2805 results about "Element analysis" patented technology

The invention relates to the technical field of press monitoring, in particular to a digital twinning-based three-dimensional monitoring system for a precision servo press, which comprises a physical layer sensing module for acquiring real-time operating parameters, environment variables and workpiece processing data of the press; the dynamic twin construction module constructs a total-factor digital twin, and simulates a force-heat-deformation coupling effect by using finite element analysis and a multi-body dynamics algorithm based on physical attributes and process parameters; the intelligent analysis center identifies a potential fault mode of the press machine and locates an abnormal source through multi-physics field simulation data in combination with an improved CNN-LSTM model; the three-dimensional visual interaction unit constructs an interactive immersive three-dimensional virtual scene, renders a running state and a processing process in real time, and generates a maintenance strategy; and the self-adaptive regulation and control unit predicts the residual life of the key component and dynamically adjusts parameters according to a maintenance strategy and real-time monitoring data. Therefore, the problems of single monitoring dimension, disjunction of maintenance strategies and the like in the prior art are solved.

The present invention relates to the technical field of heat sink structure design, and in particular to a micro-channel heat sink structure design method based on a multi-objective function. The method comprises the following specific steps: S1, constructing a general mathematical description of a topology optimization problem; S2, acquiring input conditions for a specific design scenario, and dividing a topology optimization design domain; S3, establishing a governing equation for a topology optimization model; S4, on the basis of an adjoint method, performing sensitivity analysis of a multi-objective function with respect to design variables; S5, solving the topology optimization model by means of a method of moving asymptotes (MMA); S6, obtaining a two-dimensional flow channel configuration of a heat sink on the basis of contour reconstruction, carrying out finite element analysis of a two-dimensional flow channel structure, and narrowing down the selection range of constraint conditions; and S7, on the basis of a two-dimensional finite element analysis result, constructing a corresponding pseudo-three-dimensional model, carrying out finite element analysis, and determining optimal constraint conditions to obtain a final topology-optimized heat sink configuration. Compared with traditional methods, the present invention can more efficiently solve the problem in respect of heat sink structure optimization under different scenarios.

The invention provides a method for evaluating the grouting water control effect of an underground water-sealed cave depot project. The method comprises the steps that firstly, grouting and geological parameters and hydrological monitoring data of a project area are obtained; establishing a three-dimensional seepage-grouting coupling model, and simulating the dynamic state of a seepage field by using a finite element analysis algorithm; then calculating the equivalent permeability change rate of the grouting affected zone based on a simulation result; constructing an evaluation index system, and performing quantitative evaluation by using a fuzzy comprehensive evaluation algorithm; and finally, generating a grouting parameter dynamic adjustment scheme according to an evaluation result. According to the method, scientific and accurate evaluation and engineering optimization of the grouting water control effect can be achieved, and the safety and economical efficiency of engineering are improved.

The invention discloses a thin-wall structure lightweight design method based on additive manufacturing, and belongs to the technical field of additive manufacturing, and the thin-wall structure lightweight design method comprises the following steps: S100, designing an initial structure based on function and performance mapping; s200, an additive manufacturing process knowledge base is constructed, and the adaptability of the additive manufacturing process is evaluated; s300, carrying out process and structure bidirectional coupling finite element analysis; s400, collaborative optimization of a process and a structure driven by a multi-objective optimization algorithm; s500, feature part manufacturing verification and design and process scheme iterative optimization are carried out; and S600, generating a design and process integrated scheme, wherein the integrated scheme comprises design parameters and manufacturing parameters. The technical problem that in the prior art, the structure optimization target and the manufacturing adaptive capacity are lack of collaboration can be solved.

