527 results about "Parameter analysis" patented technology

The invention discloses a CAD automatic modeling method and system based on parameter driving. The method comprises the steps that model parameter information needing modeling is obtained; generating a CAD (Computer Aided Design) model on the basis of parameter analysis, geometric construction and surface recognition schemes; performing reverse reconstruction of the three-dimensional CAD model based on topology analysis, geometric feature extraction, pattern recognition and parameter relation inference; modeling, optimization and feedback evolution are carried out based on model analysis, feature learning and generation of parametric modeling rules; and according to the obtained data information, CAD automatic modeling based on parameter driving is completed. According to the method, CAD automatic modeling based on parameter driving is achieved, the reliability is higher, the accuracy is better, and the efficiency is higher.

The invention provides an automatic history fitting method for gas drive numerical reservoir simulation, which comprises the following steps of: 1, establishing a gas drive numerical simulation mathematical model, and correcting the gas drive numerical simulation mathematical model by using a gas drive PVT phase state fitting experiment; 2, solving the corrected gas drive numerical simulation mathematical model obtained in the step 1, performing parameter analysis, and screening main control factors influencing accumulated oil production; 3, generating a numerical simulation training sample set based on an orthogonal experiment, and obtaining the main control factor parameter initial value constraint screened out in the step 2 through a machine learning algorithm; step 4, establishing a multi-parameter fitting objective function for realizing historical fitting; and step 5, using the main control factor parameter initial value constraint obtained in the step 3, performing iterative calculation through a projection gradient method, fitting the target function established in the step 4, and terminating when a convergence condition is satisfied. According to the method provided by the invention, the constraint parameter values can be adaptively calculated, automatic historical fitting is completed, and the definition of the fitting parameter range does not depend on empirical and experimental determination any more.

The invention discloses a bridge structure health state intelligent sensing and early warning system, relates to the technical field of bridge monitoring, and provides the following scheme that the bridge structure health state intelligent sensing and early warning system comprises a sensing layer, a transmission layer, a data layer, an analysis layer and an application layer which are connected in sequence and work cooperatively: the sensing layer is used for comprehensively collecting health state parameters of a bridge structure; according to the method, the comprehensiveness of monitoring parameters is guaranteed, the effectiveness and transmission efficiency of collected data are improved, redundant data are prevented from occupying resources, deep mining is achieved, a more scientific basis is provided for health status assessment and disease diagnosis, misjudgment caused by single parameter analysis is reduced, the diagnosis precision is improved, and the method is suitable for popularization and application. The intelligent optimization and simulation evaluation of the maintenance scheme are realized, the limitation of the traditional empirical scheme is avoided, the maintenance cost is reduced, the construction period is shortened, the influence on traffic is reduced, the performability of the scheme is improved, the stable and safe transmission of monitoring data in a complex environment is ensured, and the data loss or leakage is avoided.

The invention belongs to the technical field of bridge engineering, and aims to eliminate the problem of systematic underestimation of web bearing capacity under the condition of standard effective loading length. The invention provides a method for correcting a local pressure bearing capacity calculation formula of a steel beam web, which comprises the following steps of: identifying and determining a key parameter ratio and an engineering application range thereof by carrying out sensitivity parameter analysis on a bending reduction coefficient; on the basis of the reference engineering case, fixed values are taken from part of parameters, and other geometric quantities are inversely calculated; based on a preset variable sequence, finite element models are established in Abaqus in batches, and the ultimate bearing capacity and the flange longitudinal stress level of each model are extracted; the standard calculation value is corrected according to a finite element result, the corrected ultimate bearing capacity of the steel beam web is calculated, and a corrected bending reduction coefficient is obtained accordingly; and finally, fitting a corrected formula about the regularized slenderness ratio on the correction coefficient by taking the specification parameter as an independent variable to obtain an expression capable of directly replacing the original specification. The method can significantly improve the calculation precision.

The invention provides a multi-dimensional operation parameter analysis fault detection method and system, and relates to the technical field of fault detection, and the method comprises the steps: building an inspection task system and a fault triggering system, and forming a task basic data set; generating an inspection task instance object; analyzing to obtain monitoring index data; effective fault report information is extracted, and a software system inspection result set is formed; operating parameters of the hardware system are collected, threshold detection and fluctuation analysis are executed, and a hardware system inspection result set is generated; and extracting multi-dimensional features, inputting a fault scoring function, calculating a comprehensive fault score of each device or system, and automatically generating an inspection report and a fault report sheet. According to the method and the device, the problems that fault evaluation depends on manpower and judgment standards are not uniform in the prior art can be solved, automatic risk grading and result generation based on comprehensive scores are realized, and thus the accuracy and the diagnosis efficiency of fault detection are improved.

