32results about How to "Guarantee scientific" patented technology

The invention relates to the technical field of patent early warning, and discloses an artificial intelligence-driven patent risk early warning system, and the system comprises a data collection module which is used for collecting patent data from a patent data source, and carrying out the preprocessing and storage of the data; the patent analysis module is used for carrying out information analysis on the patent texts based on natural language processing and machine learning technologies so as to obtain various data of patents and carrying out classification and similarity analysis on the patents; and the risk assessment module is used for assessing risk analysis of a target patent in combination with various data of the patent, analyzing the legal status of the patent, and assessing historical litigation disputes or potential litigation risks of the patent. According to the invention, through cooperative operation of the data acquisition module, the patent analysis module, the risk assessment module, the risk early warning module and the feedback optimization module, advanced natural language processing, machine learning and other technologies are utilized, and the effects of comprehensive and accurate assessment and early warning of patent risks and continuous optimization are achieved.

The invention discloses a BIM-based communication pipeline design intelligent optimization system and method, and relates to the technical field of BIM. An initial data set X is constructed, the electromagnetic interference intensity between each pair of pipelines is deduced in combination with an electromagnetic field theory, an interference intensity matrix EMI is finally generated, the relative position of a high-interference pipeline is dynamically adjusted by adopting an optimization algorithm, and the relative position of the high-interference pipeline is optimized. The method comprises the steps of generating a preliminary pipeline layout scheme Xop, applying the preliminary pipeline layout scheme Xop to a BIM model, further combining a spatial constraint Cs to perform verification and fine tuning, calculating a pipeline position optimization evaluation index Ft, and comparing the pipeline position optimization evaluation index Ft with a preset pipeline position optimization execution evaluation threshold Fth, thereby realizing scientific evaluation and decision-making of the scheme optimization effect, and improving the pipeline position optimization efficiency. The problems of insufficient electromagnetic interference influence evaluation, disjunction of an optimization process and spatial constraint and the like are solved in a targeted manner, and electromagnetic interference minimization, path optimization rationalization and space resource utilization maximization of communication pipeline layout are realized.

The invention relates to an urban ecological protection and restoration effect evaluation method. The evaluation method comprises the following steps: (1) determining an evaluation base period and an evaluation period according to the implementation progress condition of the ecological protection and restoration project, wherein the implementation progress condition refers to a corresponding state between the start time and the acceptance time of the ecological protection and restoration project; (2) establishing an ecological protection and restoration project implementation effect evaluation index system, and determining evaluation indexes; (3) performing quantitative or qualitative evaluation on each evaluation index, obtaining an evaluation value of each index, calculating an effect evaluation result, and performing grading according to the evaluation result to form an evaluation conclusion; and (4) generating an ecological protection and restoration project implementation effect evaluation report. In order to standardize the technical requirements of urban ecological protection and restoration project effect evaluation, the invention provides an ecological protection and restoration effect evaluation method conforming to urban reality, and evaluation principles, processes, indexes, a calculation method and an evaluation report are clarified.

The invention discloses an intelligent opening and closing method and system for a reclosing circuit breaker based on an electromagnet, and relates to the field of intelligent control, and the method comprises the steps: monitoring a line current in real time, comparing the line current with a preset threshold value, and carrying out the opening after the overcurrent abnormality is detected. Entering a first time delay stage after opening, comprehensively evaluating the states of the circuit breaker and the circuit, and constructing a dynamic weight index system to calculate an evaluation score; if the score exceeds a threshold value, closing is carried out after time delay is finished, otherwise, an alarm is triggered. And entering a second delay stage after switching on, continuously monitoring the electric parameters and establishing an anomaly judgment mechanism, forming a closed-loop protection process of monitoring, switching off, evaluating, switching on and re-monitoring, and realizing intelligent linkage of overcurrent protection and state self-adaption. The method has the advantages that through real-time line electric parameter monitoring, multi-dimensional state evaluation and an intelligent decision-making mechanism, precise opening and closing of the circuit breaker are achieved, the power supply reliability is improved, the power failure time is shortened, and the misoperation risk is reduced.

