193 results about "Physical test" patented technology

The invention discloses a ventilation cooling optimization method for an all-hydrogen-cooled gas turbine generator, and relates to the technical field of all-hydrogen-cooled generator cooling, and the method comprises the steps: analyzing cooling demands, calculating loss in combination with a high-frequency start-stop peak regulation working condition, and setting a stator RTD temperature, an iron core temperature and a temperature rise target; an end ventilation structure is designed, the diameter of the fan is optimized, and bar gaps, wind shield holes and inner supporting ring ventilation grooves are formed; optimizing variable air ducts of the iron core, and adjusting the width of the air ducts according to thermal load partitions; cFD coupling simulation verification is carried out, and a loss data simulation flow field and a temperature field are imported; carrying out physical test iterative optimization, manufacturing a prototype model, testing, and adjusting parameters until errors are qualified; operation monitoring and dynamic adjustment are carried out, and a sensor is installed to collect data in real time and adapt to working condition requirements. Cooling uniformity and efficiency are improved, peak regulation start and stop working conditions are adapted, hydrogen parameter change influences are balanced, vibration and cooling are cooperatively controlled, operation and maintenance convenience is improved through modular design, and long-term stable operation of the generator is guaranteed.

The invention belongs to the technical field of escalator braking performance detection, and particularly discloses an elevator braking performance intelligent detection method and system.The method comprises the steps that a parameterized simulation model is built based on mechanical topology and dynamic characteristics of an escalator, and firstly, model initial calibration is completed through a no-load braking test; then, a gradient simulation load scheme is designed in combination with actual operation load distribution, advanced calibration is performed on the model through physical test data under multi-stage loads, and finally, accurate prediction of the full-load braking performance is realized by relying on a high-fidelity calibration model, so that actual measurement of full-load weights is not needed, the detection safety and efficiency are remarkably improved, and the detection efficiency is improved. And the problem of model mismatching caused by factors such as equipment aging and abrasion can be effectively solved through a data-driven iterative calibration mechanism, the long-term prediction precision is ensured, and reliable technical support is provided for normalized and intelligent evaluation of the braking performance.

The invention relates to the technical field of automobile intelligent driving, in particular to an intelligent network connection automobile digital twinning evaluation method and system for extreme scenes. The evaluation method comprises the following steps: constructing a knowledge graph; generating an extreme scene; the automatic driving system is tested in a virtual environment generated by the digital twin test platform based on an extreme scene; predicting a safety risk score in real time, and if the safety risk score exceeds a safety threshold, sending an intervention instruction to the digital twin test platform; performing anomaly detection on the full-quantity test log, deriving a scene and injecting the scene into a scene library if a performance inflection point is found; and calculating a root cause based on the weight vector, the system fault cause and effect graph and the test data, and generating a diagnosis result. According to the method, extreme scenes can be covered, the system can be scored from multiple dimensions, the performance bottleneck can be accurately positioned, and the closed loop of the test scene can be realized. According to the system, two-way closed loop and common evolution of physical test data and a virtual test environment are realized through a cloud side end architecture, and continuous synchronization and two-way interaction with real world data are realized.

The invention provides a reinforced concrete member damage assessment method, system, equipment and medium, and belongs to the technical field of structural damage assessment, and the method comprises the steps: constructing a fire response feature knowledge base containing fire physical test data and simulation data of a reinforced concrete member, training the machine learning agent model by taking component design parameters and fire working condition parameters of the reinforced concrete component in the knowledge base as input parameters and taking post-fire component response data as output parameters to obtain a prediction model for predicting direct physical damage indexes of the post-fire reinforced concrete component; constructing a fire vulnerability curve representing the relationship between the failure probability and the fire intensity based on the prediction model; and receiving parameters of a to-be-evaluated component, and generating and outputting a damage evaluation result of the component based on the prediction model and the fire vulnerability curve. According to the invention, through data and model collaborative optimization, high-efficiency and accurate post-fire reinforced concrete member damage evaluation is realized.

