477 results about "Rapid assessment" patented technology

The invention relates to the technical field of urban climatic science, in particular to an urban climatic environment rapid evaluation system and method. According to the technical scheme, the system comprises a data acquisition module, an index standardization and feature extraction module, an index weighting and dynamic parameter adjustment module and a climatic environment comprehensive index generation module. According to the method, based on meteorological and environmental multi-source data of an urban area, a multi-dimensional evaluation index set is firstly constructed through standardization and normalization processing, and then a fuzzy logic harmonic function and a non-linear harmonic function are utilized to identify the coupling relation and the cooperation strength among the indexes; and meanwhile, a dynamic optimization mechanism is introduced to adaptively adjust each weight coefficient according to the real-time index sensitivity, an urban climate environment index is finally generated, and spatial visual expression and grade early warning are realized. According to the method, rapid evaluation and trend judgment of the urban climate system state can be realized, and the method is suitable for urban planning, climate risk monitoring and toughness analysis.

The present application proposes a method and system for quantitative derivation of an on-line evaluation layered model for evaluating concrete dam operation performance, and a storage medium, and relates to the technical field of dam operation safety monitoring and management. A logic architecture of quantitative derivation of the concrete dam operation performance mainly has two aspects, a longitudinal dimension and a transverse dimension. The longitudinal dimension is the principal line of assessing longitudinal evaluation of the on-line evaluation layered model, and an analysis idea of the concrete dam from local to global and from details to whole is objectively reflected from six levels of monitoring data, diagnosis methods, monitored items, evaluation indicators, key parts and an overall project. The transverse dimension is an element set for evaluating the concrete dam operation performance, comparison of importance degrees of various assessment elements at the same level is conducted, and at the same time, an association relationship between the elements at the same level is established. Therefore, by means of comparison of the elements in the transverse dimension and recursion of the various levels in the longitudinal dimension, the overall concrete dam operation performance is automatically and rapidly evaluated, and grading results of an operation state of a concrete dam are given through a safety assessment set, such that safety evaluation of the concrete dam operation performance is more systematic and comprehensive in analysis method and engineering part, and more explicit and reliable in derivation logic and evaluation efficiency.

The invention discloses a bridge network anti-seismic performance rapid evaluation method based on capability spectrum analysis. The method comprises the following steps: firstly, carrying out finite element modeling on bridges in a regional bridge network needing to be analyzed by using OpenSees, extracting piers, and carrying out vulnerability analysis on the piers; a bridge vulnerability curve is obtained based on a capacity spectrum method, then the failure probability of the bridge in a certain damage state serves as a post-earthquake damage index, and the bridge failure probability is replaced by the post-earthquake failure probability of the corresponding road section; after the post-earthquake failure probability of each road section exists, all paths between a starting point and an ending point, namely, to-be-researched OD pairs in a network area are analyzed, the passing probability of each path after the earthquake is calculated based on the Bayesian theorem and an event independence calculation method, all the paths under the OD pairs are sorted according to the passing probability, and therefore the optimal passing path is obtained; and the path with small passing probability is avoided. According to the invention, a scientific basis is provided for regional bridge network anti-seismic planning and emergency management.

The invention discloses an aquatic organism diversity rapid evaluation system and method based on GIS and eDNA technologies, and the method comprises the steps: selecting a plurality of sampling points in a target region to collect water samples, and integrating and processing the geographic information data of the sampling points and surrounding regions by adopting a GIS system; extracting eDNA from the collected water sample, performing amplification and sequencing on the eDNA by adopting a high-throughput sequencing technology, obtaining species and relative abundance of the species existing at the sampling point, and forming a species list; importing species distribution information corresponding to the species list into a GIS system, and obtaining a species distribution area and species types; according to the method, a species distribution prediction model is established, aquatic organism diversity change trends of the hot spot area and the potential ecological threat area are monitored in real time, an evaluation report and protection suggestions are formed, and protection measures are updated in time, so that the data acquisition and processing efficiency is improved, and the accuracy of species identification and the comprehensiveness of diversity evaluation are enhanced; and a real-time monitoring and early warning mechanism is provided.