The invention discloses a tunnel back break intelligent finishing and surrounding rock stability dynamic evaluation method and system, relates to the field of tunnel construction, and provides a tunneling-oriented back break intelligent finishing and surrounding rock stability dynamic evaluation method which integrates point cloud sensing, geological modeling, finite element analysis and deep learning prediction. And a closed-loop control process from identification, control, modeling, prediction and feedback is constructed. An over-excavation and under-excavation area is identified through a high-precision point cloud and a neural network, a trimming instruction is generated, a three-dimensional model and a support time sequence model are dynamically constructed in combination with geologic features, a variable parameter reduction method is introduced to realize more real stability analysis, and future displacement and a safety coefficient of surrounding rock are predicted by using deep learning. The method can improve the intelligent level of tunneling control and construction safety, and has remarkable engineering application value.

The present invention relates to the technical field of mechanical property testing and characterization. Disclosed are a method and apparatus for calculating a crack propagation life of an engine structure in vibration fatigue, which method and apparatus aim to obtain reliable fracture mechanics parameters and a crack propagation rate curve and provide an accurately quantified crack propagation life, so as to provide methodological guidance for the life assessment of reusable engines. The calculation method comprises: acquiring a time-domain random stress spectrum of stress responses in an assessment section in a finite element model of an engine structure; on the basis of the time-domain random stress spectrum, performing finite element analysis processing on a crack model of the engine structure, so as to determine fracture mechanics parameters of a cracked structure; performing a vibration fatigue performance test on a crack propagation rate model, which is set up according to a preset crack propagation mode, and determining, by using parameter identification, a target parameter value corresponding to the crack propagation rate model; and in combination with the parameter value corresponding to the crack propagation rate model and a preset critical crack length value, performing crack propagation life calculation, so as to obtain a target crack propagation life.

The invention discloses a digital twinning-based major engineering construction safety active control method, system and equipment, and belongs to the technical field of construction active control. The problems of low safety risk identification efficiency and inaccurate risk control means in the major engineering construction process are solved, major engineering construction site environment and structural feature data are obtained through space-air-ground-water multi-way intelligent means and equipment, a digital twinborn model of a real-time mapping construction site is established, and the safety risk identification efficiency of the major engineering construction site is improved. Correcting the digital twinborn model by using real-time data; a digital twinborn model is used as a basic model of finite element analysis, mechanical properties of different construction stages are analyzed, dynamic early warning is performed on an analysis result in combination with real-time data, a safety risk derivation model is established to perform real-time analysis on key problems such as a risk point location, a risk influence range and risk derivation prediction in the digital twinborn model, and the safety risk derivation prediction result is obtained. Data support is provided for engineering safety active control, an active control strategy model is established, a control strategy is output to a servo control device according to risk information, strategy dynamic adjustment is performed according to a real-time effect, and high-precision cooperative control of major engineering safety monitoring is realized.

The invention provides a pipe jacking construction digital twinning optimization system and method based on high-precision physical simulation, and relates to the technical field of underground pipe network pipe jacking construction. Construction data of multiple physical entities during pipe jacking construction are collected in real time through a physical simulation engine module and then transmitted to an established digital twin model, virtual mapping synchronously updated with the construction data of the physical entities is established, and an optimization and decision module optimizes construction parameters by adopting a joint simulation algorithm fusing finite element analysis (FEA) and computational fluid dynamics (CFD), so that the construction parameters are optimized. The construction feedback module realizes automatic parameter adjustment based on PLC control according to optimized construction parameters, the analysis report module analyzes time sequence data and generates a construction efficiency evaluation report, a stress concentration area is accurately simulated, the simulation precision is improved, high synchronization of a virtual model and physics is realized, and the precision and real-time performance of system execution are improved.

The invention relates to the field of construction engineering, in particular to a roadbed construction slope displacement monitoring system based on cloud computing. A sensor network is used for collecting roadbed construction data in a roadbed, wavelet transform is used for denoising the data, a dynamic time warping algorithm in a cloud computing unit is used for aligning time sequence data in the initial roadbed construction data, and the weight of each sensor data is dynamically distributed based on an entropy weight method. A hybrid prediction model is established based on an LSTM long short-term memory network and FEA finite element analysis, a slope stress field result simulated by FEA is used as a physical constraint layer of the LSTM, an attention layer is embedded in the physical constraint layer, hyper-parameters of the initial hybrid prediction model are optimized by using a Cs-Ant improved cuckoo-ant colony combinatorial algorithm, and a slope stress field is obtained. And inputting the feature roadbed construction data into the target Cs-FEA-LSTM hybrid prediction model for prediction. The manual analysis cost is effectively reduced, and the level of roadbed engineering full-period monitoring is improved.

