model of the performance of the gripper; step 2: structure optimization design parameters and multi-objective performance evaluation indexes of the fin ray effect gripper are determined; step 3: based on a Bayesian optimization algorithm, the fast evaluation model is combined to construct a multi-objective structure optimization framework, global optimal sample search is performed on the design parameters, and a Pareto front is solved; and step 4: experimental verification is performed on typical optimal parameter combinations in the Pareto front, and optimal structure parameters of the gripper suitable for different gripping scenes are output. The present application can be applied to the design and optimization of flexible, rigid and rigid-flexible hybrid robot compliant mechanisms, and can be widely applied to the high-performance design and parameter tuning of gripper structures in industrial gripping, service robots, precision operation and the like.

The application belongs to the technical field of multidisciplinary design, and discloses a data-driven AUV multidisciplinary design optimization method considering time consumption difference of simulation units. The method comprises the following steps: generating initial samples for an optimization object and dividing the initial samples into design samples of each discipline sequence; analyzing high-fidelity evaluation average time consumption of the design samples of each discipline sequence, calculating expansion multiples of the design samples of other non-most time-consuming discipline sequences based on the design samples of the most time-consuming discipline sequence as a benchmark to construct design samples according to a total time consumption consistency principle, performing high-fidelity evaluation on the constructed design samples to construct a discipline sequence library; establishing a proxy model of each discipline sequence based on the discipline sequence library; and dividing a multidisciplinary system of the optimization object into each discipline sequence and performing rapid evaluation based on the corresponding proxy model. The method of the application significantly improves optimization efficiency by solving the problem of evaluation time heterogeneity in the process of multidisciplinary design optimization.

The invention discloses a method for evaluating thermal decomposition behavior characteristics and risk degrees of same-type derivatives, which comprises the following steps of: firstly, carrying out a DSC (differential scanning calorimetry) test on the same-type derivatives of a certain substance to obtain initial thermodynamic data; analyzing an exothermic peak curve of the DSC, obtaining an after-treatment curve of exothermic quantity, conversion rate-temperature and reaction rate-temperature, and calculating thermal decomposition characteristic parameters including activation energy, pre-exponential factors, a decomposition mechanism function model, comprehensive thermal decomposition characteristic parameters and self-accelerated decomposition temperature; further quantitatively characterizing microstructure characteristics of group types, group positions and group volumes by using electronegativity, Hammett constants and group topological volumes, constructing a relation model between pyrolysis characteristic parameters and microscopic parameters by using a correlation coefficient, regression analysis and a judgment matrix, and determining the molecular structure of the same type of derivative according to a given molecular structure of the same type of derivative. Calculating corresponding pyrolysis characteristic parameters; and according to the property and process of the chemical reaction, establishing a pyrolysis risk degree calculation model of the same type of derivatives, and quantitatively evaluating the risk degree.

The application discloses a kind of small reservoir dam safety monitoring facility operating state fast evaluation method. Including: obtaining the initial measuring point state of target dam safety monitoring facility and field detection state, determine the measuring point ontology state;Obtain the monitoring time series in the set statistical period and execute singular value identification, obtain the identification result;Based on monitoring time series and identification result, calculate data anomaly proportion, current data stop detection duration and effective data missing duration;As a reference, determine the measuring point working state based on the preset threshold value determination rule;Combined with measuring point ontology state and working state, determine and output the evaluation result of the operating state of facility.The application can reduce the evaluation error caused by non-stationary environmental interference and data pollution, realize efficient, accurate quantification classification of the real reliability level of monitoring facility.

The invention provides a GEO electric propulsion satellite orbital transfer process solar cell radiation effect rapid evaluation method, which comprises the following steps that: firstly, a solar cell radiation damage space distribution database is constructed through space radiation effect analysis software, and the database comprises daily average equivalent 1MeV electron flux distribution data under different orbit heights, inclination angles and cover glass thicknesses; generating satellite space track data according to an electric propulsion orbital transfer strategy; counting accumulated operation time of the satellite in each height and dip angle interval according to a preset interval; and finally, multiplying and accumulating the daily average equivalent 1MeV electron flux corresponding to each interval by the accumulated running time to quickly obtain the accumulated equivalent 1MeV electron flux in the whole orbital transfer process. Therefore, the problem of long calculation time consumption of a traditional method is solved, and rapid evaluation support can be provided for radiation mitigation optimization design of the orbital transfer strategy.