The invention relates to the technical field of bridge structure health monitoring, and particularly provides a bridge earthquake damage rapid assessment method and system, and the method comprises the steps: carrying out the cross-modal coupling calibration of a time-history sudden change feature and a phase of a space energy spectrum, and generating a high-confidence three-dimensional dynamic response field; inputting the spatial gradient distribution characteristics into a nonlinear material state inversion program, performing path integrity verification in combination with an energy dissipation path, and outputting a potential damage topology boundary of the bridge; dividing an output bridge potential damage topological boundary into discretized damage units, and mapping strain constraints of the discretized damage units into triple decision-making indexes including a traffic capacity attenuation coefficient, an emergency disposal aging threshold value and an aftershock risk level through a bridge structure function attenuation rule. The system comprises a mixed field dynamic response reconstruction module, a damage sensitive domain reverse locking module and a function level damage quantitative mapping module. According to the method, deterministic mapping of the bridge structure damage state and the engineering function index is realized.

The invention relates to the technical field of bridge earthquake damage performance evaluation, and particularly discloses a high-speed railway bridge earthquake damage performance rapid evaluation method based on machine learning, and the method comprises the steps: collecting multi-source data of a bridge structure of a high-speed railway, a historical earthquake database and a BIM model of the bridge structure in real time through a heterogeneous data collection system; constructing a multi-modal feature space containing partial features of time-frequency domain features, spatial features and probability features; constructing a hierarchical machine learning framework based on a dynamic Bayesian network damage propagation model, a mixed model of a multi-scale convolutional neural network and a long-short term memory network and an uncertainty quantization and dynamic updating mechanism, and establishing an earthquake damage performance evaluation model based on the hierarchical machine learning framework; carrying out seismic damage performance evaluation on the multi-modal feature space by adopting a seismic damage performance evaluation model, and generating damage probability distribution; potential earthquake damage related information behind the data is effectively mined, and the earthquake damage condition of the bridge in an earthquake can be more accurately simulated and predicted.

The invention discloses a multi-modal data driven commercial vehicle frame performance prediction method and system. The method comprises the following steps: uniformly coding design variables of a frame; constructing a multi-modal performance response data set based on finite element simulation and test results of mass production vehicle models, and realizing fusion of simulation and test data by adopting a maximum mean difference and related alignment algorithm; constructing a graph perception Transform multi-task prediction model fusing the structure topology and the physical position features, and predicting key performance indexes of the frame under a plurality of typical working conditions; through weighted multi-task loss function joint training, an uncertainty mechanism is introduced to dynamically adjust task weights; and after training is completed, deploying to an inference engine to realize second-level prediction and support increment fine adjustment updating. According to the method, repeated modeling and solving processes are avoided, the frame performance prediction efficiency and the adaptive capacity are remarkably improved, and the method is suitable for rapid evaluation of the frame performance of commercial vehicles of various structural configurations and material types.

Disclosed in the present invention is an anti-seismic simulation method for an existing building by considering a real damage state. The method comprises: determining a quantified component damage index on the basis of an observed component damage state; determining a material damage index of a damaged component on the basis of the component damage index; determining key parameters of a constitutive law for a damaged material on the basis of the material damage index; establishing a finite element model of a damaged building on the basis of the constitutive law for the material of the damaged component; and assessing the seismic risk and anti-seismic performance of the damaged building on the basis of the finite element model. In the present invention, a constitutive law for a damaged material is incorporated into a fiber model in OpenSEES, so that rapid modeling of a damaged building can be realized, thereby effectively reproducing the real damage of an existing building; and by using a seismic vulnerability analysis method, rapid assessment of the seismic risk and anti-seismic capability of the existing building can be realized, thereby further providing support for formulating reasonable reinforcement and reconstruction strategies by related departments.