The invention relates to an interactive intelligent test analysis system based on a natural language. The system comprises a natural language processing and dialogue management module used for receiving and presenting natural language information, analyzing user input, identifying operation intention and extracting key parameters, an intelligent parameter recommendation and execution module used for connecting and controlling the physical test instrument according to a language understanding result, and an intelligent parameter recommendation and execution module used for importing from the instrument or a file, the working area and management module is used for storing and managing test data; the data processing and analysis engine module is used for automatically selecting and executing a data analysis algorithm according to user intention and context; the natural language processing and dialogue management module analyzes and generates a structured intention based on a pre-trained large language model and a domain knowledge base; and the intelligent parameter recommendation and execution module automatically recommends and sets optimal instrument parameters according to the structured intention based on a pre-trained large language model and a domain knowledge base. According to the invention, complex signal processing is simplified into natural dialogue interaction with experts.

The invention discloses an SSD full-automatic aging test system and method, and the system comprises a physical test cluster layer which comprises one or more test bins, a central control and data processing unit, a task scheduling and resource management engine, a self-adaptive stress field generator, a data lake, and a digital twinborn model. The system comprises a data processing module for establishing a corresponding virtual instance and a model calibration and synchronization interface for each SSD body, a predictive analysis module for predicting the residual life and the potential fault mode of the SSD body based on accelerated operation of a digital twin model, and a reinforcement learning module for establishing a model calibration and synchronization interface for each SSD body, and keeping the state of the virtual instance consistent with the state of the physical SSD body by using information of a data lake. The self-adaptive stress field generator works cooperatively with the self-adaptive stress field generator; and the feedback and evolution layer is used for calculating a test efficiency index TEI and periodically optimizing a self-adaptive stress field generation algorithm and a strategy network of a reinforcement learning agent by utilizing the accumulated TEI and data.

The invention discloses multi-parameter test analysis equipment for a complex environment, which belongs to the technical field of chemical or physical test analysis and comprises a test cabin, a comprehensive measurement and control system, a vacuum pumping system, a field environment simulation system and a climate temperature and humidity simulation system. The vacuum pumping system, the field environment simulation system and the climate temperature and humidity simulation system are sequentially arranged on the outer side of the test cabin body and are communicated with the test cabin body. By changing and adjusting the air pressure, the temperature, the humidity, the wind, the ultraviolet radiation, the space range and the air density in the specified range in the test cabin body, the extreme climate environment of any single parameter can be simulated, the special environment of combination, alternation and intersection of multiple parameters can also be simulated, and different types of test pieces can be made to have different functions. Test detection operation under a traditional atmospheric state, atrocious weather and an extreme environment of an outdoor environment is completed in the same space, so that multi-parameter data of different types of test pieces can be obtained.

The invention discloses a digital twinborn body and a digital twinborn method for a hydraulic test system of a turbine pump of a liquid rocket engine, and solves the technical problem of high production and test resource consumption caused by research and development of engine products. The basic architecture of the digital twinning body comprises a digital twinning engine, a physical entity and a digital virtual body, and dynamic unification of digital virtual body prediction performance and object actual measurement performance is realized through virtual-real interaction and model training and optimization; finally, the display effect that a digital virtual body completely replaces a liquid rocket engine turbine pump hydraulic test system entity can be achieved, and the contradiction between increasing turbine pump hydraulic test tasks and limited physical test resources is greatly relieved.

The invention relates to the technical field of dynamic balance testing of rotating machinery, and discloses a dynamic balance state testing system based on equipment operation data, which comprises a synchronous sampling module, a fundamental frequency vector analysis module and an influence coefficient self-adaptive calibration module, the synchronous sampling module collects key phase pulses and original vibration signals of the rotating equipment; a fundamental frequency vector analysis module extracts an instantaneous rotating speed and a real-time fundamental frequency vibration vector; the influence coefficient self-adaptive calibration module stores a weight matrix representing rotor supporting characteristics, monitors a rotating speed fluctuation variance, corrects the weight matrix according to complex deviation of a vibration vector when the variance exceeds a preset threshold value, solves a net unbalance vector of the controlled rotating equipment, and outputs the net unbalance vector. According to the method, the rotating speed micro fluctuation in the operation process is used as an excitation increment source, and the sensitivity model reflecting the rotor bearing characteristics is constructed, so that the dynamic balance test gets rid of the limitation of adding a physical test weight, and the online test requirement under the continuous working condition is met.