The invention discloses a manned lunar vehicle elastic wheel traction performance rapid evaluation method and device, and the method comprises the steps: building a virtual lunar soil model based on a discrete element method, and obtaining the ground mechanics parameters of the interaction of lunar soil and wheels through a virtual pressing plate test and a virtual shear test; on the basis of the terramechanics parameters and the wheel parameters, the wheel soil acting force is calculated through an improved semi-empirical model, so that the traction performance of the wheels is evaluated; solving a wheel soil contact parameter by adopting an iteration mode, and evaluating the traction performance of the wheel according to the calculated wheel soil acting force; wherein the improved semi-empirical model divides the contact area of the wheel and the lunar soil into an elastic contact area with elastic deformation and a rigid contact area without deformation, the wheel soil acting force in the two areas is calculated respectively, and the wheel structure parameters and the lunar soil parameters are analyzed in a simulation mode according to the wheel structure parameters and the lunar soil parameters. And the traction performance such as hook traction force, rolling resistance and rolling efficiency of the elastic wheel can be quickly calculated.

This invention discloses a rapid evaluation method for the enhancement factor of the dynamic coefficient by the high-frequency component of a strong impact load, belonging to the field of structural dynamic response analysis technology. This method performs time-frequency domain energy accumulation analysis on the strong impact load signal, extracts the concentrated frequency of load energy and its proportion in the total energy, and then, based on this, combines the dynamic amplification factor under the triangular time history assumption to quantitatively calculate the enhancement factor of the dynamic coefficient by the high-frequency component of the strong impact load. This method is further extended to arbitrary frequency components and the entire frequency band to obtain the comprehensive enhancement result of the dynamic amplification factor by the high-frequency effect of the strong impact load. Compared with traditional dynamic analysis methods based solely on idealized time history assumptions, this invention can introduce the real time-frequency characteristics of strong impact loads while maintaining computational efficiency, effectively compensating for the insufficient consideration of high-frequency excitation effects. It is applicable to rapid dynamic response evaluation in engineering fields such as aerospace structures, high-frequency components, and precision equipment.

The invention discloses a workshop-oriented traffic vibration load influence rapid evaluation method, which comprises the following steps of: arranging an instantaneous synchronous measurement array comprising a plurality of measurement points on one side, adjacent to a traffic road, of a workshop area along the direction vertical to the road; performing 1 / 3 octave analysis on the vibration data of each measuring point to obtain a vibration speed effective value of each measuring point under each 1 / 3 octave center frequency; for each 1 / 3 octave center frequency, performing power function fitting on the vibration velocity effective value of each measuring point under the frequency and the distance from the measuring point to the road, and establishing a frequency-space attenuation model; and determining a vibration velocity frequency spectrum of the target position caused by traffic vibration by using a frequency-space attenuation model, and calculating a traffic vibration dominance index TVDI of the target process equipment in combination with vibration sensitive characteristics of the target process equipment so as to quantitatively evaluate the influence degree of the traffic vibration on the target process equipment. According to the invention, traffic vibration influence evaluation is realized through one-time short-time synchronous measurement.

The present disclosure relates a method for evaluating packets of subscribed data streams comprising receiving incoming data packets belonging to a plurality of data streams; buffering the incoming data packets in a raw packet buffer; extracting the first words of the incoming data packets and forwarding the extracted first words to a packet header buffer; evaluating the first words in the packet header buffer, wherein the evaluation comprises extracting information identifying a data stream, performing a binary search on the extracted information to determine whether the incoming data packet from which the information was extracted belongs to one of the subscribed data streams, storing the result in a packet evaluation result buffer; determining based on the result whether a data belongs a subscribed stream; reading, in case the data packet in the raw packet buffer belongs to one of the subscribed streams, the data packet from the raw packet buffer.