The invention discloses a hydrogen leakage accident holographic perception and disaster situation dynamic prediction system in a tunnel scene, and belongs to the technical field of hydrogen energy traffic safety and intelligent risk management. According to the system, multi-modal information such as environmental parameters, hydrogen concentration, heat source temperature, leakage acoustic characteristics and vehicle states is collected in real time through a multi-modal sensing unit; abnormal detection, time synchronization and space registration are carried out through the information fusion module to generate fusion data in a unified format; the hazard source analysis module locates a leakage source, estimates a leakage rate, locates an ignition source and extracts disaster characteristics based on the fused data; the disaster dynamic prediction module predicts spatio-temporal evolution of diffusion, combustion and explosion by using an agent model and calculates disaster levels; the feedback early warning unit synchronously outputs the prediction information to the tunnel monitoring platform and issues early warning information; and the data storage and self-optimization module uniformly stores historical data and optimizes the prediction model through incremental learning. The system realizes real-time monitoring, rapid evaluation and intelligent disposal of tunnel hydrogen leakage accidents.

The invention relates to a battery self-discharge characteristic analysis and rapid evaluation method, and aims to improve the precision and efficiency of battery self-discharge performance detection. According to the method, in a set environment stable interval, an instantaneous voltage change sequence and a current perturbation response sequence of a target battery are acquired through micro-load disturbance, and a battery internal resistance dynamic evolution tensor representing dynamic response characteristics in the battery is constructed; extracting local features by applying a multi-scale time window segmentation strategy, forming a feature vector group containing a voltage nonlinear rebound factor and a delay response index, inputting the feature vector group into a trained Bayesian weighted adaptive mapping network, and outputting a battery self-discharge rate estimated value combining a manufacturing batch residual error and temperature offset compensation; performing trend fitting and consistency checking on the estimated value to obtain a battery self-discharge grade evaluation result, and generating a structured detection report containing initial offset, rebound amplitude and estimation confidence; the method can be widely applied to battery production, quality control and performance screening scenes.

The invention discloses a multi-dimensional rapid evaluation method for snow-melting agent corrosion resistance of stainless steel, and relates to the technical field of stainless steel performance evaluation.The multi-dimensional rapid evaluation method comprises the steps that sodium chloride, calcium chloride and magnesium chloride are weighed by mass and dissolved in deionized water, acetic acid and sodium hydrogen sulfite are added after dissolution, and the pH value is adjusted to 4-6; performing potentiodynamic polarization scanning and electrochemical impedance spectroscopy testing on the stainless steel sample to obtain pitting potential and impedance modulus; the method comprises the following steps: placing a stainless steel sample in a cyclic corrosion experiment box, carrying out a corrosion experiment under the conditions of controlling the cyclic temperature change of an environment temperature and periodically carrying out cyclic switching of a spraying mode, a humid mode and a drying mode, taking out the sample every set time, and measuring the corrosion rate and the maximum pitting depth; and according to the pitting potential, the impedance modulus, the corrosion rate and the maximum pitting depth, carrying out graded judgment on the corrosion resistance of the stainless steel. According to the method, the corrosion resistance of the stainless steel can be accurately evaluated in a short time.

The invention relates to a quick mountain torrent disaster risk assessment method and system based on multi-source data fusion. The method comprises the following steps: performing space-time registration on multi-source data, constructing a dynamic factor matrix and a static geological parameter matrix, and calculating soil saturation; on the basis of the dynamic factor matrix, removing redundant factors, analyzing and generating a weight vector through an entropy method, on the basis of the effective factor set, the static geological parameter matrix and the soil saturation, correcting the rock-soil shear strength by quantifying the sediment deposition effect, obtaining the corrected rock-soil shear strength, and calculating the slope safety coefficient; and according to the coefficient, the effective factor set and the weight vector, generating a risk membership degree vector through fuzzy evaluation, calculating a risk feature value, identifying a disaster dominant type, and constructing a risk map. According to the method, through multi-source data space-time registration, redundant factor elimination, sediment deposition effect quantitative correction and the like, the efficiency and precision of mountain torrent disaster risk assessment are improved, and the support of an assessment result on disaster prevention and reduction decisions is enhanced.