The application discloses a tunnel structure long-term stability evaluation method based on intelligent detection and monitoring data, relates to the technical field of tunnel engineering monitoring and evaluation, and comprises the following steps: S1, tunnel monitoring data is extracted from a preset database, the data set after classification is processed by adopting a branch condition setting and feature selection mechanism, and a mapped user demand set is obtained; S2, the demand difference is analyzed by adopting a node splitting rule according to the mapped user demand set, and if the demand difference points to a management personnel, a safety level quantitative index is extracted, and preliminary deconstruction information is judged by information gain calculation; the tunnel structure long-term stability evaluation method based on intelligent detection and monitoring data not only improves the accuracy of information expression and the efficiency of report generation, but also establishes a closed-loop information chain from original data to a final report, and effectively guarantees the reliability and scientificity of tunnel structure long-term stability evaluation.

The application discloses a kind of inventory optimization methods of charging facility spare parts replacement cycle and failure rate analysis, and the core process of this method includes building data layer, multidimensional data is cleaned and optimized, to realize standardized storage;Based on the LSTM algorithm, a multidimensional linkage prediction model is built, the loss effect of design defects and environmental factors is quantified to optimize the model, and the accurate spare parts replacement cycle threshold and equipment failure rate are output;According to the flow properties of spare parts, a differentiated inventory management mode is designed, and the optimal management mode of slow-moving parts is selected;A full-cost quantification model is built to calculate the total cost and service level under each mode;Finally, with the goal of minimizing cost, an intelligent inventory control model is built, which dynamically outputs inventory warning thresholds, replenishment quantities and times;Through the algorithmization and parameter quantification of the whole process, the application realizes fine and intelligent management of inventory, significantly reduces operating costs and stockout risk, and improves the stability of charging facilities.

The application provides a low-carbon travel carbon emission reduction amount verification method and system based on travel chain big data, which comprises the following steps: step 1) obtaining sample data of travel data; step 2) when the sample data is walking data, going to step 3); when the sample data is bicycle data, going to step 4); when the sample data is electric bicycle data, going to step 5); step 3) verifying the sample data by using a walking travel distance verification method and removing duplicates to obtain a final effective travel distance; calculating the carbon emission of walking according to the final effective travel distance; step 4) verifying the sample data by using a bicycle travel distance verification method and removing duplicates to obtain a final effective travel distance; calculating the carbon emission of the bicycle according to the final effective travel distance; step 5) verifying the sample data by using an electric bicycle travel distance verification method and removing duplicates to obtain a final effective travel distance; and calculating the carbon emission of the electric bicycle.

The invention relates to the technical field of transmission data detection, in particular to an edge side total detection method and system based on the industrial internet, and the method comprises the steps: determining data collection sites of an edge side, and obtaining original data collected by each data collection site; the method comprises the following steps: respectively determining a site monitoring state and a data acquisition parameter of a corresponding data acquisition site according to each data acquisition site and original data acquired by the data acquisition site so as to determine a site characterization state, setting preprocessors according to the site characterization state, and judging a data security trend of the corresponding site through each preprocessor, determining a subsequent detection mode of the core processor on each data acquisition site according to the data security trend, and determining a corresponding data detection period according to the number of the data acquisition sites subjected to queue jumping processing; according to the method, scientificity and high efficiency of edge side data detection are effectively guaranteed, the data safety situation can be accurately controlled, flexible response can be achieved according to the reality, and the method plays an important role in improving the data detection quality.