The invention belongs to the technical field of safety evaluation of service materials, and particularly relates to a microscopic rapid evaluation method for a long-time thermal service state of a nuclear power pressure vessel material, which comprises the following steps of: 1, selecting a pressure vessel micro-area material in a certain service state; 2, a specific corrosive liquid is selected for corrosion for a certain time, and a state monitoring sample piece is obtained; step 3, the microscopic morphology of the state monitoring sample piece is shot through a microscope; 4, counting the percentage composition of the corrosion area; and 5, evaluating the thermal service state of the material according to the linear relationship between the percentage composition of the corrosion area and the thermal aging time. According to the microscopic rapid evaluation method for the long-time thermal service state of the nuclear power pressure vessel material, thermal aging degradation damage of the pressure vessel material is presented through an over-corrosion method, rapid evaluation of the thermal aging state can be achieved only by obtaining a local monitoring material, and the microscopic rapid evaluation method still has a good prediction effect on long-time thermal service equipment.

The embodiment of the invention provides a method and device for evaluating an intelligent agent, equipment and a medium, and the method comprises the steps: obtaining to-be-evaluated data which at least comprises data for at least one bad case; based on the number of the at least one bad case, obtaining at least one first agent corresponding to the at least one bad case; and correspondingly processing the at least one bad case by using the at least one first agent so as to generate at least one bad case analysis result corresponding to the at least one bad case. According to the method, the multi-agent collaboration architecture for evaluating the performance of the agents is established. For each bad case of the to-be-evaluated agent, the corresponding agent can be adaptively acquired to carry out bad case-by-bad case analysis. According to the mode, the effects of high evaluation speed and comprehensive evaluation results can be achieved, and the context explosion phenomenon can be prevented.

The invention relates to a parallel deduction and rapid evaluation system for quality evaluation of a test scene set, and belongs to the technical field of software engineering. According to the system, a k8s tool is adopted to bind a test scene set with an intelligent agent and then deduce in parallel, so that the deducing efficiency of a series of intelligent algorithms in a large number of test scene sets is improved; the data is stored by applying a ClickHouse column type storage method, so that the data compression rate and the query efficiency are improved; and through expert scoring and consistency verification, the reliability of an evaluation result is ensured.

The invention discloses a building group demand response potential multi-dimensional rapid evaluation method considering user intentions. The method comprises the following steps: constructing an EnergyPlus calculation model and an RC initial model of a typical building type; respectively inputting the same input data into the EngyPlus calculation model and the RC model to obtain a first calculation result of the EngyPlus calculation model and a second calculation result of the RC model, fitting to obtain an error value, and adjusting model parameters of the RC initial model according to the error value to obtain an RC accurate model; and performing demand response on each single building based on an RC accurate model, analyzing a demand response result to obtain a physical attribute index, a social attribute index, an economic attribute index and a probability that users in the building group participate in response adjustment, and further calculating to obtain a demand response index of the building group. According to the method, more multivariate evaluation indexes are adopted, and user response intentions are taken into consideration, so that the demand response potential of the building group can be evaluated more scientifically and accurately.

The application discloses an aero-engine key part dangerous position temperature rapid evaluation method and device, electronic equipment and storage medium, the method comprises the steps that S1, the temperature value, pressure value and rotating speed value in the flow channel are calculated by using the proportional conversion method, the steady-state temperature of the key part dangerous position is calculated, the transition state temperature calculation reduction model is established, and the model parameters are obtained; S2, the material parameters of the aero-engine key part, the temperature value, pressure value and rotating speed value corresponding to the main flow channel at the life calculation point are substituted into the transition state temperature calculation reduction model to rapidly calculate the transient temperature of the aero-engine key part dangerous position under any state. The application directly calculates the rapid temperature of the key part dangerous position by substituting the mathematical theoretical model established by the flight parameters, avoids the consumption of hardware resources and solving time caused by large-scale simulation solving, improves the calculation speed to the order of millisecond, shortens the design cycle, and reduces the calculation cost.

The application discloses a kind of online refining effect fast evaluation methods of automobile die-casting aluminum alloy melt, specifically related to melt refining quality monitoring field, the method includes: through acoustic sensor, thermal imager and electrochemical sensor, synchronous acquisition refining process multimodal sensing data;Parallel processing various data streams, extract acoustic features characteristic of melt viscous property, temperature field characteristics of thermal uniformity and electromotive force characteristics of alumina concentration change;Using time series fusion network based on attention mechanism, analyze the dynamic coupling relationship of multiple parameters, and adaptively calculate the refining effect index;Compare the dynamic threshold interval generated by historical data clustering, realize real-time evaluation and feedback control of refining effect, and output the decision instruction of adjusting refining gas flow, stirring speed or holding power.The application realizes multidimensional, high-precision online monitoring and rapid evaluation, significantly improves the quality control efficiency and stability of the melt refining process.