The invention discloses a method for rapidly evaluating the safety of a structure after a bridge fire, and the method comprises the steps: obtaining an air temperature, flue gas speed distribution, air pressure distribution and a flame flue gas image through simulating a fire scene; the method comprises the following steps: when simulating that a fire enters a fire quasi-steady-state stage, obtaining a fire smoke image for completely describing a dynamic change process of thermal plume and a smoke speed distribution image and an air pressure distribution image above a fire source, and forming a training sample; constructing a long and short term memory network model; training the model; shooting a flame smoke image of a fire scene, inputting the flame smoke image into the trained long-short term memory network model, and outputting a smoke speed distribution image; calculating a final fire source heat release rate according to the flame smoke image and the smoke speed distribution image; the average temperature of the components in the cable at different moments is calculated; according to the average temperature of the components in the cable at different moments, whether the structural components lose efficacy or not is judged. According to the invention, the monitoring accuracy and timeliness are improved.

The invention relates to the technical field of remote sensing image recognition, in particular to a method for determining a moso bamboo forest snow disaster affected area based on a GEE platform. The method mainly solves the problems of low efficiency, high cost and difficulty in realizing large-range rapid evaluation caused by dependence on manual field investigation in the prior art. According to the technical scheme, the method comprises the following steps: firstly, obtaining a multi-temporal Sentinel-2 image before and after a snow disaster, and carrying out the preprocessing of the multi-temporal Sentinel-2 image; extracting spectral bands, vegetation indexes and texture features to form an initial feature set; then, a key feature variable combination is determined through statistical significance filtering and machine learning optimization; on this basis, establishing a logistic regression discrimination model and determining an optimal classification threshold; and finally, carrying out snow disaster state classification on the moso bamboo forest region by utilizing the trained model, and generating a disaster region spatial distribution diagram.

The invention discloses an unsupervised unmanned aerial vehicle air combat situation assessment method based on a double attention mechanism and a BiGRU, and belongs to the technical field of crossing of machine learning and modern military. The method comprises the following steps: firstly, designing a clustering method, providing a parameter adaptive density grid clustering method based on a fuzzy theory to process a large-scale target, and establishing an air combat information sample set with time and tactical meanings to facilitate subsequent rapid evaluation; on the basis, an encoder-decoder structure taking BiGRU as a trunk is designed to extract depth information of a historical state and a subsequent flight state of a target in two directions, and a double attention mechanism suitable for time sequence data is improved, so that the model can better pay attention to key parts and key features of an input sequence. According to the method, the generalization ability and the practical application value of an air combat situation evaluation model can be improved, the processing ability and the evaluation precision of situation data are improved, the influence of irrelevant parts in high-dimensional and long-sequence time data on an evaluation result is reduced, and the modern air combat requirement is met.

The invention relates to the field of bridge damage rapid assessment, in particular to a bridge damage rapid assessment method based on residual displacement, which comprises the following steps: determining the section structure and stress condition of a pier; calculating the yield curvature and the limit curvature of the damaged section; according to the yield curvature and the limit curvature, respectively calculating the maximum displacement of the pier top when the damaged section yields and is damaged; building a pier column fiber unit model or a finite element model, applying forces corresponding to the maximum displacement of the pier top when the damaged section is yielded and damaged to the pier top, and then unloading to obtain the residual displacement when the damaged section is yielded and damaged; and the post-disaster bridge pier top residual displacement is measured on site and compared and evaluated. According to the method, the relation between the residual displacement and the section damage degree is established, the bridge damage rapid assessment method is provided, compared with an investigation comprehensive assessment method, the method is more objective, compared with a load test assessment method, the method is more economical, compared with a traditional structure analysis and calculation assessment method, complex initial defects do not need to be established, and calculation is simpler and more convenient.

The present invention belongs to the field of dimension measurement technology, and specifically relates to a method, system, device, and medium for evaluating the uncertainty of a large-scale multilateral coordinate measurement system. The method inputs the acquired target point coordinates into an error transfer model to obtain three coordinate uncertainty components corresponding to the coordinate values. This uncertainty coefficient is then calculated based on the uncertainty introduced by the offset of the reflector's optical center, and the uncertainty evaluation is performed. The present invention, based on the fundamental principles of the multilateral coordinate measurement system, simplifies the system coordinate system to reduce parameters, thereby reducing the amount of calculations. The method also provides a specific mathematical formula, which facilitates rapid evaluation at the measurement site and is easy for metrologists to learn and apply.