The invention provides a battery cell fault real-time monitoring method and system based on multi-parameter analysis and calculation, and relates to the field of battery safety monitoring. The method comprises the following steps: synchronously acquiring voltage, temperature and internal resistance signals of a battery cell, and preprocessing to obtain original data; and performing voltage correlation analysis, internal resistance-temperature collaborative judgment and isolated forest anomaly detection on the original data in sequence to form a progressive anomaly judgment chain, and extracting multi-dimensional battery cell state features. And dynamically correcting the voltage protection threshold value based on the battery health state attenuation rate and the real-time temperature. And fusing multi-dimensional battery cell state characteristics through a fuzzy rule base, and calculating a comprehensive fault probability to divide a fault probability grade. And triggering a matched response strategy based on the fault probability level. The technical problems that single-parameter monitoring is low in sensitivity and high in false alarm rate, and the real-time monitoring requirement is difficult to meet by depending on historical data are solved.

The invention discloses a confidential evaluation compliance document automatic generation system and method based on strategic data management and control and full-link verification, and aims at solving the problems that traditional confidential evaluation document generation is low in efficiency, insufficient in safety protection, poor in expansibility and the like. According to the method, hard coding logic is replaced by a strategy engine center, a scene-template-strategy association mechanism is constructed, and full-process automatic generation of secret evaluation documents is achieved through scene configuration, intelligent template matching, parameter analysis, multi-dimensional data cleaning and desensitization, national secret standard automatic signing and full-process log management and control. The generation efficiency is remarkably improved, a sensitive data'identification-processing-protection 'safety closed loop is formed, the tamper-proof and auditing requirements of secret evaluation are met, a newly-added scene can be quickly accessed through strategy configuration, and the expansibility and reusability are excellent.

The invention belongs to the field of electronic design automation, and discloses a multi-agent radio frequency circuit netlist generation method and system based on a large language model, and the method comprises the steps: preparing a data set, and constructing a knowledge base; the method comprises the following steps: receiving and analyzing a natural language demand of a user, combining a cue word project and an RAG mechanism, carrying out chained reasoning, introducing a radio frequency design rule, and converting the information into structured parameter information; combining RAG knowledge base retrieval and new topology generation, and fusing PDK process constraints to obtain candidate topologies and a simulation netlist; a simulation tool is called to execute parameter analysis, iterative optimization is conducted on parameters in combination with a closed-loop feedback mechanism, and a final netlist meeting user requirements is obtained. Automatic decomposition, parallel cooperation and high-speed iteration of design tasks are achieved through multi-agent cooperation and in combination with the radio frequency knowledge graph and the RAG; introducing physical constraints to enable the generated topological structure and parameters to meet the physical constraints; and a closed-loop simulation feedback mechanism is fused, so that the dependence on manpower is reduced.

The invention discloses a graphite equipment weld defect intelligent detection and positioning system based on multispectral imaging, and particularly relates to the field of welding, and the system is characterized in that a multiband image acquisition unit acquires spectral image data of multiple bands and transmits the spectral image data to a multispectral data storage library; the spectral parameter analysis unit extracts characteristic parameters of the weld joint area and establishes a spectral characteristic parameter library; a spectrum abnormity identification unit locates a suspected defect area of spectrum abnormity; the weld defect positioning unit marks defect boundaries and ranges; the defect identification and grading unit calculates a defect severity index; the element component analysis unit is used for detecting the suspected defect position sample and analyzing the types and contents of trace elements in the suspected defect position sample; the defect and component data are integrated through the weld quality comprehensive evaluation unit, the quality grade and the rectification suggestion are generated, the problem that the defect cause cannot be positioned in the prior art is solved, data support is provided for follow-up maintenance and process optimization, and potential safety hazards of equipment operation and maintenance are reduced.

The invention relates to the technical field of intelligent safety management and control of a thermal power plant, and discloses a safety management and control application method and system based on big data acquisition and analysis. The method comprises the following steps: constructing an equipment operation situation map by fusing real-time data streams, and realizing dynamic panoramic perception of a system operation state; key nodes are identified based on the atlas, a real-time safety margin index is calculated by using a safety evaluation model, a dynamic instruction set with priority is generated, and the inspection robot is driven to carry out self-adaptive accurate data acquisition; and the central processing unit updates the atlas by comparing and analyzing real-time and historical data, so as to realize risk re-assessment and early warning. According to the method, equipment monitoring is improved from isolated parameter analysis to global association cognition, a fixed inspection mode is converted into predictive intervention based on real-time risks, and the state perception depth, the early warning timeliness and the resource allocation efficiency are improved.