The invention relates to the technical field of coal mine water plugging, and discloses a coal mine grouting water plugging effect big data analysis monitoring method and system.The method comprises the steps that spatial overlay analysis is conducted on grouting construction time sequence data and geological structure information of a target area, and an initial incidence relation is obtained; detecting sudden pressure increase and water inflow decrease events, and constructing a precise hydraulic communication relation graph based on a time sequence lag window; performing flow stability evaluation on water inflow data after grouting in the water inflow monitoring time sequence data to obtain a water inflow stable state result; performing relevance study and judgment on the water quality monitoring time sequence data and the water inflow stable state result to obtain a water shutoff long-term evaluation conclusion, and determining a long-term monitoring threshold value of the target area; subsequently, early warning cause diagnosis information is obtained through data comparison and topology traceability; the efficiency of coal mine grouting water plugging effect big data analysis monitoring can be improved.

The application provides a performance test system and method of a micro-arc oxidation product, which comprises the following steps: obtaining a stable open circuit potential of the micro-arc oxidation product in an electrolyte solution at a preset temperature; taking the stable open circuit potential as a starting point, applying a linear potential signal to the micro-arc oxidation product, and determining a current inflection point of the micro-arc oxidation product corresponding to a micro-arc oxidation coating in an anode region in a potential signal scanning process; extracting an accelerated spectrum of a target environment for corrosion based on a coating integrity factor determined based on the current inflection point; placing the micro-arc oxidation product in a controllable environment box for accelerated corrosion exposure treatment based on the accelerated spectrum of the target environment, and determining a current degradation point of the micro-arc oxidation product corresponding to the micro-arc oxidation coating in the anode region after the corrosion exposure ends; and determining a corrosion resistance grade of the micro-arc oxidation product according to the current inflection point and the current degradation point. The technical scheme provided by the application can realize accurate matching of the corrosion resistance grade of the micro-arc oxidation product under accelerated corrosion test conditions.

The invention relates to the technical field of health assessment, in particular to a sleep quality and emotion regulation ability assessment system based on traditional Chinese medicine constitution identification, which comprises the steps of S1, traditional Chinese medicine constitution basic parameter acquisition, S2, constitution corresponding symptom parameter library calling and association degree initial calculation, S3, symptom expression association multi-stage verification, S4, symptom and sleep basic parameter association operation, S5, emotion regulation ability assessment and S6, emotion regulation ability assessment. And S5, performing comprehensive correlation evaluation on the symptom and emotion parameters. According to the method, the preliminary pre-judgment is generated through matching of the traditional Chinese medicine constitution typing parameters and the tongue vein posture parameters, the overlapping degree is calculated in combination with the corresponding symptom library, the symptom collection priority is generated, and the data collection efficiency is improved. And then a traditional Chinese medicine constitution nine-score method associated threshold matrix is called to check symptom information, and invalid data interference is reduced. And finally, the correlation degree is calculated by fusing symptom, sleep and emotion parameters, so that closed-loop evaluation of physique-sleep-emotion deep fusion is formed, the systematicness and accuracy of evaluation are improved, and targeted support is provided for health management.

The invention relates to the technical field of germplasm screening, and discloses a melon low-temperature-resistant germplasm screening method and system, and the method comprises the steps: carrying out the abnormal value correction of time sequence phenotypic data, and obtaining standard phenotypic data; extracting low-temperature stress response data of the standard phenotype data to obtain key physiological features, and performing curve fitting on timestamps of the key physiological features to obtain a time sequence change curve of the key physiological features; performing nonlinear time-varying analysis on the key physiological features and the time sequence change curve to obtain a digital low-temperature response spectrum; based on historical response spectrum data, performing adaptive spectrum enhancement on the digital low-temperature response spectrum to obtain an optimized low-temperature response spectrum; carrying out dimension reduction treatment on the optimized low-temperature response spectrum to obtain a low-temperature-resistant principal component, and determining a comprehensive low-temperature-resistant index according to the low-temperature-resistant principal component; grading the muskmelons to be screened based on the comprehensive low temperature resistance index to generate a germplasm screening report; the low-temperature-resistant germplasm screening efficiency of the muskmelon can be improved.