The invention provides an asphalt material softening point prediction modeling method based on an infrared spectrum, and belongs to the technical field of road engineering material performance prediction. The method comprises the following steps: collecting infrared spectrum data of a multi-source asphalt sample and carrying out standardization pretreatment; fusing and extracting functional group quantitative features, wavelet multi-scale features and principal component dimension reduction features; constructing a high-stability feature subset by adopting a progressive feature optimization strategy guided by a physical mechanism; a self-adaptive Stacking fusion model is constructed and trained, the model integrates four base learners including PLSR, SVR, random forest and gradient boosting regression, and Bayesian ridge regression is used as a meta-learner to realize uncertainty quantification of a prediction result. The method can quickly output the predicted value of the softening point without a physical test, solves the technical problems of low efficiency and poor consistency of a traditional method, and is suitable for production quality control, on-site quick detection and formula optimization of asphalt materials.

The invention discloses a real object test block and method for calibrating magnetic particle inspection sensitivity of a locomotive axle, the test block is made of the axle, the test block is provided with sections B, C, D, E, F, G, H, I, J, K and L and an end face A, four longitudinal defect holes with the diameter of 1mm and the hole depth of 8mm are formed in the end face A, the section B, the section C, the section D and the section E, and the four longitudinal defects are equally arranged at 90 degrees in the circumferential direction; four longitudinal defects formed in the F section are arranged at intervals of 36 degrees in the circumferential direction; the H section, the I section, the J section, the K section and the L section are each provided with four transverse defect holes with the diameter of 1 mm and the hole depth of 8 mm, the four transverse defects are equally arranged at 90 degrees in the circumferential direction, and the four transverse defects formed in the G section are arranged at the intervals of 60 degrees in the circumferential direction. According to the physical test block and the method for calibrating the magnetic powder inspection sensitivity of the rolling stock axle, provided by the invention, the accuracy of magnetic powder sensitivity calibration is improved.

This invention discloses a hydrophobicity rating system for superhydrophobic surfaces of energy equipment, relating to the field of hydrophobicity rating technology. The system includes a data acquisition module, an optimal parameter combination module, a sample preparation module, a hydrophobicity quantification and evaluation module, a test closed-loop calibration module, and a hydrophobicity rating classification and output module. These modules are interconnected, and through their collaborative operation, the system quantifies, performs closed-loop calibration, and classifies the hydrophobicity index of superhydrophobic samples of energy equipment with different microstructures. The closed-loop calibration process fully considers both anti-icing and weather resistance, significantly improving the accuracy and generalization ability of the hydrophobicity rating results. This solves the problems of inaccurate evaluation results and inability to adapt to extreme field conditions caused by traditional evaluation systems relying solely on conventional laboratory environments, single physical tests, and empirical thresholds for rating. This enhances the intelligence level of hydrophobicity rating evaluation for superhydrophobic surfaces of energy equipment.

The present application relates to the field of connector testing, in particular to a connector-based locking structure testing method and system, comprising the following steps: building a multi-physical field coupling test environment to output a composite environmental stress; based on the actual application scenario of the to-be-tested locking structure, obtaining assembly deviation data, and obtaining an assembly deviation state through a preset multi-degree-of-freedom adjustable clamp; based on the physical data of the to-be-tested locking structure, constructing a three-dimensional model of the locking structure, giving real material mechanics parameters, inputting the composite environmental stress and the assembly deviation data into a finite element software for simulation testing, and outputting a simulation test data set; performing physical testing through the multi-physical field coupling test environment, and outputting a physical test data set; comparing and analyzing the simulation test data set and the physical test data set, and outputting a test report. The present application builds a multi-physical field coupling test environment, and combines a multi-degree-of-freedom adjustable clamp to make the test scenario closer to the real application working condition of the connector.

1. Name of the product in this design: Physical Test Bench. 2. Purpose of this design: For conducting physical experiments. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention provides an aero-engine complete machine digital test method which comprises the following steps: firstly, establishing an engine main combustion chamber fuel flow neural network PID control model and an open-loop control rule of a guide vane angle, a channel area and a thrust augmentation fuel flow, and establishing an engine control system digital test model according to the PID control model and the open-loop control rule; and an engine performance digital twin model is constructed and used for predicting and outputting real-time performance parameters according to the engine control parameters and the test run environment parameters. In the test process, the real-time rotating speed of the engine serves as a middle bridge, a closed-loop control loop is formed between the control system model and the performance model, the whole machine dynamic test process of the aero-engine is simulated, and the aero-engine can be driven to be subjected to a high-fidelity simulation test in a digital space only through environment parameters and the angle of a throttle lever. The real physical test requirement is reduced, the engine development efficiency is improved, and compared with a traditional method, the high coincidence between the digital test process and the real test is ensured.

