57 results about "Impact model" patented technology

The invention provides a lithium battery degradation threshold-impact model construction method and device, equipment and a storage medium. Relates to the field of lithium battery life prediction. The method comprises the following steps: establishing an inherent degradation model of the lithium battery by adopting a nonlinear Wiener process, and describing nonlinear characteristics of capacity fading; constructing an external impact damage model based on a non-homogeneous Possion process, and representing time-varying characteristics of random impact; coupling a degradation process and impact damage through a dual-threshold failure mechanism, and defining a capacity attenuation soft failure threshold and an impact accumulation hard failure threshold; the degradation parameters and the impact parameters are corrected in a dynamic linkage mode through a Bayesian updating and optimizing algorithm; and realizing probability distribution prediction of the residual life based on Monte Carlo simulation. The method can improve the prediction precision and engineering applicability of the residual life of the lithium battery under complex working conditions.

The invention provides a robot training method and system, electronic equipment and a storage medium. The training method comprises the following steps: constructing a training scene according to simulation environment configuration parameters and based on an implicit rendering equation and a contact impact model; the simulation environment configuration parameters comprise robot model parameters, scene asset parameters and physical parameters; and controlling the robot to execute a training task based on a near-end strategy optimization algorithm in the training scene. According to the method, the high-precision simulation scene is constructed through the implicit rendering equation and the contact impact model, the scene construction efficiency is remarkably improved, and manual intervention is reduced; the robot is driven to execute the training task based on the near-end strategy optimization algorithm, rapid adaptation of the strategy model to complex physical interaction is achieved, and compared with a traditional fixed trajectory planning scheme, the task success rate is increased, and the hardware development cost is reduced; the core pain points of low scene construction efficiency, insufficient physical simulation and weak strategy generalization ability in traditional robot training are comprehensively solved.

A method of evaluating impact of a change on nodes of a network, including collecting information of changes to configuration items of the network with a change management module that is executed on a computer of the network and forming a list of changes, receiving a dependency graph that defines dependencies between nodes of the network, receiving an impact model that includes an impact value that provides an indication of a risk value for different types of changes to nodes of the dependencies, executing an impact score generation module configured to receive the dependency graph, the impact model and the list of changes to determine a risk value responsive to a specific change to a node of the network and an impact of the change on other nodes of the network, repairing or predicting problems in the network based on the determined risk value for each change.

The invention belongs to the technical field of abnormal behavior analysis, and particularly discloses a security and protection monitoring abnormal behavior recognition method based on artificial intelligence, and the method comprises the steps: firstly collecting construction videos and natural environment data, and obtaining construction environment data through a construction management system; identifying personnel and security configuration features by using a machine vision technology, and performing statistics on environmental feature indexes through data mining and performing multi-modal fusion; then building an environment influence and process interlacing influence model, and outputting corresponding influence factors; according to an output result, an abnormal evaluation triggering index is defined, and an abnormal behavior recognition model is built for judgment; and finally, matching a judgment result with an early warning triggering mechanism and performing early warning. According to the invention, the construction site can be monitored in an omnibearing and multi-dimensional manner, and influence factors in multiple aspects are integrated. Meanwhile, by means of model building and analysis, a scientific basis is provided for judgment of abnormal behaviors. And timely and effective early warning can be realized.

A model predictive maintenance (MPM) system for building equipment includes one or more processing circuits having one or more processors and memory. The memory store instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including estimating a degradation state of the building equipment, using a degradation impact model to predict an amount of one or more input resources consumed by the building equipment to produce one or more output resources based on the degradation state of the building equipment, generating a maintenance schedule for the building equipment based on the amount of the one or more input resources predicted by the degradation impact model, and initiating a maintenance activity for the building equipment in accordance with the maintenance schedule.