The invention relates to the technical field of groundwater refilling processing, and discloses a geophysically embedded rock mass deformation constraint refilling water quantity regulation and control method and system, and the method comprises the steps: obtaining multi-source monitoring data containing refilling water, rock mass strain monitoring data, rock mass spatial position and fault geological information, determining initial rock mass strain estimation data of back-replenishing water-rock mass coupling through a Kalman filtering algorithm state space model; performing exception processing to obtain standardized data, and generating fault sensing position codes fused with back water replenishing features; microcosmic, microcosmic and macroscopic scale feature extraction is carried out on the standardized data based on geological physical rules, initial fusion features are obtained after geological physical feature fusion, and enhanced fusion features are obtained through fault sensing position coding geological prior enhancement; the characteristics are analyzed to determine emergency, conventional and macroscopic regulation and control requirements, and the methods of model predictive control, near-end strategy optimization, uncertainty modeling and the like are respectively adopted to execute back-replenishing water quantity regulation and control at different time scales.

The utility model discloses a wire end connection strength testing device of a power supply cabinet, and particularly relates to the technical field of wire end testing of the power supply cabinet, which comprises a working table, two U-shaped fixing frames are arranged at the top of the working table, first electric telescopic rods are fixedly arranged in the two U-shaped fixing frames, and an adjusting mechanism is arranged on one side of each first electric telescopic rod. The adjusting mechanism comprises a fixing plate fixedly arranged at the output end of the first electric telescopic rod, two guide rods are fixedly arranged on one side of the U-shaped fixing frame, one end of each guide rod penetrates through the fixing plate and extends towards the outside of the fixing plate, a stabilizing plate is fixedly arranged on the inner wall of the U-shaped fixing frame, and mounting grooves are formed in the surfaces of the fixing plate and the stabilizing plate. And a T-shaped mounting block is arranged in the mounting groove in a sliding manner. The wire end fixing device can be flexibly adapted to wire ends with different sizes, the rubber layer protects the wire ends and realizes stable fixation, and the connection strength of the wire ends can be accurately tested.

The invention relates to the technical field of data processing, in particular to a digital management system for group meals, which comprises a data acquisition module, a data integration module and a catering prediction module, wherein the data integration module is used for determining the meal selling quantity of the catering train in each meal selling time period so as to determine the meal selling high-point time period of the catering train and the corresponding expected meal selling quantity, and determining the average meal selling quantity and the meal selling fluctuation value of the train in the meal selling time period in the same time period; determining a plurality of meal selling floating time periods of the catering train and floating meal selling quantity corresponding to each meal selling floating time period; the catering prediction module determines the meal selling trend of the catering train, the meal preparation number of the catering train in the meal selling high-spot time period and the floating meal preparation number of each meal selling floating time period; the digital management system for group meals provided by the invention is helpful for improving meal selling efficiency, optimizing resource allocation, promoting digital transformation and improving customer experience.

The invention discloses a method for quickly investigating and evaluating an ecological geologic background in a high mountain and valley region based on remote sensing and geological information, and belongs to the technical field of ecological geologic investigation and evaluation. According to the method, through information integration of multi-source remote sensing and geology, landform, soil and vegetation databases, and through radiometric calibration, atmospheric correction and spatial registration processing, topographic factors and landform structural features are accurately extracted. And carrying out landform unit subdivision by combining fractal dimensions and landform morphological indexes, introducing a geology-ecology coupling self-supervised graph neural network model, and carrying out spatial heterogeneous graph expression on different geology and ecology attributes. Spatial statistics and clustering analysis are utilized to realize automatic zoning evaluation of regional ecological sensitivity and geological stability, and model parameters are optimized through field sample plot check. According to the method, the ecological geologic background unit identification of the alpine and valley complex area can be efficiently realized, and a scientific support is provided for ecological protection and geological disaster risk management.