The present application relates to the technical field of seismic performance evaluation for building structures, and in particular to a BIM-based system and method for evaluating the seismic performance of a building structure. The method comprises: acquiring BIM data of a target building structure, and extracting geometric features and material properties thereof; on the basis of the geometric features and the material properties, generating a finite element analysis model under multiple load cases; performing dynamic response simulation on the finite element analysis model to obtain key performance indicators under the load cases; and on the basis of the key performance indicators combined with preset evaluation criteria, outputting an evaluation result of the seismic performance of the building structure. The present application can improve the automation level, application scope and accuracy of seismic performance evaluation, and also realizes the comprehensive analysis of complex building structures.

The invention discloses a bridge structure optimization method based on BIM and a finite element method, and relates to the technical field of bridge structure optimization. According to the method, the finite element analysis model can be more accurately established, and the design precision is improved. Through finite element analysis and a digital simulation technology, structure response data is rapidly obtained, and design optimization is accelerated; the optimization of the final scheme is ensured by a multi-iteration optimization strategy, the extreme load response is predicted by introducing a machine learning algorithm, a high-risk area is identified in advance, and the overall performance is improved; based on a multi-scale analysis method, the durability and safety of the structure are comprehensively evaluated, weak links are identified, and long-term performance is guaranteed; meanwhile, the influence of environmental factors on material characteristics is considered, adjustment is performed according to climate data, the design scheme is closer to the actual environment, and durability is enhanced.

The invention provides an intelligent grabbing control method and system based on tactile perception, and the method comprises the steps: obtaining a tactile feedback signal through a sensor array of a humanoid robot, carrying out the frequency domain decomposition of the signal through a Fourier transform method, and carrying out the analysis of the pressure and deformation data of each contact point on the surface of a to-be-grabbed object, calculating to obtain frequency characteristic distribution of the tactile feedback signal; if the initial estimation value of the object rigidity gradient exceeds a threshold value, performing finite element analysis on the object rigidity gradient, and combining a time domain processing result of the tactile feedback signal to obtain object rigidity gradient distribution; carrying out probability modeling on the deformation field by adopting a Bayesian inference method according to the gradient distribution of the rigidity of the object, and carrying out iterative optimization on a modeling result to obtain dynamic update parameters mapped by the deformation field; and regenerating an action sequence of the end effector of the humanoid robot based on the optimized strategy according to a trigger condition of grabbing failure detection, and determining a final grabbing control parameter.

The invention relates to the technical field of coal mine disaster monitoring, in particular to a gas coal mine goaf coupling disaster monitoring method, an electronic device and a storage medium, and the gas coal mine goaf coupling disaster monitoring method comprises the following steps: obtaining comprehensive data of a goaf through a sensor network, and carrying out data preprocessing to obtain standardized data; constructing a digital twinborn model through a 3D modeling and geographic information system technology; performing data synchronization and model correction processing on the digital twinborn model, and optimizing parameters and states of the digital twinborn model; constructing a fluid-solid-heat multi-field coupling model through a computational fluid mechanics and finite element analysis method; constructing a risk assessment model through an analytic hierarchy process and a fuzzy comprehensive evaluation method; training a disaster early warning model by using a machine learning algorithm based on the standardized data and the risk assessment model; a digital twinborn model, standardized data, a risk assessment model and a disaster early warning model are integrated, and a visual interaction platform is constructed. According to the monitoring method, multiple disaster elements can be coupled and dynamically evolved, and the disaster prediction accuracy and timeliness are greatly improved.