The invention discloses a photovoltaic cable health state assessment method and system, and the system comprises a signal collection module which is disposed at a key node of a cable, and comprises an ultra-wideband pulse sensor, an infrared thermometer, and an illumination sensor; the edge processing module is used for constructing a state characteristic curve and identifying a target sample time interval; the cloud analysis engine is used for executing defect contribution simulation value extraction and thermal-electric coupling model iterative optimization; according to the scheme, multi-dimensional signals such as current, voltage, partial discharge pulse, temperature and illumination intensity are synchronously collected through a distributed sensor network, a multi-parameter evaluation system including amplitude, phase and temperature is constructed, and the health state level, the defect position distribution and the simulation value change trend are displayed through multi-dimensional signal fusion and multi-parameter analysis. And the detection accuracy and comprehensiveness are improved.

The invention relates to the field of environment-friendly packaging boxes, and discloses a multi-modal data fusion environment-friendly packaging box intelligent design auxiliary system which comprises a packaging full-life-cycle heterogeneous atlas database module, a design constraint parameter analysis module, a topological variation index engine module, a compliance and multi-objective optimization module and a parameterization scheme generation module. According to the method, a time dimension is introduced through a topological variation index engine, instantaneous stress in a folding process is calculated in combination with a nonlinear viscoelastic model, physical evolution of a structure is simulated in a virtual design stage, and the fracture risk is predicted; meanwhile, multi-objective optimization is carried out by utilizing a Hash mask mechanism based on laws and regulations and a pruning algorithm, and a compliance design scheme containing production process parameters is output, so that the problems of lack of physical simulation and low compliance verification efficiency in environmental protection material design are solved, and the physical feasibility and the production yield of the design scheme are improved.

The invention provides an optical cable fault rapid positioning method, system and equipment, and the method comprises the steps: obtaining multi-dimensional attribute parameters of a target optical cable section, specifically including a static attribute, a dynamic attribute and an environment attribute for evaluating the operation state of an optical cable; inputting the multi-dimensional attribute parameters into the weighted analysis model and the trained machine learning prediction model in parallel; wherein the weighted analysis model calculates and outputs a first candidate fault position set based on an attribute weight data set, and the attribute weight data set comprises weight scores defined for different types of attribute parameters; analyzing the current multi-dimensional attribute parameters by using the trained machine learning prediction model, and outputting a second candidate fault position set; and fusing overlapped data of the first candidate fault position set and the second candidate fault position set to generate comprehensive fault positioning information. Based on the method, the invention also provides an optical cable fault rapid positioning system and equipment. According to the method, the accuracy of fault positioning and the decision robustness are remarkably improved.

The invention belongs to the technical field of data filtering query, and particularly relates to a dynamic SQL-based parameter data transmission filtering query mode for a low-code visual component, which comprises the following steps of: S1, constructing a low-code visual large-screen component and a background service API (Application Program Interface); s2, interactively filtering the linkage demand by the visualized large-screen component, and realizing dynamic parameter transmission of the SQL parameter transmission query request; s3, providing a visual operation interface by using the visual large screen component; s4, calling the data source identifier stored in the step S2 by the SQL parameter analysis constructor generation component; and S5, performing parameter extraction on the structured filtering condition data by the SQL parameter analysis constructor. According to the overall structure provided by the embodiment of the invention, the SQL parameters are transmitted during data query, and then the back-end service constructs the filtering and screening conditions meeting the conditions based on the dynamic SQL parameter transmission mode to query the SQL and query the database to obtain the data, so that accurate filtering and screening query of the data can be realized; the problem that a traditional large screen cannot perform database level filtering and screening is solved.

The invention discloses a slope soil erosion prediction method, system, equipment and medium, and relates to the technical field of soil erosion, and the method comprises the following steps: taking slope soil with different grain composition as a research object, and carrying out a rainfall simulation experiment; constructing a production and construction project soil erosion prediction model according to the product of a subrainfall erosivity factor, a soil erodibility factor, a slope length factor, a slope factor and a slope surface area on the basis of the grain composition characteristic particle size; and predicting the soil erosion of the slope surface of the to-be-predicted production and construction project through the production and construction project soil erosion prediction model. According to the model disclosed by the invention, a direct quantitative relationship between the characteristic particle size and the erosion strength is established, so that an acquisition way of the soil erodibility factor is simplified, the dependence of the model on complex and expensive soil physical and chemical parameter analysis is greatly reduced, and the operability and the popularization efficiency of the model in a production field are greatly enhanced.