This application provides a method, apparatus, and electronic device for generating a design scheme for a power battery system. The method includes: reading multi-source cell data, filtering the cells, and generating an initial electrical topology for the power battery system; discretizing the battery pack cavity to obtain several independent sub-cavities, constructing a thermo-mechanical weight field, and allocating target capacity to each sub-cavity based on the cell requirements of the initial electrical topology and the thermo-mechanical weight field; performing cell arrangement operations within each sub-cavity, and reorganizing the resulting cell units into module space to obtain the arrangement result; performing double verification on the arrangement result until a compliant arrangement result passes both verifications; if the battery pack power distribution unit configuration is a top-mounted configuration, performing PDU space permutation optimization; and generating an interpretability label for the power battery system design based on the optimized compliant arrangement result to obtain the design scheme for the power battery system. This method solves the design deadlock problem.

The invention relates to the technical field of microorganisms, in particular to a multifunctional lactobacillus paracasei strain capable of promoting growth and development and application of the multifunctional lactobacillus paracasei strain. The Latin name of the multifunctional Lactobacillus paracasei strain is Lacticaseibacillus paracasei ZG1, the preservation number of the multifunctional Lactobacillus paracasei strain is CGMCC No.36863, the preservation date of the multifunctional Lactobacillus paracasei strain is December 5, 2025, and the preservation unit of the multifunctional Lactobacillus paracasei strain is China General Microbiological Culture Collection Center. Experiments prove that the multifunctional lactobacillus paracasei strain has the functions of promoting neurocognitive development, immune system maturation and bone growth, and can be added into an infant probiotic preparation to play a role in promoting growth and development. Compared with existing probiotics, the lactobacillus paracasei ZG1 has a multi-target and multi-system synergistic promotion function on growth and development, is expected to replace a traditional mixed probiotic scheme, and fundamentally solves the core problems of single function, mixed antagonism and the like of most of existing probiotics.

This application relates to a multi-level adaptive control method, apparatus, device, and storage medium for power quality, belonging to the field of power grid service technology. The method includes: determining the disturbance condition type of the power grid based on target indicator data; selecting a first control strategy from a control strategy template based on the disturbance condition type; updating the strategy parameters of the first control strategy based on the target indicator data and the disturbance condition type to obtain a second control strategy; and managing power quality of the power grid according to the second control strategy. This application effectively improves the efficiency and effectiveness of power grid power quality management, while relying on data-driven strategy selection and parameter optimization to reduce the blindness of management and ensure the scientific nature and effectiveness of power grid power quality management.

The invention belongs to the technical field of traffic infrastructure underground disease detection, and particularly relates to an underground cavity detection and filling quality safety assessment method based on elastic wave exploration. Comprising the following steps: step 1, arranging elastic wave exploration survey lines along the longitudinal direction and the transverse direction of a target area, simultaneously extracting three feature values of reflection intensity, two-way travel time and instantaneous spectral bandwidth for each voxel to identify a cavity area, dividing injection and filling subareas through three-dimensional connected domain search, and determining a target filling volume of each injection and filling subarea; and 2, after filling media are injected into all the cavity areas, the filling effect is evaluated in combination with settlement monitoring, and a differential inspection management scheme is formulated. According to the invention, cavity refined partition identification based on elastic wave exploration, quantitative evaluation of filling quality and differentiated inspection management of multi-source data fusion are realized.

The present application belongs to the field of sewage treatment, and provides a chemical industry park groundwater pollution tracing method based on geophysical exploration cooperation, which uses geophysical methods to detect target areas in the chemical industry park, and obtains underground electrical parameter data; based on the spatial form characteristics and physical parameter gradient change law of the resistivity anomaly area, a layout scheme of groundwater chemical sampling target points is determined; groundwater samples are collected according to the layout scheme, and chemical detection analysis is performed; the pollutant data obtained by the chemical detection analysis is subjected to spatial position corresponding and correlation analysis with the resistivity three-dimensional model; the pollutant concentration spatial distribution map, the park enterprise layout and the regional hydrogeological conditions are comprehensively considered to identify the pollutant migration path, lock the pollution source and output the pollution tracing result. The method improves the accuracy of pollution tracing.