The invention discloses a wind power plant wide area safety risk early warning method, device and equipment, a medium and a program product, and the method comprises the steps: carrying out the data monitoring of a wind power plant through a space-air-ground data monitoring module, obtaining multi-source heterogeneous monitoring data, carrying out the fault feature correlation analysis of the multi-source heterogeneous monitoring data, and carrying out the fault feature correlation analysis of the multi-source heterogeneous monitoring data; obtaining a historical fault event set and characteristic factors and fault results corresponding to the historical fault events, constructing a fault data matrix according to the historical fault event set and the characteristic factors and fault results corresponding to the historical fault events, and constructing a dynamic time sequence reliability influence model of the wind power plant, risk prediction is carried out through a dynamic time sequence reliability influence model, a risk distribution structure chart is generated based on a risk prediction result, and the risk prediction result comprises a time node and a distribution area of reliability reduction of a wind power plant, so that a time sequence coupling relationship among multiple factors in a complex system is effectively captured, and the accuracy and timeliness of risk prediction are ensured.

The application provides a flood risk prediction method and system considering index and weight uncertainty, and belongs to the technical field of risk analysis, and specifically comprises the following steps: determining the weight coefficients of flood monitoring indexes corresponding to different combinations based on the flood monitoring indexes of historical flood processes in different combinations, determining stable monitoring indexes based on the analysis results of the weight coefficients, determining the construction strategy of the influence model of the flood monitoring indexes based on the variation of the weight coefficients of the flood monitoring indexes between different combinations and based on the stable monitoring index data, and determining a flood risk prediction analysis method according to the influence model and the rainfall data of the rainfall process before the current rainfall process, so that the accuracy of flood risk prediction processing is improved.

This invention relates to the field of intelligent control technology for industrial robots, and discloses a precise compliant force control method for a grinding and polishing robot under uncertain environmental conditions. The method includes establishing a dual-closed-loop control model of the environment and the robotic arm based on a set linear environment model and a robotic arm dynamics model; iteratively solving for the optimal control gain in a data-driven manner based on adaptive dynamic programming for the unknown environmental characteristics in the control model; designing a free-space control gain to achieve stable relative motion approaching the environment; designing a smooth transition mechanism for the free-contact space control gain; achieving model-free optimal control based on data iteration through adaptive dynamic programming; employing dual-closed-loop impedance control to achieve the impedance effect of the force; and utilizing contact transient impact modeling to dynamically adjust the control gain, ensuring the stability of the contact force and processing quality, making it suitable for various complex working environments.

The present application discloses a PLC-based wind turbine generator control system and method, the system comprising: an acquisition module, used to set a plurality of monitoring points, acquire real-time monitoring data of each monitoring point, and generate an operation evaluation value of each monitoring point; a generation module, used to generate a first control strategy according to the operation evaluation value of each monitoring point and a preset control model of a device associated with each monitoring point; a determination module, used to construct an influence model according to the influence relationship between the monitoring points, integrate the first control strategies of the devices involved in the corresponding monitoring points according to the influence model, and determine the comprehensive control strategy of the wind turbine generator; a control module, used to perform control simulation on the comprehensive control strategy, generate an application evaluation value of the comprehensive control strategy according to the virtual monitoring data of each monitoring point after simulation, and judge whether to generate a correction instruction for the comprehensive control strategy according to the application evaluation value, thereby greatly improving the control efficiency of the wind turbine generator control system.

The invention discloses a transaction decision-making method for a rubber wood cross-border trade supply chain, and the method comprises the steps: obtaining rubber wood transaction decision-making features through fusing a price fluctuation coefficient, a weather influence factor and a risk income balance point, and constructing a model through employing the transaction decision-making features and the transaction decision-making method, the model processes the to-be-transacted decision-making features of the rubber wood to obtain an instant transaction decision-making method so as to realize accurate matching of suppliers. The method is based on historical price and market supply and demand data, utilizes an LSTM model to predict a price fluctuation coefficient, integrates sea transportation cost, tax fluctuation, inventory turnover rate and supplier credit risk through Monte Carlo simulation, processes to obtain a risk income balance value, and utilizes a weather and production influence model to process an obtained weather influence factor to obtain a risk income balance value. And finally, the fusion features are processed based on a collaborative filtering algorithm of improved machine learning to match high-quality suppliers in the supply library, and the risk of manual decision making is reduced and the accuracy of model decision making is improved by using objective data influencing decision making.