The invention relates to the technical field of smart city operation and maintenance, in particular to a smart city-oriented municipal facility state operation and maintenance analysis method. The method comprises the following steps: collecting multi-source monitoring data of municipal facilities; performing linkage facility state load feature analysis under each collaborative operation based on the municipal facility multi-source monitoring data, and generating linkage facility state load feature data; performing linkage facility state load characteristic trend prediction processing on the linkage facility state load characteristic data to generate linkage facility state load characteristic trend data; establishing a load energy efficiency multi-agent decision model according to the linkage facility state load characteristic data and the linkage facility energy efficiency data; and transmitting the state load characteristic trend data of the linkage facility to a load energy efficiency multi-agent decision-making model to carry out linkage facility intelligent control parameter analysis of global energy efficiency optimization, and generating linkage facility intelligent control parameters. According to the invention, state linkage intelligent operation and maintenance control of smart city municipal facilities is realized.

The invention relates to the technical field of purchase matching, in particular to an online purchase processing method and system oriented to multiple subjects and configurable rules, and the method comprises the following steps: obtaining parameter contents, verifying semantic relationships, field formats and numerical boundaries, embedding state paths, synchronously updating parameter positions, constructing a rule configuration set, and establishing a rule matching set; dividing a role permission supplement operation path, mapping a multi-subject behavior structure, screening a same-value field pushing round sequence, marking time, and matching a response sequence to judge a path inheritance relationship. According to the method, through a parameter checking and semantic analysis mechanism, the consistency of content embedding paths is kept, a multi-role action sequence is constructed based on permission mapping, an operation path is divided and cooperatively controlled, a field aggregation and timestamp extension rule is identified, a quotation round sequence is constructed, and an action path is inherited and promoted by depending on a response matching judgment mechanism. The state link dynamic state is updated, the interface is synchronized, and the overall linkage of parameter analysis, path control, behavior recognition and process scheduling is enhanced.

The invention relates to the technical field of high-pressure injection control, and discloses a high-pressure injector intelligent control system based on the 5G technology. An injection pressure dynamic adjusting module driven by a microcontroller of the system analyzes pressure fluctuation characteristics and generates a primary pressure compensation instruction; the fluid state reconstruction module is used for calculating fluid state reconstruction parameters in combination with the real-time flow velocity data; the multi-channel cooperative control module distributes a pressure compensation weight and generates a channel cooperative instruction set based on reconstruction parameter analysis; the abnormal pressure tracing module monitors abnormal pressure sudden change points of each unit, traces corresponding fluid state parameter change tracks and outputs tracing mark data; the injection path optimization module re-plans a propulsion path trajectory based on the marked data to generate a three-dimensional path optimization parameter table; and the safety threshold self-correction module dynamically adjusts the boundary value of the pressure threshold sequence according to the track offset, and outputs an updated safety threshold parameter set to the microcontroller.

The invention relates to a metadata-driven data consanguinity analysis and influence evaluation method, system and device and a medium. The method comprises the following steps: performing parameter analysis on an original query language script, and constructing a parameter function model in combination with a parameter dimension table; performing parameter replacement on an original query language script according to the model, and analyzing the replaced script to obtain a table-level blood relationship, a field-level blood relationship and the like; constructing a record-level query template based on the field-level blood relationship and the conversion logic, and constructing a dynamic blood relationship map; and executing a record level query template, carrying out record node mounting on the atlas, obtaining and responding to a data change event, carrying out hierarchical influence propagation calculation, obtaining and responding to a data exception event, carrying out root cause node positioning based on the mounted dynamic blood relationship atlas, and generating a repair suggestion. According to the method, through dynamic parameter analysis and record-level blood relationship analysis, the accuracy and automation level of data blood relationship analysis are improved, and the efficiency of data governance is improved.

According to the intelligent production scheduling method and device based on the large model, the production state evaluation model is innovatively designed, and accurate mastering of productivity is achieved through parameter analysis and capability scoring. And a production scheduling optimization system is constructed, and a reliable task allocation mechanism is established in combination with multi-target tradeoff and constraint processing. Dynamic adjustment is introduced, and the adaptability of a production scheduling scheme is ensured through progress monitoring and rule updating. According to the method, the defects of the traditional technology in the aspects of state evaluation, task optimization, dynamic adjustment and the like are effectively overcome, and technical guarantee is provided for intelligent production scheduling.