This invention relates to the field of artificial intelligence technology and discloses a method for identifying marine environmental risks based on big data. The method includes: standardizing marine environmental monitoring data to obtain a standardized dataset of the ocean; performing correlation analysis on the standardized dataset based on a pre-set risk knowledge base to obtain risk correlation features of the ocean; constructing a topology of the risk correlation features based on historical risk events of the ocean to obtain an environmental risk feature map of the ocean; tracking the trajectory of the environmental risk feature map to obtain the spatiotemporal evolution path of the ocean; simulating the spatiotemporal evolution path to obtain a risk evolution trajectory report of the ocean; and comprehensively evaluating the risk evolution trajectory report to obtain the risk level and early warning information of the ocean. This invention can improve the efficiency of marine environmental risk identification based on big data.

This invention relates to the field of electric drive system design and development for new energy vehicles, specifically to a method for testing and analyzing the dynamic stiffness of electric drive assembly mounts and the accuracy of simulation. The method involves standardized frequency response testing of the electric drive assembly mounts, identification of minimum dynamic stiffness, and the construction of a dynamic simulation model consistent with the test boundaries to extract the minimum dynamic stiffness on the simulation side. Then, it sequentially performs frequency and amplitude error analysis of the minimum dynamic stiffness points in the tests and simulations, as well as average dynamic stiffness error analysis. Finally, it comprehensively calculates accuracy performance coefficients based on multi-dimensional error coefficients and establishes a scoring system to achieve a quantitative evaluation of the test and simulation accuracy. This method solves the technical problems in existing technologies where evaluating the dynamic stiffness of electric drive assembly mounts requires multiple physical impact tests, which are resource-intensive, time-consuming, and lack a systematic and quantitative analysis method for testing and quantifying the accuracy of mount dynamic stiffness, thus failing to utilize the preliminary analysis results to guide subsequent mount design and development.

The application relates to a kind of open public place emergency decision-making method, equipment and medium based on multi-agent, comprising: obtaining the attribute and definition domain of current emergency problem data, historical case data and emergency scheme;Based on emergency knowledge enhancement big model intelligent agent framework, the key attribute set and attribute value vector of current emergency problem are generated by case analysis expert intelligent agent, the similarity of each key attribute with historical case is calculated, and the set of alternative emergency scheme is generated;Through the group decision-making combination weighting of multiple weighting expert intelligent agent, attribute weight vector and emergency cost attention degree value are generated;The comprehensive utility value of each alternative emergency scheme is calculated by decision expert intelligent agent, and the scheme corresponding to the maximum value is selected as the solution.Compared with the prior art, the application has the advantages of high intelligence, strong real-time performance and good reliability.

The invention relates to the technical field of resource scheduling, and discloses a fire emergency resource intelligent allocation method and device based on big data and a medium, and the method comprises the steps: carrying out the semantic situation reconstruction of a target disaster event, and obtaining the structural event description of the target disaster event; performing spatio-temporal topological relation mining on the structured event description, and constructing a dynamic evolution association graph of the structured event description; performing reverse backtracking on the dynamic evolution association graph to obtain a disaster-causing causal chain of the dynamic evolution association graph; performing coupling quantitative evaluation on the target fire-fighting emergency resource to obtain an effectiveness weight of the target fire-fighting emergency resource; performing path planning on the target fire-fighting emergency resource, and performing collaborative coding on the planned path to obtain a collaborative scheduling instruction of the target fire-fighting emergency resource; issuing the cooperative scheduling instruction to the target fire-fighting emergency resource, and generating an emergency disposal scheme of the target disaster event; according to the invention, the efficiency of the fire emergency resource intelligent allocation method based on big data can be improved.