The invention discloses a hydrogen fuel cell production management method and system based on a digital twinning technology, and relates to the technical field of digital twinning, and the method comprises the steps: collecting the production data of a hydrogen fuel cell in real time, carrying out the data preprocessing, and generating standardized data; based on the standardized data, constructing a digital twinborn model by utilizing finite element analysis and a computational fluid dynamics strategy, and training the digital twinborn model through historical data; building a reinforcement learning environment based on the trained digital twinborn model, defining a reinforcement learning agent, and generating an optimal control strategy; production parameters are adjusted according to the optimal control strategy, production data are fed back through the digital twinborn model, the optimization effect is verified regularly, and the digital twinborn model and the optimal control strategy are iteratively updated. According to the method, the optimal strategy is autonomously learned in the simulation environment through the reinforcement learning agent, the generated control strategy can dynamically adjust production parameters, efficiency is improved, energy consumption is reduced, quality is improved, and intelligent decision making and control are achieved.

The invention relates to an existing building glass curtain wall operation and maintenance method and system based on a digital base. The method comprises the following steps that curtain wall vibration response data, visible light image data and three-dimensional point cloud data are obtained; based on the curtain wall vibration response data, comparing the current modal parameter with the historical modal parameter, and determining the dynamic characteristics of the curtain wall panel; identifying the curtain wall apparent damage type and the corresponding damage degree based on the visible light image data; based on the three-dimensional point cloud data, a curtain wall live-action three-dimensional point cloud model is constructed and mapped into a numerical model, a local stiffness reduction coefficient is calculated based on curtain wall panel dynamic characteristics, curtain wall apparent damage types and corresponding damage degrees, and a local stiffness matrix of a corresponding unit or node in the numerical model is corrected; and performing finite element analysis on the corrected numerical model to realize performance evaluation and deduction of the glass curtain wall. Compared with the prior art, the method has the advantages that the performance change of the glass curtain wall can be accurately and dynamically sensed and predicted, and the like.

The invention discloses a spiral anchor foundation bearing effect evaluation method and system, and relates to the technical field of finite element analysis, and the method comprises the steps: building a soil body and spiral anchor finite element model, setting boundary conditions, and obtaining finite element data; according to the finite element data, a local damage variable is introduced based on a stress-strain degradation function, local shear band development is simulated, first damage data are generated, and the first damage data comprise a first stress-strain curve and a first local damage variable; layering the soil body, and optimizing the first damage data based on intra-layer constraints to obtain second damage data; calculating full-field stress, displacement and bearing capacity for effect evaluation based on a finite element solver according to the second damage data; the problem of inaccurate evaluation of the screw anchor effect caused by the nonlinear behavior and the layered heterogeneous effect of the soil body is solved.

The invention relates to the technical field of digital twinning, and particularly discloses a historical building structure evaluation system based on digital twinning, which comprises a multi-source data acquisition module, a dynamic digital twinning modeling module, a structure health evaluation module, an intelligent maintenance decision module and a collaborative optimization analysis module. According to the scheme, geometric, material and environment information of the historical building is captured, omnibearing monitoring of the historical building is realized through a digital twin modeling technology, an intelligent evaluation model is constructed in combination with finite element analysis and an SVM algorithm, a high-risk area is rapidly identified, and authenticity and accuracy of an evaluation result are ensured; a reinforcement learning algorithm is used to adapt to complex and changeable environmental requirements of historical buildings, a maintenance strategy is automatically generated, cooperation efficiency between modules is continuously optimized through collaborative optimization analysis, the overall operation performance is improved, evaluation precision is guaranteed, and meanwhile system resource consumption is effectively controlled.

The invention discloses a mass concrete intelligent temperature control system, and relates to the technical field of concrete temperature control, the system comprises a sensor monitoring module, a data collector, a data transmission module, a central control module, an execution mechanism and a data recording and remote monitoring module; by integrating the sensor monitoring module, the data collector, the data transmission module and the central control module, real-time monitoring and accurate analysis of key parameters in the concrete and in the construction environment are achieved, and a temperature and humidity prediction unit in the central control module can predict the temperature and humidity of the concrete by means of a finite element analysis method and a CFMH dynamic prediction formula. According to the method, the temperature and humidity trends of the concrete in different time and areas can be accurately predicted, the concrete quality problem caused by temperature and humidity fluctuation is greatly reduced, the quality stability of concrete construction is improved, a scientific and reliable decision basis is provided for constructors, the construction process is optimized, and the construction cost is reduced.