The invention belongs to the field of electrical engineering, and relates to a dry-type transformer capacity rapid assessment method and system based on a two-section short-time small current, and the method comprises the steps: inputting a first section of small current I1 to a winding of a transformer, and collecting the winding temperature data T (t) 1 of the first section until a steady state is reached; under the condition that the power supply is not interrupted, the current is directly increased to a second section of small current I2, and the winding temperature data T (t) 2 of the second section is continuously collected until the stable state is reached again; fitting the winding temperature data T (t) 1 and T (t) 2, and outputting an index model and index model parameters; inputting the index model parameters into a power function model related to the load rate, and outputting power function model parameters; setting the load rate to be 100%, and calculating to obtain a temperature rise stable value and a time constant under the 100% rated current Ie of the transformer; and based on the GB / T1094.12 standard, comparing the average temperature rise of the winding with the maximum allowable temperature rise value, and evaluating the actual capacity and bearing capacity of the transformer. The device has the effects of saving energy, reducing consumption and improving efficiency.

The invention discloses a bridge pile group system earthquake damage rapid assessment method fusing Hilbert-Huang transformation and physical prior, belongs to the technical field of civil engineering and building earthquake resistance, and aims at solving the problems that a traditional method is lagged, physically unreasonable and limited in local monitoring. The method comprises the following steps: S1, model training and embedding: before an earthquake, constructing a deep learning model, and embedding a pile-soil vibration control equation and boundary conditions in the model as loss function constraint terms; s2, establishing a damage mapping relation: before an earthquake, establishing a quantitative mapping relation between a frequency domain index representing the overall dynamic characteristics of the system and an engineering demand parameter representing the local plastic damage degree; and S3, post-earthquake real-time evaluation: determining the overall damage degree and damage position of the structure according to the extracted frequency domain index difference on the basis of the established quantitative mapping relation during an earthquake.

The invention relates to the technical field of power system risk assessment, in particular to a frequency safety assessment method, device and equipment considering source load uncertainty and a medium, and the method comprises the steps: generating a source load scene at a future moment in a rolling manner based on source load data at a plurality of historical moments before the future moment, obtaining an uncertain operation scene set in combination with future plan information; establishing a time-phased frequency safety evaluation model before the day, evaluating the frequency safety under the uncertain operation scene set, and updating the time-phased frequency safety evaluation model based on a source load scene under the future moment of rolling refreshing; a risk analysis method is introduced, a frequency deviation out-of-limit risk is calculated based on an uncertain scene evaluation result, a safety risk threshold value is set, and a frequency safety dynamic risk threshold value represented by the central moment of each order of the uncertain quantity of the source load is defined through the relation between the safety risk threshold value and the uncertain quantity of the source load in different time periods. According to the method, the frequency safety in a large number of uncertain scenes can be quickly evaluated.

The invention relates to a green prickleyash quality evaluation system and method based on image recognition, and belongs to the technical field of image data recognition processing. The method comprises the following steps: collecting a green prickleyash image, recognizing a shape contour after preprocessing, comparing the shape contour with a standard contour to judge the existence of green prickleyash, and counting; the method comprises the following steps: calculating the area, grading and solving the uniformity by using a curvature-based segmentation method and a shoelace formula, then constructing a characteristic spectrum according to the shape, obtaining spectral characteristics through hyperspectral imaging, extracting texture characteristics by combining multiple algorithms, establishing a growth stage database and associating stages, and constructing a sequence spectrum by using a dynamic time warping algorithm during multiple times of acquisition; the invention discloses a method for evaluating the quality of green prickleyash, which comprises the following steps of: weighting the characteristics of a characteristic spectrum by adopting an analytic hierarchy process, calculating a quality comprehensive score and evaluating the quality of the green prickleyash according to a score threshold value, and aims at solving the problems of poor accuracy and incapability of meeting large-scale rapid evaluation requirements in a traditional green prickleyash quality evaluation mode.