The invention discloses an agricultural data acquisition and transmission system based on Internet of Things, belongs to the technical field of data acquisition, is used for acquiring, transmitting and storing agricultural data through an Internet of Things acquisition terminal, and comprises a plurality of edge acquisition stations and a storage device for storing the agricultural data, wherein the edge acquisition station is used for receiving and processing agricultural data from the Internet of Things acquisition terminal; determining a data distribution process by the edge acquisition station, and determining at least one target edge acquisition station of any type of Internet of Things data; according to the invention, detailed data processing rules are formulated according to different conditions, and the accuracy and scientificity of data distribution are guaranteed, so that the stability and reliability of an agricultural data acquisition and transmission system are enhanced on the whole, and more powerful data support is provided for agricultural production.

The application discloses a manufacturing process intelligent generation method based on a knowledge graph and controllable reasoning. First, manufacturing process data of a target manufacturing object is automatically extracted and stored in a structured manner to construct a manufacturing process knowledge graph adopting a node-edge model. An optimal process template is selected through a two-level mechanism of field matching preliminary screening and directed graph judgment. A parameter context is generated based on knowledge graph reasoning to complete intelligent parameter filling of the process template. Finally, a standardized process procedure file is output and closed-loop verification is performed. The application realizes automatic intelligent generation of a manufacturing process procedure in the whole process, which is controllable and interpretable, significantly improves process preparation efficiency and quality consistency, and can be widely applied to process planning links in various high-end manufacturing scenarios.

This invention provides a method for dynamic urban renewal based on deep reinforcement learning, relating to the field of urban renewal. The method includes: step S1, data acquisition; step S2, state prediction; step S3, hierarchical decision-making; step S4, execution feedback; and step S5, iterative optimization. Hierarchical decision-making, based on the urban state data in step S1 and the predicted state in step S2, implements hierarchical update schemes for macro-level, meso-level, and micro-level intelligent agents. This method transforms urban renewal from a one-time static planning process to dynamic adaptive decision-making that evolves with the urban system, thereby achieving dynamic adaptation of infrastructure and public services and avoiding negative impacts such as environmental damage, facility idleness, resource waste, and increased costs caused by mismatch.

The invention relates to the technical field of nuclear safety and emergency, discloses a design method and system of a nuclear accident auxiliary decision-making software architecture, provides an implementation method of a core function module, follows a corresponding combination rule, and further solidifies a basic form of a decision-making support system facing accident emergency disposal. Comprising an overall structure, a relationship between modules and a data flow direction. According to the design method, operation data are analyzed, a simulation calculation engine is loaded, advanced simulation is carried out on the future state of the nuclear power station, an intervention scheme is formulated, and the implementation effect of the intervention scheme is evaluated in combination with prediction calculation. According to the method, high modularization of nuclear accident auxiliary decision-making software design is realized, analysis software for emergency decision-making needs in the nuclear accident period can be quickly constructed, and the design flexibility and the overall stability are improved.

The invention relates to the technical field of online tool status monitoring, and specifically discloses an online tool status monitoring system for a CNC machining center, comprising a cutting process preprocessing module, a cutting process status analysis module, a cutting process early warning analysis and display module, a cutting completion preprocessing module, a cutting completion status analysis module and a cutting completion early warning analysis and display module. By analyzing a tool jamming evaluation coefficient corresponding to a target cutting action, the system effectively makes up for the deficiency of modern tool monitoring technology in analyzing the jamming height and jamming number corresponding to a specified tool in a cutting process video, improves the reliability and effectiveness of the cutting action analysis corresponding to the specified tool, provides strong data support for the cutting process status evaluation coefficient corresponding to the target cutting action, increases the timeliness and response efficiency of replacing the specified tool, avoids the safety hazards existing in the quality of processed workpieces, and improves the processing efficiency of processed workpieces.