The application discloses an elevator full-data simulation test system, and relates to the technical field of elevator testing.The scheme comprises a multi-source data acquisition module, a digital twin modeling module, a full-scene simulation test module, a data processing and analysis module, a closed-loop optimization module and a terminal interaction module.The application realizes full-cycle multi-dimensional data coverage of the elevator, integrates mechanical, electrical, environmental, personnel and fault data, improves the completeness of test data, constructs a full-dimensional model based on digital twin technology, realizes multi-element coupling simulation, simulates various working conditions, fits actual operating conditions, iterates the simulation model, outputs optimization schemes, improves test efficiency and optimization effect, supports custom parameters, meets the test requirements of various types of elevators, does not require a physical test platform, greatly reduces test costs and shortens the test cycle, and avoids safety risks in physical tests.

The invention relates to the technical field of physical test devices, and particularly discloses an AI digital-intelligent two-dimensional steady-state excitation Newton pendulum device, which comprises a steady-state parameter calculation module used for calculating control parameters of a motor according to the length of a light rope and the radius and material of a small ball; the steady-state parameter calculation module is connected with the motor, the motor is connected with the sliding rail device through the connector, the sliding rail device is arranged on the guide rail device, a guide rail of the guide rail device is vertically arranged, and the two small balls are connected with fixing points of the sliding rail device through the light ropes respectively. The motor drives the sliding rail device to longitudinally reciprocate along the guide rail through the connector according to the control parameters. According to the steady-state determination method based on combination of theoretical modeling and AI simulation algorithm optimization, scarce steady-state parameters can be accurately and rapidly obtained for a complex two-dimensional excitation system, and the two-dimensional excitation steady-state Newton pendulum is obtained by designing a two-dimensional excitation driving device and a digital intelligent measurement mode.

This invention discloses a small-sample Bayesian optimization sampling method and system based on cloud droplet data augmentation, belonging to the field of transportation engineering material design. Addressing the problems of limited initial samples and poor fit of the Bayesian optimization surrogate model in modified asphalt formulation design, this invention acquires initial small-sample data; constructs a clustering cloud model to obtain expectation, entropy estimates, and hyperentropy estimates; generates cloud droplet virtual samples using a forward cloud generator and merges them with the original samples to expand the dataset; trains a Gaussian process regression surrogate model based on the expanded data; constructs an expectation-improved acquisition function to optimize and solve candidate formulations; updates the data after physical testing verification; and iterates repeatedly until the termination condition is met to output the optimal formulation. This invention mines the distribution information of small-sample data through cloud droplet data augmentation, improves the accuracy and sampling efficiency of the surrogate model, significantly reduces the number of expensive physical tests, and lowers the cost of formulation design. It can be widely applied to the formulation optimization of modified asphalt and similar high-cost experimental materials.

This invention relates to the field of fluid machinery testing technology, and in particular to a performance testing system shared by circulating pumps and submersible pumps. The system includes a data acquisition and control unit, a drive unit, a load adjustment unit, and an intelligent control and analysis server, configured to perform: startup and intelligent identification, digital twin model construction and test planning, adaptive basic performance sampling, boundary performance exploration, real-time safety monitoring and prediction, synchronous acquisition of multi-source heterogeneous information, and digital profile generation and model training. Before physical testing begins, this invention pre-calculates key feature points under all operating conditions through numerical simulation. Based on these pre-calculated key points, the system can automatically generate a dynamic test sequence that balances safety and efficiency, enabling subsequent real-world testing to be targeted and precise, capturing the core performance framework of the pump with the fewest possible tests, greatly improving the scientific rigor and efficiency of the testing.