The invention provides a water jet water column impact pressure intensity determination method. The method comprises the following steps: S1, constructing a water jet water column impact model; s2, the stress area of the impact force sensor is determined, and jet flow parameters are set; s3, a nozzle is controlled to output water jet to the impact force sensor according to the set jet flow parameters, and the current impact force value output by the impact force sensor is obtained; s4, determining the water jet impact pressure according to the impact force value and the stress area of the impact force sensor, and substituting the impact pressure into the water jet water column impact model to determine the coefficient of the water jet water column impact model; s5, determining flushing parameters of the to-be-flushed equipment, and substituting the flushing parameters into the water jet water column impact model to determine the impact pressure intensity of the water jet water column received by the to-be-flushed equipment, through the method, the flushing effect is ensured, meanwhile, no additional damage is caused to the to-be-flushed equipment, no additional test needs to be carried out on the to-be-flushed equipment on site, and the cost is reduced. And the efficiency is ensured.

The present invention belongs to the technical field of mission environment effectiveness evaluation, and particularly relates to a task-oriented multi-dimensional effectiveness evaluation method, which constructs an effectiveness evaluation framework for multi-dimensional indicators of a mission under the influence of the environment. The effectiveness evaluation framework is implemented based on a task-oriented spatio-temporal comprehensive environment impact model. Among them, the comprehensive environment impact model uses a function model that records the continuous change of the comprehensive environment with spatial position and time in a spatio-temporal coordinate system to quantify the impact of the environment on the mission. By rasterizing the model, path search based on the shortest time cost and the minimum threat degree cost is used to obtain the reachable spatio-temporal range of mission activities, the degree of adaptation of the mission to the environment, and the optimal execution plan within the spatio-temporal range of feasible solutions, thereby realizing the prediction of mission effectiveness evaluation in multiple dimensions. The present invention can achieve an all-round evaluation of the mission under the influence of the environment, including extreme performance, mission spatio-temporal range, and optimal comprehensive performance, which is more scientific, reasonable, and convenient for practical scenario applications.

Scanner aberration impact modeling in semiconductor manufacturing processes is described. Scanner aberration impact modeling can facilitate co-optimization of multiple scanners. Scanner aberration impact modeling can include executing a calibration model and controlling a scanner based on output from the model. The model is configured to receive patterning system aberration data. The model is calibrated with patterning system aberration calibration data and corresponding patterning process impact calibration data. New patterning process impact data for the received patterning system aberration data can be determined based on the model. The model includes a hyperdimensional function configured to associate the received patterning system aberration data with the new patterning process impact data. The hyperdimensional function is configured to associate the received patterning system aberration data with the new patterning process impact data in an approximate form, rather than full simulation, and without involving computation of aerial images or representations thereof.

The present invention belongs to the field of task execution environment evaluation, and particularly relates to a method and system for comprehensively evaluating the environmental cost of a task plan based on spatio-temporal voxels. A spatio-temporal comprehensive environmental impact model for describing the laws of spatio-temporal environmental impact for tasks is constructed in a spatio-temporal coordinate system; the spatio-temporal comprehensive environmental impact model is rasterized to construct spatio-temporal voxels, and the spatio-temporal trajectory during the execution of the task plan is obtained through trajectory tracking. The comprehensive environmental cost of the task plan is calculated according to the occurrence and accumulation laws of the cost of the spatio-temporal voxels passed through. By constructing a comprehensive environmental impact model based on spatio-temporal voxels, the present invention extends the time dimension on the basis of the spatial cost law of the task environment to realize the situation of continuous change in time at any point in space, can reflect the impacts of various factors of time and space on the task, comprehensively and reasonably realizes the spatio-temporal environmental evaluation of the task plan, and the analysis principle is close to the actual situation, having a good application prospect.

Using a failure probability model, a probability of a failure in a first system within a specified time period is predicted. Using an impact model, an impact of the failure on a second system is predicted. Using a resilience model, an impact reduction of the failure is predicted. The probability, the impact, and the impact reduction are mapped into a recommended service level agreement category for the first system, the mapping performed using a classifier model.