The application discloses a kind of social network information propagation effect fast evaluation's prediction user influence method, method includes the following steps: step A, training data and constructing with offline annotation;Step B, seed set-graph joint coding;Step C, comparative learning;Step D, influence value regression and sorting consistency joint training;Step F, agent model auxiliary evolution's intelligent optimization solution.The application significantly reduces the time overhead and the power consumption of single influence evaluation, so that the influence maximization method can be stably landed in large-scale network, real-time or quasi-real-time business system;The application constructs influence similar sample, significantly different sample and marginal gain sorting sample, and applies constraint in representation space and output space simultaneously, so that the agent model can still maintain stable and reliable relative ordering relationship between candidate seed set in the presence of certain numerical estimation error, significantly improve the overall consistency.

The application discloses a kind of transient power angle stability online evaluation method, device and system, belong to power system stability analysis technical field, by prediction model, the relative speed of the disturbed serious generator set pair in power system is predicted, and then relative power angle is predicted;Relative speed and relative power angle are used to carry out PMLE estimation and PMLE phase plane trajectory calculation, and finally according to PMLE and its phase plane trajectory, the stability of power system transient power angle is quickly and accurately evaluated.Utilize the model-free method of PMLE to realize the online fast evaluation method of transient stability, can greatly reduce the time-consuming while maintaining excellent accuracy to all kinds of power angle swing;Thus solve the technical problem of low rate of existing transient power angle stability evaluation method.In addition, the speed and power angle of each generator, without involving system structure and other model parameters, so data is easy to obtain, so that the method application is more in line with the actual, can be applied to engineering practice.

The invention provides a large-scale programmable metasurface array far-field rapid evaluation method based on subarray partition, which comprises the following steps: modeling array far-field performance as an electromagnetic scattering problem, enabling a controllable device in a metasurface unit to be equivalent to a network port by combining an electromagnetic scattering theory and a microwave network theory, enabling different coding states to correspond to port load impedance, and enabling the network port to be equivalent to the network port. A total scattering field evaluation relational expression for separating a structure scattering field from a mode scattering field is constructed, in order to improve the large-scale array analysis efficiency, a regional solving strategy is adopted, the whole array is divided into a plurality of sub-arrays for high-precision simulation, pre-processing data is generated based on the sub-array result, and the pre-processing data is used for analyzing the large-scale array. Comprising a structure scattering field, a port scattering parameter matrix and a single-port excitation radiation field, so that far-field characteristics in different coding states are quickly calculated, and repeated full-wave solution does not need to be carried out on the whole large array. According to the method, the calculation complexity can be remarkably reduced on the premise that the precision is guaranteed, and efficient and rapid evaluation of the far-field performance of the large-scale programmable metasurface array is achieved.

The invention relates to a rapid evaluation method for high-temperature energy storage characteristics and failure behaviors of a dielectric film, and belongs to the technical field of performance testing of electrical insulating materials. The method comprises the following steps: placing a dielectric film sample in a closed temperature control environment, applying stage step boosting until breakdown, and collecting a leakage current curve under each stable voltage until the sample is broken down; analyzing a Weibull distribution scale parameter alpha and a Weibull distribution shape parameter beta of the breakdown field intensity at different temperatures, an inflection point electric field in the leakage current curve and current density J under preset field intensity, and drawing alpha-T, beta-T and eta-T change curves; and finally, determining the temperature resistance grade, the insulation degradation temperature and the leakage current surge temperature of the material by taking the characteristic breakdown field strength, namely a scale parameter alpha, a shape parameter beta, an inflection point electric field in a leakage current curve and the temperature corresponding to the temperature surge position of the charging and discharging efficiency eta as characteristic criteria. According to the method, the multi-dimensional high-temperature performance parameters of the material are obtained in a single test process, and the problem that a traditional method is low in efficiency is solved.