The invention relates to the field of thin-wall structure displacement field monitoring, and discloses a coupled functional unilateral inverse finite element cylindrical thin-wall structure displacement field monitoring method, which comprises the following steps of: performing discretization by adopting a four-node inverse shell unit, and arranging a sensor at a geometric center position of each unit; based on the basic mathematical model of the inverse finite element, establishing an overall pseudo-stiffness matrix and an overall pseudo-force matrix; and calculating to obtain a displacement field of the structure by solving a linear equation set formed by the overall pseudo-stiffness matrix, the overall pseudo-force matrix and the global displacement vector. According to the method, the structural displacement field is calculated by using the strain information measured at one side, and the global deformation is accurately and reversely deduced under the condition that only the local strain data is obtained by combining the advantages of finite element analysis and inverse problem solution. By optimizing local strain data solution, high cost and low efficiency of global strain measurement in a traditional method are avoided, and the method has remarkable practical advantages.

The invention belongs to the technical field of digital twinning, and discloses a hydraulic engineering-oriented digital twinning model dynamic construction and risk assessment method, which comprises the steps of dividing a hydraulic engineering into a static basic component area and a dynamic response area, accessing historical hydraulic engineering data, combining BIM and a finite element analysis technology, and carrying out dynamic construction and risk assessment on a digital twinning model. Constructing a structure model of the static basic component area and an agent model of the dynamic response area; combining the structured model with the proxy model to obtain the hydraulic digital twin; state data in the water conservancy digital twinborn body operation process are collected, and a twinborn state sequence is generated; constructing a water conservancy semantic map, and carrying out semantic binding on the water conservancy digital twin, the real-time water conservancy data and the control logic; dynamically updating a twinning state sequence when the node state of the water conservancy semantic map changes by adopting an event-driven strategy; and the response time efficiency and the emergency regulation and control capability of the water conservancy project are further improved.

The invention discloses a concrete structure crack image detection method and system based on deep learning. The method comprises the following steps: acquiring a multi-view image; performing spatial alignment according to the multi-view image to obtain a matched image sequence; performing image fusion according to the matched image sequence to obtain a fused image; performing semantic segmentation based on transfer learning according to the fused image and a preset neural network model to obtain a crack mask; according to the crack mask and the fusion image, skeleton extraction is carried out, and a preliminary crack network topology is obtained; optimizing the preliminary fracture network topology to obtain a fracture network topology; carrying out finite element analysis according to preset material attributes, a stress state and a concrete structure to obtain a stress distribution cloud picture; and according to the stress distribution cloud picture and the fracture network topology, carrying out space matching to obtain a stress fracture correlation model. The method can analyze the dynamic change of the concrete crack.

The invention relates to an intelligent building damage detection method based on machine vision. The method comprises the following steps: multi-modal data acquisition; preprocessing and feature enhancement: processing the visual data and the acoustic data; damage detection: designing a material constitutive driven GAN architecture, calculating and generating stress distribution of a crack by a generator through a differentiable finite element analysis layer, performing L2 loss constraint on the stress distribution and an ABAQUS simulation result, evaluating image authenticity and physical consistency by a discriminator by adopting a double-branch structure, and outputting damage parameters in cooperation with a lightweight YOLOv8-Nano detection head; acoustics-vision depth fusion detection: aligning a potential space through a double-flow cross-modal encoder in combination with cross-modal contrast learning, and preferentially processing hidden damage by using a gating fusion unit for dynamically calculating a fusion weight through material acoustic impedance; when the visual detection confidence coefficient is smaller than a set threshold value, triggering frequency domain mutation detection and spatial positioning of the acoustic mode; and edge-cloud cooperative processing.