This invention relates to the field of wind and sand protection, and discloses a vegetation protection method based on the laws of wind and sand erosion. First, historical wind and sand erosion patterns are collected, recording data on the air impact, soil erosion, and vegetation erosion. Using large-scale modeling technology, an impact model is established, and erosion simulation experiments are conducted to obtain air protection data, soil protection data, and vegetation protection data. Real-time monitoring and evaluation are performed to obtain wind and sand monitoring data. Based on this data, the wind and sand movement patterns are predicted, yielding wind and sand trajectory prediction results. The protection data are then integrated to obtain a first vegetation protection scheme, establishing a vegetation protection trajectory model. The vegetation protection trajectory model is then corrected in real time to obtain a second vegetation protection scheme. This invention solves the problem in existing technologies where vegetation selection for wind and sand protection lacks specificity and cannot be tailored to the wind and sand erosion trajectory.

The application provides a block analysis method for a transient strong impact non-stationary response signal, a storage medium and computer equipment, belongs to the field of non-stationary impact response signal processing, strong impact model test and nonlinear dynamics analysis, and solves the problems that the traditional method cannot objectively identify the stage dynamics evolution of the transient strong impact non-stationary response signal, cannot adaptively extract a local approximate stationary block in the same stage, and finally cannot reveal the system motion evolution law and cannot support subsequent dynamics characteristic extraction analysis. Through signal preprocessing, phase space reconstruction, maximum Lyapunov index stage division, critical time criterion block and stationarity test, the application extracts effective block characteristics, realizes accurate analysis of the transient strong impact non-stationary signal, and has objectivity, adaptivity and universality, and can support subsequent dynamics research.

The invention relates to the field of railway electrified power supply systems, in particular to a railway overhead line system icing form evolution characteristic quasi-steady-state numerical simulation method which comprises the steps of numerical simulation modeling, freezing rain liquid drop impact model setting, freezing rain liquid drop impact simulation, liquid film generation and phase change icing and ice layer appearance updating. According to the method, the whole process of the contact network surface from microscopic droplet impact to macroscopic ice layer formation is fully considered, the whole process comprises droplet impact, breaking, liquid film generation, phase change and ice layer form growth, compared with the prior art, prediction deviation caused by single link simplification is avoided, meanwhile, the grid is dynamically deformed through the RBF interpolation function, and the prediction accuracy is improved. Real-time updating of the ice layer appearance in the simulation process is achieved, and the limitation of a traditional fixed boundary method is overcome; in addition, the method also has the characteristics of real reproduced freezing rain intensity and environmental characteristics and high calculation efficiency.

The present invention discloses a method for predicting the trend of atmospheric air quality along the coast of the Yellow Sea during the frequent period of the Yellow Sea green tide, which relates to the technical field of air quality prediction, and includes the following steps: clarifying the research area of ​​the Yellow Sea green tide, and collecting ocean data related to the frequent period of the Yellow Sea green tide and historical data of atmospheric air quality; by comparing the ocean and atmospheric data during the period when the green tide occurs and the period when the green tide does not occur, analyzing the correlation between the ocean data and the historical data of atmospheric air quality. The present invention constructs and applies an air quality impact model, accurately predicts the atmospheric air quality along the coast of the Yellow Sea based on historical data and real-time monitoring information, comprehensively considers multiple factors such as meteorological conditions and marine environment, thereby improving the accuracy and reliability of the prediction, which not only helps us to understand the air quality status in a timely manner, but also provides a scientific basis for formulating targeted prevention and control measures, and effectively responds to air pollution problems.

The present invention relates to the field of scattering analysis of optical elements, and particularly to a method for scattering analysis of optical elements under ultra-high-speed impact based on finite element simulation, including: setting the parameters of each impactor and the target plate respectively in finite element simulation software, constructing an impactor model and a target plate model, and the impactor model and the target plate model form an ultra-high-speed impact model; performing ultra-high-speed impact simulation based on the ultra-high-speed impact model to obtain the target plate model after impact, and extracting the three-dimensional topography data of each impact crater from the target plate model after impact; constructing an optical element model, and importing the three-dimensional topography data of each impact crater into the optical element model, and obtaining an optical element model with multiple impact craters through data fitting; calculating the bidirectional scattering distribution function according to each impact crater of the optical element model to obtain the influence of the scattering of the impact crater on the optical system. The present invention can analyze the influence of light scattering caused by impact craters on the imaging quality.