The invention relates to the technical field of aviation electrical system design and verification, and provides an aircraft power distribution system controller rapid prototype design method and system based on multi-level hardware-in-loop verification, and the method comprises the steps: S1, an architectural offline simulation stage: carrying out the preliminary function verification and parameter setting of a control logic through a unified simulation model; s2, in a distributed real-time simulation and code generation stage, real-time closed-loop verification and iterative optimization are carried out on control logic; and S3, a hardware replacement type rapid prototype verification stage: performing performance verification and final setting on the control strategy under a highly approximate real working condition. The method provided by the invention not only can greatly reduce the safety risk in the physical test, but also has the remarkable advantages of short development period, low verification cost and support of multi-level integrated verification, thereby providing reliable experimental data support for the subsequent physical verification of the aircraft power distribution system control strategy.

The invention discloses a macrostructure inspection method of a high-activity and high-purity rare earth metal gadolinium target material, and belongs to the technical field of physical testing. The method comprises the steps of processing a macroscopic sample, preparing a macroscopic corrosive agent, carrying out macroscopic corrosion and inspecting a macrostructure. Firstly, the surface of a gadolinium target macroscopic sample is machined; then performing low-power corrosion on the gadolinium target material sample; and finally, observing the macroscopic tissue of the sample by visual observation or a magnifying lens and collecting a macroscopic tissue image. The method has the advantages of no over-corrosion or non-uniform corrosion phenomenon, obvious grain boundary and clear structure, and is convenient for carrying out macroscopic structure uniformity observation and analyzing and identifying defects such as inclusion, looseness and air holes. The problems that due to intrinsic characteristics of high purity, active chemical properties and the like of the gadolinium target, during conventional low-power corrosion, corrosion pits, blackening and darkening of the surface, serious oxidation and other illusions are extremely prone to occurring are solved, and high-quality development of rare earth gadolinium target products used in the key strategic fields of integrated circuits, OLED display and the like is promoted.

The invention discloses a bed screen package and health test management method, device and equipment and a storage medium, and the method comprises the steps: collecting physical test data and subject physiological parameters of a bed screen, and constructing a test data set; performing index quantification on the test data set by using the test index to obtain an index quantification result; based on the test data set, performing multi-dimensional evaluation by using a multi-dimensional health evaluation model to obtain a multi-dimensional evaluation result; scoring and grading the bed screen according to an index quantification result and a multi-dimensional evaluation result; and generating an optimization strategy based on the scoring and grading results. According to the invention, by collecting the physical test data of the bed screen and the physiological parameters of the subject, various performance indexes of the bed screen can be accurately quantified, multi-dimensional health evaluation is carried out, and quantitative evaluation of the wrapping feeling and health of the bed screen is realized. The limitation of subjective experience and conventional mechanical performance testing is avoided, and a scientific and objective basis is provided for design and optimization of the bed screen.

The invention is suitable for the technical field of luggage design, and particularly relates to a luggage pull rod dynamic impact strength simulation design method, which comprises the following steps: ensuring the reliability of a design result by obtaining a structure attribute set, a historical attribute set and a design attribute set of a target design luggage; modeling simulation processing is carried out based on the structure attribute set and the historical attribute set, accurate recognition of the high strain energy density area and the geometric weak position of the pull rod is achieved, a feature response set containing the geometric information and mechanical response data of the weak area is obtained, and a clear target spot is pointed out for optimization design; according to the characteristic response set and the design attribute set, variable density lattice structure generation processing is carried out on the high strain energy density area, a traditional empirical design and repeated physical test mode is replaced, the research and development period is greatly shortened, the trial and error cost is reduced, the dynamic impact strength and structural stability of the luggage pull rod are improved, and the service life of the luggage pull rod is prolonged. And reliable technical support is provided for high-performance, light-weight and low-cost design of the luggage pull rod.

The full-aircraft ground vibration test method based on virtual-real fusion is suitable for the detection of the overall vibration performance of an aircraft, and comprises the following steps: determining an optimal initial excitation force which is determined by inputting a plurality of virtual results into an excitation vibration force vector model, the virtual result is determined according to a test model established by the test aircraft; and synchronously performing a virtual test and a real physical test on the basis of the optimal initial excitation force, obtaining a structural frequency spectrum and a result model of the real physical test, determining initial modals of each order of the aircraft according to the structural frequency spectrum, optimizing or correcting a dynamic simulation model through the initial modals of each order, and obtaining a dynamic simulation result of the aircraft. According to the method, a real dynamic simulation model is determined, the real dynamic simulation model is optimized or corrected according to a result model to obtain a final dynamic simulation model, and the final dynamic simulation model is stored, so that the test efficiency is improved.