The invention discloses an animal abnormal behavior phenotype rapid evaluation method and device, and is applied to the technical field of animal behavior analysis, and the method comprises the steps: obtaining video data of animals of different weeks old in spontaneous behavior experiments; tracking animal body key points in the video data to obtain animal behavior characteristics; performing classification extraction on the basis of the behavior characteristics to obtain target behavior parameters, and calculating the target behavior parameters to obtain indexes for evaluating animal behavior states; analyzing the difference change of the indexes, and evaluating and classifying the behavior state of the animal; by analyzing the dynamic balance relationship between the exploration behavior and the engraving behavior, the accurate classification of the animal abnormal behavior state is improved.

The invention relates to the technical field of accelerator radiation protection, in particular to an induced radioactivity assessment method suitable for a mobile accelerator component. Monte Carlo simulation software is adopted to calculate radionuclide activity concentrations in different areas of an acceleration component before movement, then radionuclides serve as radiation source items, and three-dimensional space dose rate distribution of the component and the periphery when the position of the accelerator component changes is obtained through calculation. And rapid evaluation of the received dose of the staff during maintenance and rapid formulation of a maintenance scheme are realized. The method effectively promotes the application of the Monte Carlo method in the field of radiation protection of the accelerator, provides reference for radiation hazards to workers, and provides technical support for radiation protection and operation maintenance of the accelerator.

The invention discloses an epoxy resin aging diagnosis method based on electric frequency and optical frequency combined characteristics, and belongs to the technical field of electrical equipment insulation aging assessment. The sum of products of frequency under electric frequency and a dielectric loss angle tangent value and the sum of products of frequency under optical frequency and the dielectric loss angle tangent value are used as characteristic values; the method comprises the following steps: fitting with equivalent breakdown field strength, constructing a quantitative characterization relationship between the equivalent breakdown field strength of an epoxy resin sample and an electric frequency-optical frequency dielectric loss angle tangent value, and evaluating the actual aging degree of the epoxy resin insulating material by calculating the decline rate of the equivalent breakdown field strength, thereby avoiding a large number of repeated breakdown experiments. The aging degree of the epoxy resin insulating material can be accurately and quickly evaluated; the function relationship between the breakdown field strength of the epoxy resin material and the electric frequency-optical frequency dielectric parameters is constructed from two directions, the evaluation index suitable for the aging degree of the whole period is established, and theoretical support is provided for accurate and rapid evaluation of the aging degree of the epoxy resin insulating material.

The present application provides a method, device, equipment, and medium for evaluating the damage of a power grid under compound chain disasters. The method includes: establishing a physical model of the power grid; establishing an evolution model of compound chain disasters based on a Bayesian network according to sensor data, meteorological data, geographic information data, and historical disaster data; fusing historical ground motion records and the physical model of the power grid to evaluate the probability of power grid damage caused by a single disaster; based on the Copula function and the evolution model of compound chain disasters, evaluating the joint damage probability of the power grid caused by compound disasters; evaluating the difference between the probability of power grid damage caused by a single disaster and the sum of the joint damage probabilities of the power grid caused by compound disasters under compound chain disasters. The method provided by the present application evaluates the damage of the power grid under compound chain disasters through the probability of power grid damage caused by a single disaster and the joint damage probability of the power grid caused by compound disasters, achieving accurate and rapid evaluation of the damage of the power grid under compound chain disasters.

The invention belongs to the technical field of high voltage and insulation, and relates to an XLPE breakdown field strength evaluation method and system based on gel content and preparation process, and the method comprises the following steps: S1, sampling, weighing, shearing and bagging; s2, extracting, weighing and calculating the gel content; s3, constructing an evaluation model; s4, predicting the breakdown field intensity; according to the technical scheme, the physical model fusing the cross-linking enhancement effect and the thermal damage effect is constructed, the breakdown field strength is predicted based on the physical model, accurate and rapid evaluation of the XLPE insulation performance under different process conditions can be achieved only through a small amount of breakdown test data calibration model, dependence on a traditional destructive electrical test is remarkably reduced, and the reliability of the XLPE insulation performance is improved. The test cost is greatly reduced, the research and development period is greatly shortened, and an effective tool is provided for cable insulation material performance analysis and production process optimization.