The disclosure herein describes predicting potential impact of issues reported in incident ticket data on infrastructure element. A ticket manager component includes an impact model utilizing machine learning to analyze real-time event and metric data with incident-related data to generate predicted impact data. The predicted impact data identifies potentially impacted infrastructure elements, such as, potentially impacted users, predicted infrastructure components impacted by the issue and / or an updated time-period associated with the issue. The ticket manager component creates labeled incident tickets by updating user-generated incident tickets with additional data generated by the impact model, including predicted impact data and / or additional details associated with the issue. The labeled incident tickets are provided back to the model as training data to further refine predictions generated by the model.

This invention belongs to the field of unmanned aerial vehicle (UAV) control technology, specifically relating to a method and system for attitude stabilization control of UAVs under special environmental disturbances. The method includes the following steps: S1: Establishing a wind field disturbance model, a dust particle impact model, and an electromagnetic interference model, and dynamically coupling these three models into a total disturbance vector experienced by the UAV; S2: Constructing a six-degree-of-freedom dynamic model incorporating the influence of the total disturbance vector. This model describes the translational and rotational motion of the UAV's center of mass under multi-source disturbances in complex environments; S3: Based on traditional aerodynamic models and incorporating environmental disturbance parameters, constructing a variable structure model with aerodynamic coefficients. This invention effectively improves the UAV's adaptability to multi-source coupled disturbances by constructing a unified multi-layered architecture for environmental identification, disturbance observation, Lyapunov robust control, and actuator compensation, thereby ensuring mission accuracy and safety.

This invention provides a big data-based intelligent matching method for upstream and downstream enterprises in the chemical industry chain, belonging to the technical field of matching upstream and downstream enterprises in the chemical industry chain. The method includes collecting multi-dimensional feature data of the chemical industry chain; analyzing basic enterprise data using an industry chain attribute matching algorithm; analyzing the dynamic changes in supply and demand relationships with market cycles; constructing a quantitative model of supply and demand impact, analyzing the influence weight of dynamic supply and demand data on initial enterprise matching data; and building an intelligent matching model of the industry chain to evaluate the matching process of upstream and downstream enterprises in real time. By integrating multi-dimensional feature data of enterprises and utilizing industry chain attribute matching algorithms, dynamic supply and demand analysis methods, quantitative supply and demand impact models, and intelligent matching models of the industry chain, this invention achieves accurate matching and dynamic optimization of upstream and downstream enterprises in the chemical industry chain, solving problems such as reliance on manual experience in matching, untimely response to dynamic changes in supply and demand, and insufficient risk management capabilities in existing technologies.

The present invention provides a hydrogen consumption simulation system and method for vehicle transportation routes based on multiple models. Belonging to the fields of new energy and simulation technologies, the method includes: based on a basic power demand model and a hydrogen consumption calculation model, combining the multi-source data collected in real time by a multi-source data acquisition network with historical data, optimizing the existing model through a machine learning algorithm, and updating the hydrogen consumption calculation model. By collecting multi-source data in real time, combining historical data and a machine learning algorithm to optimize the existing model, the hydrogen consumption situation can be predicted more accurately. At the same time, by collecting new data on external environmental factors in real time, optimizing the environmental impact model, and further correcting the hydrogen consumption calculation results, the accuracy of the simulation is improved.

The application discloses a method and system for designing parameters of a ground surface concrete cushion layer for protecting a buried pipeline based on rockfall influence, and the method comprises the following steps: constructing a rockfall impact model, a buried pipeline model and a cushion layer model; collecting strain data and velocity of rockfall, variation of earth pressure in an undisturbed soil layer and strain of the buried pipeline model by using a data testing device; analyzing the collected data, and retaining data not exceeding a preset safety range; changing parameters of the cushion layer model by using a control variable method, and keeping other model parameters unchanged until analysis of all parameters of the cushion layer model is completed, and then stopping; further analyzing the retained data to obtain a relationship between strain and the parameters of the cushion layer model, and completing parameter design of the buried pipeline. The application effectively simulates the protection effect of the concrete cushion layer on the buried pipeline under rockfall impact, is closer to an actual engineering, and provides a reference value for the actual engineering.