The invention belongs to the technical field of intelligent monitoring and safety early warning, and provides an intelligent separation grouting opportunity decision system and method.The system comprises a multi-source monitoring data synchronous acquisition and preprocessing module, an InSAR deformation field spatio-temporal feature extraction module and a micro-seismic event cluster multi-parameter analysis module; according to the method, an InSAR macroscopic deformation field and a microseismic microcosmic fracture sequence are cooperatively utilized by the modules, the real-time evolution stage of mining separation is accurately diagnosed through multi-parameter feature extraction and machine learning intelligent judgment, and a quantitative and scientific optimal grouting opportunity decision is provided accordingly. And effective technical support is provided for prevention and control of mine disasters.

The invention discloses an intelligent air conditioner energy-saving control system and method based on AI optimization, relates to the technical field of energy-saving control, solves the technical problems that state judgment and fault early warning are lagged and an energy-saving strategy lacks pertinence, avoids limitation of a single threshold value by constructing a normal working interval of a sub-scene, and improves the energy-saving control efficiency. The potential anomaly analysis unit reduces the misjudgment rate through trend curve modeling and multi-dimensional mutation environment judgment and correlation parameter verification, accurately distinguishes environment fluctuation and equipment anomaly, achieves accurate tracing of fault causes through construction of an anomaly cause knowledge base and combination of deep learning feature extraction and strong correlation parameter analysis, does not need manual troubleshooting one by one, and improves the detection efficiency. According to the method, the fault response time is shortened, the service life of equipment is prolonged, a scenarized energy-saving strategy is generated through an AI algorithm based on the three-dimensional combination characteristics of indoor and outdoor temperature difference, personnel density and parameter change rate, dynamic linkage of load adaptation-parameter optimization is achieved, system energy consumption is reduced, and indoor comfort can be guaranteed.

The invention discloses a laser cutting machine tool security early warning system based on multi-parameter analysis, which relates to the technical field of laser cutting equipment and comprises a front-end sensing layer, a core processing layer and an early warning distribution layer, the front-end differential conditioning circuit is matched with the electric-optical-electric optical fiber transmission link, a high-frequency radiation path of the laser generator and the servo motor is cut off in a physical layer, millisecond-level real-time stripping of dynamic electromagnetic noise is achieved, the problem of weak sensing signal distortion is fundamentally solved, and the detection precision is improved. And meanwhile, the characteristic frequency of the servo motor is stripped in combination with variational mode decomposition, so that the reconstructed monitoring signal has an extremely high signal-to-noise ratio, the crossing from simple early warning to intelligent diagnosis is realized through collaborative analysis of current, vibration and optical data, the risk of mistaken shutdown caused by interference is greatly reduced, the machining continuity is guaranteed, and the working efficiency is improved. And the data transmission delay is greatly reduced, and the security of the equipment is protected to the greatest extent in cooperation with the multi-stage synchronous notification of the early warning distribution layer.

The invention relates to the technical field of semiconductor manufacturing, in particular to a semiconductor scheduling algorithm model configuration system, method and equipment and a medium. The system comprises a data configuration module, an algorithm configuration module, a parameter analysis module, a task scheduling module, a data acquisition module, a model execution module and a result processing module. The data configuration module receives data model configuration parameters input by a user; the algorithm configuration module receives algorithm model configuration parameters. The parameter analysis module analyzes parameters and generates a data preprocessing rule and an algorithm model instance, the task scheduling module creates a scheduling task and triggers a process, the data acquisition module acquires original data from a source data table and preprocesses the original data, the model execution module executes a scheduling algorithm based on the algorithm instance, and the result processing module outputs standard data. According to the invention, decoupling of the data and the algorithm is realized, and the adaptability and expandability of the system are improved.

The invention discloses a scientific research instrument intelligent duplicate checking method based on multi-dimensional parameter decoupling and dynamic weighting, and relates to the technical field of instrument duplicate checking. The method comprises the following steps: constructing a scientific research instrument intelligent duplicate checking model; rAG (enhanced index generation) is adopted as a model framework, and the knowledge base comprises a question preprocessing module and an answer generation module; the classification prediction model is used for classifying query instruments in the question preprocessing module to obtain target instruments; the dynamic weight training model is used for automatically learning the contribution degree of each parameter dimension of a query instrument to overall similarity judgment; performing model processing to obtain the similarity of each parameter dimension of the query instrument and the target instrument, and taking the contribution degree as a weight to generate the overall similarity of the query instrument and the target instrument; determining a duplicate checking result; and judging whether the overall similarity reaches a set threshold value or not. According to the method, objective quantitative calculation of the duplicate checking result based on multi-dimensional parameter analysis and weight optimization is realized through a parameter decoupling and dynamic weighting mechanism.