The present invention relates to the technical field of bridge earthquake damage performance assessment, and specifically discloses a method for rapid earthquake damage performance assessment of high-speed railway bridges based on machine learning, comprising: real-time acquisition of multi-source data of high-speed railway bridge structures, historical earthquake databases, and BIM models of bridge structures through a heterogeneous data acquisition system; construction of a multimodal feature space comprising partial features including time-frequency domain features, spatial features, and probabilistic features; construction of a hierarchical machine learning architecture based on a dynamic Bayesian network damage propagation model, a hybrid model of a multi-scale convolutional neural network and a long short-term memory network, and an uncertainty quantification and dynamic update mechanism; and establishment of an earthquake damage performance assessment model based on the hierarchical machine learning architecture; use of the earthquake damage performance assessment model to perform earthquake damage performance assessment on the multimodal feature space and generate a damage probability distribution; and effective mining of potential earthquake damage-related information behind the data to more accurately simulate and predict earthquake damage to bridges.

The invention belongs to the technical field of intelligent manufacturing and digital twinning, and discloses a machine tool spindle angular contact ball bearing stress field digital twinning modeling method based on a graph neural network, and the method comprises the steps: firstly building a finite element analysis model, and generating a multi-working-condition stress sample set; secondly, a mixed graph structure is constructed based on the grid topology and the surface k neighbor relation, and node geometric features and region labels are generated; then stress field shape-amplitude decoupling is implemented, and a stress field is decomposed into a normalized shape field and an amplitude scalar; constructing and training a dual-branch architecture shape prediction map neural network model and an amplitude regression model again, wherein a key area mask and a continuous weight are introduced into the shape model to enhance the prediction precision of the contact area; and finally, quickly predicting an amplitude and a shape field by using the model, and reconstructing full-field stress distribution. According to the method, the prediction efficiency and the prediction accuracy of a high-stress area are remarkably improved while finite element-level geometric accuracy is kept, and the method is suitable for rapid evaluation and digital twinning application of the machine tool spindle bearing.

The invention belongs to the field of infectious disease community transmission multi-subject simulation, and relates to an infectious disease community transmission multi-subject simulation method and system containing asymptomatic infectors. The method comprises the following steps: establishing a virtual community group which comprises a plurality of communities and a plurality of destinations; distinguishing subjects in the virtual community group by using the health state and the space state, wherein the subjects comprise a susceptible subject S, an exposed subject E, an asymptomatic infection subject A, an infection subject I and a rehabilitation subject R; a motion sequence of all subjects in the virtual community group is established, the infectious disease transmission process is simulated according to the motion sequence, and the motion sequence comprises movement, infection and state updating, infection detection and isolation and community sealing control; and obtaining a simulation result, and evaluating the effectiveness of the infectious disease prevention and control policy. According to the method, rapid evaluation of different prevention and control strategies on infectious disease transmission conditions, social and economic influences caused by infectious diseases and the like can be realized, and beneficial reference is provided for a macroscopic regulation and control policy for restraining infectious diseases.

The invention provides a method suitable for rapidly evaluating the aging state of a large-scale energy storage power station battery, and belongs to the technical field of battery state evaluation. According to the method, data acquisition is carried out during battery standing, two subsequent interval voltages of standing initial voltage are recorded, equivalent capacity loss instantaneous values at different moments are calculated in combination with a calibration proportionality coefficient and a working condition correction factor, a voltage relaxation integral area is obtained through calculation, and then a health state assessment result and confidence are obtained; the technical means of synchronously collecting the temperature change rate and the internal resistance change value, dynamically allocating weight fusion calculation, and performing evaluation in parallel in the whole station to generate an aging state distribution diagram and an abnormal alarm are adopted, and the method is adaptive to an existing energy storage power station monitoring system, does not need additional transformation, avoids voltage fluctuation to obtain high-quality data, comprehensively represents the battery polarization state, and improves the quality of the battery. The problems that large-scale energy storage power station battery evaluation is low in efficiency, insufficient in precision and lack of a global view angle are solved.