A computer-implemented method includes generating a digital simulation model of an object, identifying portions of the object for physical prototyping based on confidence scores derived from the digital simulation model and creating a stereolithography (STL) model for the portions. Three-dimensional (3D) printing of the portions is performed based on the STL model. Physical testing is performed on 3D printed portions, and the digital simulation model is updated based on results of the physical testing.

The invention provides a wheel product heat treatment process parameter optimization method and system, and the method comprises the steps: taking the production parameters of wheels of different furnaces and corresponding equipment health vectors as features, taking the performances of the corresponding wheels as labels, and constructing sample data, the production parameters including a heating parameter, a cooling parameter and a tempering parameter; constructing a double-layer Bayesian network model, wherein the double-layer Bayesian network model comprises a first-layer Bayesian network model and a second Bayesian network model connected with the first-layer Bayesian network model; and inputting the target performance of the wheel and the current equipment feature vector into a double-layer Bayesian network model, wherein the double-layer Bayesian network model outputs multiple groups of prediction production parameters with high confidence. While multiple performance indexes such as hardness, static balance and residual stress are met, the number of physical tests is reduced, the process development period is shortened, and the production stability is guaranteed through uncertainty quantification and online self-learning.

The invention discloses a self-adaptive pipeline erosion test device, which belongs to the technical field of physical testing, and comprises a fixed support arranged in a plane, and a clamping linkage mechanism is arranged above the fixed support. The clamping linkage mechanism is composed of a lifting driving assembly arranged in the middle of the fixed support, a positioning clamp arranged on the fixed support in a sliding mode and a connecting rod connecting the lifting driving assembly and the positioning clamp, and an erosion medium circulating system matched with the lifting driving assembly is arranged on one side of the fixed support. The erosion medium circulating system is connected with a to-be-tested pipeline clamped on the positioning clamp; the self-adaptive pipeline erosion test device provided by the invention is simple in structure, high in rigidity and high in reliability, and can be widely applied to erosion performance tests of different pipe diameters and pipeline bending curvatures.

The application provides a transmission high-low temperature cycle endurance test method and system, which comprises the following steps: collecting basic parameters, key parameters and implicit parameters of the transmission at a physical layer through a dual-mode sensing unit, mapping a physical test state through a digital twin model at a virtual layer to generate a virtual sensing feature set, and corresponding integration into a dual-mode sensing feature tensor; calculating a dynamic adaptation degree between a test requirement feature matrix and the dual-mode sensing feature tensor in real time through a preset multi-field coupling feature discriminator, generating a three-dimensional composite feature map based on the dynamic adaptation degree; constructing a virtual-real linkage adaptive test framework according to the three-dimensional composite feature map; extracting target data from the dual-mode sensing data and the test requirement document and filling it into the corresponding analysis sub-column, synchronously passing through the coupling correlation path in the three-dimensional composite feature map to complete the corresponding endurance test. The application can comprehensively and accurately complete the endurance test, and the test efficiency is improved.

A kind of semi-physical test system and method of robot operating system application verification, including GPS transmitting module, state monitoring module, formation similarity calculation module, autonomous path planning module and effect evaluation module.Wherein, GPS transmitting module is used to generate and emit GPS signal in indoor environment simulation;State monitoring module is used to monitor the measured stress of each unmanned aerial vehicle;Formation similarity calculation module is used for each unmanned aerial vehicle to autonomously calculate the expected target position of itself in formation;Autonomous path planning module is used for each unmanned aerial vehicle to autonomously calculate the expected control acceleration of itself, and determine expected stress;Effect evaluation module is used to exclude the hardware failure of each unmanned aerial vehicle, and the function and performance of robot operating system are evaluated.The application can reduce the frequency of large-scale unmanned aerial vehicle to field test, reduce test cost.

The application provides a multi-target optimization method for material performance, and belongs to the technical field of material science and artificial intelligence. The method process provided by the application takes a small sample learning model as a core, combines an active learning optimization strategy, and realizes quantitative optimization of multi-target performance indexes in material research and development in an extreme service environment. The method fully utilizes limited test data for learning, significantly reduces the number of physical tests, improves the efficiency and success rate of searching for a material design scheme meeting multi-target performance requirements through intelligent optimization search, and has important significance for accelerating development of new materials in harsh environments.