The invention discloses an intelligent construction method, system, equipment and medium based on a digital twin tunnel, and aims to construct a high-precision physical entity model by fusing dynamic and static data in real time through multiple types of sensors so as to improve data acquisition comprehensiveness; based on tunnel-level, soil-level and ground building-level multi-level modeling and finite element analysis, fine mechanical stability simulation is realized; multi-dimensional data features are extracted by combining a convolutional neural network algorithm, security risks are evaluated, and a reinforcement scheme is optimized through dynamic iteration; a closed-loop regulation and control mechanism of data monitoring, numerical simulation and dynamic feedback is formed by utilizing a collaborative architecture of a sensing layer, a simulation layer and a display layer, so that environmental disturbance is effectively reduced, and construction safety is guaranteed; according to the method, digital twinning, BIM, finite element analysis and deep learning are fused, real-time monitoring and intelligent optimization of the whole construction process are achieved, efficiency and safety are remarkably improved, and influences on the surrounding environment are reduced.

The invention discloses a digital twin system architecture of a vertical shaft and a structural performance monitoring method. The method comprises the following steps: constructing a five-dimensional digital twin system framework suitable for a vertical shaft based on a shaft operation mechanism and performance monitoring requirements; establishing a shaft digital twinborn model with dynamic characteristics; a finite element proxy model is constructed through a virtual-real mapping technology in combination with a grid dimensionality reduction finite element analysis method, and rapid generation of the digital twinborn body is realized. According to the system, a three-dimensional operation platform is constructed based on a Unity 3D virtual engine, and efficient mapping and bidirectional interaction between twin and finite element simulation data are realized by adopting a radial basis function (RBF) proxy model. And real-time acquisition and online prediction are carried out on structural performance parameters in the shaft operation process. And dynamically updating the twinborn model according to a prediction result, and constructing a high-precision and light-weight digital twinborn evolution model, thereby realizing real-time observation of the stress change of the shaft and intelligent monitoring of the structural performance. The method can be widely applied to the fields of shaft safety assessment, maintenance decision making, intelligent mine construction and the like.

The invention provides a packaging and sintering evaluation method and device for a power semiconductor device, and the method comprises the steps: carrying out the non-destructive scanning through a high-frequency acoustic microtechnique, carrying out the correction through combining with a temperature-sound velocity relation model, achieving the real-time monitoring of a sintering process, and solving a problem that the transient change cannot be captured. Through frequency domain conversion and an improved inverse Fourier transform algorithm, precise reconstruction of the microstructure of the sintering interface is realized, and the limitation that the microstructure is difficult to evaluate in the prior art is overcome. Based on the reconstructed microstructure, a detailed three-dimensional geometric model is established, and time domain finite element analysis is performed, so that comprehensive thermal stress evolution data is obtained, and the defect of surface information of a traditional method is overcome. And quantitative evaluation is carried out by using the multi-dimensional feature space and the preset discrimination model, so that comprehensive analysis of the sintering quality is realized, and the defect of lack of comprehensive quantitative evaluation capability is overcome. Through organic combination of the steps, the accuracy and comprehensiveness of packaging and sintering evaluation are remarkably improved.

The invention relates to the technical field of material simulation models, and particularly discloses a finite element analysis and thermal expansion mismatch effect-based comprehensive simulation model construction method, which comprises the following steps of performing geometric model construction on a target material; constructing a geometric model: adopting modeling software to create the geometric model of the target material, and obtaining a thermal mismatch target area interface; parameter data of a target material are obtained for assignment, and then a target material grid is preprocessed; performing boundary condition constraint on the geometric model of the target material, and applying a temperature load; establishing a thermal stress corresponding mechanism for the geometric model of the target material, calculating to obtain thermal stress values of the unit grids, and converting the thermal stress value on each unit grid into a cloud picture in a color manner based on the thermal stress values of the unit grids to obtain a thermal expansion mismatch effect comprehensive simulation model; the quantitative analysis capability of the thermal stress difference of multiple materials is realized; potential stress concentration areas caused by thermal expansion mismatch can be identified.