The invention discloses a method for establishing a multi-particle multi-azimuth impact model for a glass cabinet surface. The method comprises the following steps: establishing a glass substrate model, a plurality of micro-nano super-hydrophobic CNT / SiO2 particle models and an Euler domain model; assembling the glass substrate model, the Euler domain model and the plurality of micro-nano CNT / SiO2 super-hydrophobic particle models; performing grid division on the glass substrate model and the Euler domain model; establishing a temperature-displacement coupling analysis step; setting contact interaction attributes; and setting boundary conditions of all the models, speed parameters of the micro-nano CNT / SiO2 super-hydrophobic particle model and initial temperatures of the micro-nano CNT / SiO2 super-hydrophobic particle model and the glass substrate model, so that the micro-nano CNT / SiO2 super-hydrophobic particle model impacts the glass substrate model in multiple directions at different incident angles. The method lays a foundation for research on particle deformation, equivalent plastic strain, residual stress and the like of cold spraying particle impact.

The invention discloses a method and device for establishing a specific field modeling environment. The method comprises the following steps: constructing a three-layer abstract system for specific field modeling based on a meta-meta model; generating a domain meta-model containing entity class definition, relation class definition and enumeration class definition through an automatic instantiation rule, and configuring attributes, representation forms and constraint relations; packaging the meta-model and the constraint thereof into standardized framework data with a unique identifier; loading the frame data by a runtime analysis module, dynamically generating a visual domain model editor, and enabling a user to complete model construction conforming to constraints; triggering increment verification based on an operation-level event in a model construction process; when the meta-model is updated, executing difference comparison to identify affected model elements and giving repair suggestions; and the runtime expansion of the modeling capability is realized through a plug-in mechanism.

The invention discloses a multi-scale multi-parameter evaluation system for the puncture resistance of a fiber composite material. The multi-scale multi-parameter evaluation system comprises a pretreatment interface and a post-treatment interface which are connected in sequence, a puncture impact model is constructed through a pretreatment interface, the puncture impact model comprises a multi-scale composite material combination structure, an impactor structure and a backing material structure, and mechanical property data for testing a fiber composite material and test data for testing the type of an impactor are obtained; parameters of the composite material combination structure and the cutter structure are set according to the mechanical property data and the test data; performing simulation analysis on the set puncture impact model through a post-processing interface to obtain an anti-puncture response result, and performing effectiveness evaluation and personnel injury risk evaluation on the tested fiber composite material according to the anti-puncture response result; and according to an evaluation result, optimizing the tested fiber composite material to obtain an optimal scheme of the tested fiber composite material. According to the scheme, multi-parameter accurate evaluation and design guidance can be carried out on the puncture-proof performance of the fiber composite material.

The invention discloses a viewpoint dynamics modeling method introducing external event impact, which comprises the following steps: (S1) constructing a multi-agent opinion dynamics model, and initializing system parameters and agent attributes with activeness; (S2) dynamically constructing a social network structure based on viewpoint homogeneity according to the current opinion difference between the agents; (S3) defining and quantifying an external event, and decoupling the influence of the external event into continuous information content and a dynamic response probability attenuating along with time; (S4) establishing a viewpoint dynamic differential equation by integrating the internal attenuation, the local social influence and the external influence of the intelligent agent; and (S5) updating opinion states of all agents through numerical integration to realize dynamic evolution of viewpoints. According to the method, the dynamic impact model in which the event information and the response intention are decoupled is constructed, so that the technical defect that an existing model simplifies external influence into deterministic impact is overcome, and a computing framework which is closer to reality and higher in interpretation is provided for simulation and prediction of complex social phenomena such as public opinion evolution and crisis response.

This invention discloses a multi-dimensional encryption method for secure data output, comprising: acquiring the data to be encrypted; establishing a quantum-resistant encryption computational model, considering the resource consumption problem that may occur during the encryption process; constructing a side effect impact model; analyzing the resource consumption contribution of the quantum-resistant encryption model; designing a resource consumption contribution mitigation strategy and a model feedback mechanism; optimizing and monitoring the side effect impact model in real time; the optimized model can not only reduce the time and space complexity in the encryption process, but also significantly reduce the computational resource consumption without sacrificing encryption strength, thereby improving encryption efficiency while ensuring data security.