The invention discloses a traffic engineering construction management method and system based on intelligent perception, and belongs to the technical field of construction management. The system comprises an environment sensing module, an intelligent analysis module, a risk assessment module and an early warning prompt module. The environment sensing module is used for collecting GIS map and environment data, azimuth parameters of operation objects in a construction area and operation parameters of moving objects in a road area, and constructing a three-dimensional scene; the intelligent analysis module analyzes the state of the operation object according to the azimuth parameters and sets equivalent points in the three-dimensional scene; analyzing and calculating a weight coefficient of the moving object in combination with the environment data and the operation parameters; the risk assessment module sets detection points for the equivalent points, analyzes the parameters of the driven-in moving object, calculates the risk coefficient of the equivalent points and the risk index of the operation object in combination with the weight coefficient, marks the operation object and sets a safety point; the early warning prompt module gives out acousto-optic early warning through the helmet, and voice prompt marks that the operation object immediately moves to a safety point for danger avoiding.

A system for analyzing a battery module for possible reuse can include a stage, a measuring component, and a parameter analysis component. The stage can be configured to support the battery module that includes a plurality of batteries. The measuring component can be configured to measure, across a range of frequencies, an impedance across the battery module. The parameter analysis component can include a processor and a memory. The memory can store a reuse assessment module. The reuse assessment module can include instructions that cause the processor to: (1) determine a difference between values, at a first frequency and at a second frequency, of a first derivative, with respect to frequency, of a real part of the impedance and (2) determine, responsive to the difference being less than a threshold, that the battery module is suitable for reuse.

The application discloses a kind of rockfill dam deformation stability evaluation method based on multi-parameter analysis, it is related to water conservancy engineering technical field, and evaluation step is:S1, based on the data of monitoring point to rockfill dam is collected, data includes dam body deformation data and dam body contour data, data set is formed after data pre-processing;S2, dam body deformation data is converted into deformation time series according to time sequence, its fractal dimension is calculated by box counting method, and the mapping relationship between fractal dimension and rockfill dam deformation stability is established by combining historical data statistical analysis;S3, dam body contour data is imported into three-dimensional modeling software, and three-dimensional geometric model of rockfill dam is constructed.The application constructs comprehensive evaluation system, carries out correlation degree analysis and verification to fractal dimension, displacement strain index, obtains evaluation value based on weighted average method, intelligently divides stability grade, and provides intuitive decision basis for water conservancy engineering management.

This invention belongs to the field of shearing technology and discloses a staged simulation optimization method for the shearing process of non-oriented silicon steel disc shears. By dividing the shearing process into stages during simulation analysis, this invention breaks through the traditional one-time simulation analysis mode that only focuses on the overall result, achieving a refined description of the intrinsic evolution mechanism of the shearing process. Compared to the problem of overlapping effects between different stages in one-time simulation methods, this invention can distinguish the stress characteristics and damage evolution laws of each shearing stage at the simulation level, improving the pertinence and reliability of process parameter analysis results. This method mainly identifies and analyzes the stage characteristics of the shearing process based on simulation results. Compared to relying on stage detection or online monitoring methods in actual production processes, the implementation process is more convenient; at the same time, its analysis results meet the accuracy requirements of engineering applications and have good engineering applicability.

The invention relates to the technical field of knowledge management, in particular to a cardiovascular special nursing knowledge management and intelligent auxiliary method and system. The method comprises the following steps: acquiring and storing cardiovascular specialized nursing original knowledge data, executing text analysis and semantic processing, and generating a structured cardiovascular specialized nursing knowledge entry set; performing parameter analysis and weighted matching in combination with nursing demand information or patient characteristic parameters, and screening target nursing knowledge entries; and completing content combination and slot filling based on a preset nursing template, generating individualized cardiovascular specialized nursing guidance information, recording a nursing knowledge calling process and a generation result, and forming nursing behavior record data. According to the method, the accuracy and the individuation degree of calling the cardiovascular special nursing knowledge and the scientificity, the normalization and the intelligent level of nursing decision are improved.