The invention discloses a method and a system for predicting and monitoring frame fatigue based on twinning of the Internet of Vehicles. The method comprises the following steps: analyzing a vehicle use scene and a working condition ratio based on historical data of the Internet of Vehicles; carrying out a frame real vehicle load test, and converting a strain-time history into a load-time history in combination with static loading calibration; performing weighted combination on each load history according to a working condition ratio to obtain a weighted composite load-time history; reconstructing a stress-time history of each measuring point based on finite element analysis, and constructing a stress cyclic spectrum by adopting a rain flow counting method; calculating the fatigue life of the frame by combining a stress-life method and a Miner linear damage criterion; and constructing a frame twinborn model corresponding to the real vehicle at the cloud, accessing vehicle operation data in real time, dynamically updating a stress process and fatigue damage, calculating the residual fatigue life, and triggering early warning when the life is lower than a threshold value. The method can achieve the precise evaluation and online monitoring of the fatigue life of the vehicle frame, and is suitable for the durability design and structural health management of new energy commercial vehicles.

The invention discloses a brittle material laser cutting thermal stress control method and system, and the method comprises the steps: obtaining real-time temperature distribution through infrared thermal imaging, combining finite element analysis and material characteristic dynamic data, constructing a thermal stress and fracture relation model, carrying out the iterative calculation of a thermal stress out-of-control threshold through a lambda algorithm, and determining a regulation boundary condition. According to the boundary condition, laser parameters are optimized, synchronous cooling airflow is introduced, the temperature gradient is dynamically controlled through an airflow pressure adjusting algorithm, historical data are processed through a convolutional neural network, the optimal laser parameter combination is predicted, in the cutting process, the microcrack diffusion state is monitored in real time, and auxiliary technological parameters are finely adjusted when necessary. The problem of fracture caused by out-of-control thermal stress in laser cutting of the brittle material is effectively solved, the cutting quality and efficiency are improved, and a new technical scheme is provided for precision machining of the brittle material.

The invention discloses an optimization design method of a large-model-driven mechanical part, which comprises the following steps of: performing knowledge retrieval according to a design task and a constraint condition, and generating text description of a structure design scheme by fusing the retrieved knowledge through a large-scale language model (LLM); the LLM performs task decomposition and modeling code mapping on the structure design scheme described by the text, and generated modeling codes are directly executed by modeling software to generate a three-dimensional model; the LLM generates a reasoning track and calls a finite element analysis tool set to perform performance analysis on the generated three-dimensional model; and according to optimization requirements and design constraints, the LLM optimizes the three-dimensional model to generate an optimal three-dimensional model. The invention discloses an optimization design system of a large model driven mechanical part. The optimization design system comprises a design scheme generation module, a parametric modeling module, a design scheme verification module and a structure parameter optimization module. The method and the system provided by the invention can save code quantity, reduce manual intervention and improve design efficiency.

The invention discloses a multi-axial fatigue and reliability analysis method for a semi-submersible wind turbine supporting structure, which comprises the following steps of: firstly, determining an input load power spectral density function of each part of an offshore semi-submersible wind turbine by combining a motion theory, a wind speed spectrum theory and a wave spectrum theory of the offshore semi-submersible wind turbine; carrying out finite element analysis on the offshore wind turbine in a frequency domain according to the load power spectral density function, determining a dangerous point through a frequency domain method, calculating damage by using a W-B critical plane method, predicting the fatigue life of the dangerous point in a time domain, verifying that wind-induced damage is far greater than wave-induced damage, and finally solving a failure probability curve of the wind turbine support structure. And multi-axial fatigue and reliability analysis of the semi-submersible wind turbine supporting structure is completed. According to the method, the randomness of the marine environment and the calculation interval of the wind turbine load can be well unified, the accuracy of predicting the fatigue life of the wind turbine supporting structure is improved, and the method has universality for any type of wind turbine supporting structures and is easy and convenient to operate and wide in application range.