2604 results about "Geometric modeling" patented technology

The invention discloses an electromechanical system fault pre-diagnosis method and system based on digital twinning. The method comprises the following steps of obtaining multi-source data in an electromechanical system operation process; preprocessing the acquired multi-source data, wherein the preprocessing comprises data cleaning, normalization processing and feature extraction; and on the basis of the preprocessed multi-source data, an electromechanical system design drawing, a three-dimensional geometric model, material attributes and a kinetic equation are fused, and a digital twin model is constructed. According to the invention, through a digital twin model dynamic calibration and prediction algorithm, early abnormity of the equipment is identified in advance, the fault probability and the residual life are output, and non-planned shutdown is reduced; by constructing a cross-physical domain fault feature system and fusing model simulation and actual measurement data, the potential fault identification accuracy is improved, and the missed diagnosis rate is reduced; by calibrating parameters of the digital twin model in real time, the method adapts to nonlinear changes of equipment, ensures high-fidelity mapping of the model, and improves fault prediction precision.

The invention relates to the technical field of target detection, in particular to a robot three-dimensional environment sensing method and device based on deep visual learning, and the method comprises the steps: collecting visual data based on a sensing system carried by a robot, carrying out the synchronous processing, extracting the spatial structure characteristics of a synchronous visual data stream and a preliminary semantic segmentation map, and carrying out the recognition of a target image; combining the spatial structure features with the preliminary semantic segmentation map to generate a geometric semantic feature map; extracting and optimizing local, regional and global features of the geometric semantic feature map, and performing three-dimensional modeling processing according to a multi-scale feature tensor to generate a three-dimensional geometric model; and carrying out fusion optimization on the structure information of the three-dimensional geometric model and the geometric semantic feature map, and carrying out verification processing based on a verification framework to obtain three-dimensional environment perception data. Through deep visual learning and visual data fusion, the defects of insufficient accuracy and limited deep semantic understanding ability in complex three-dimensional environment perception in the prior art are solved.

A dynamic optimization system for energy consumption of a refrigeration house based on digital twinning is characterized by comprising a data acquisition module used for acquiring basic structure data of the refrigeration house, technical parameters of a refrigeration system, real-time operation data and historical operation data, preprocessing the data and then outputting a standardized multi-dimensional real-time data stream; the model construction module is used for constructing a 3D geometric model, a thermodynamic transfer model and a refrigeration system mathematical model according to the multi-dimensional real-time data flow, performing machine learning calibration on model parameters through historical operation data, and performing fusion to construct a refrigeration house digital twin model; the prediction analysis module is used for predicting future energy consumption demand and load change according to the refrigeration house digital twin model and the real-time operation data, and outputting an energy consumption prediction result and a load analysis report; a strategy generation module; an execution feedback module; and a learning optimization module. Overall energy consumption of the refrigeration house is reduced, energy utilization efficiency is remarkably improved, and goods storage safety is guaranteed.

The invention discloses a territorial space planning optimization method and system based on three-dimensional modeling, and relates to the technical field of three-dimensional modeling, and the method comprises the steps: obtaining multi-source territorial space data, constructing a three-dimensional space data set, carrying out the three-dimensional geometric modeling, and generating a territorial space three-dimensional model; carrying out multi-dimensional space analysis on the land space three-dimensional model, obtaining a space conflict feature set, carrying out planning constraint, and formulating a space optimization suggestion; executing the space optimization suggestion to perform three-dimensional dynamic modeling, generating a multi-time sequence planning simulation result to perform space planning evaluation, generating a land space planning score, performing planning compensation based on the backtracking space optimization suggestion, updating the space optimization suggestion, and obtaining a space planning optimization scheme. The technical problem that in the prior art, land space planning depends on two-dimensional data, the space conflict and the dynamic evolution process are difficult to comprehensively recognize, and the planning scheme is insufficient in scientificity is solved, and the technical effect of improving the space conflict recognition precision and the planning decision scientificity is achieved.

The invention relates to the technical field of digital twinning control, and discloses a composite structure prefabricated segment digital twinning-adaptive assembly correction method and system, and the method comprises the steps: reading BIM geometric model data, and constructing an assembly reference coordinate system and a digital twinning geometry of a prefabricated segment; composite data are collected in real time, and end tooth groove boundary feature point cloud is extracted; matching the actually measured point cloud with the digital twinborn geometry through a dynamic point cloud registration technology, calculating a six-degree-of-freedom pose error vector, and generating a predicted total pose error vector in combination with a pre-constructed pose drift prediction model; based on the error vector, a mechanical fine adjustment jack is driven to execute position and posture adjustment until the position and posture are converged, and then tooth groove precise meshing and mechanical locking are completed; according to the method, through the synergistic effect of the dynamic mapping of the digital twinborn model and the self-adaptive correction algorithm, high-precision dynamic correction of the multi-combination structure segment assembly process is achieved on the premise that an original mechanical connection structure is not changed.

The invention relates to the technical field of electrical design and intelligent optimization calculation, and discloses a capacitor structure design optimization method and system and a storage medium. The method comprises the following steps: carrying out modeling processing on capacitor structure parameters, and dividing a parameter space to obtain an initial model set; obtaining a multi-physical field simulation model according to the geometric model and the material attributes; obtaining performance indexes such as capacitance value, heat distribution and stress based on the simulation model; setting a target function and constraint conditions, and operating an optimization algorithm to obtain an optimal solution set; performing feedback control processing on an optimization result, and analyzing a convergence path to obtain a structure parameter; according to the invention, the execution efficiency of capacitor structure design optimization is improved, and the consistency and stability of the optimization process and the performance prediction result are improved.

The invention discloses a BIM model automatic generation method and system based on point cloud data, and belongs to the field of building information modelling, and the transmission method comprises the steps: obtaining original point cloud data, and employing a filtering algorithm based on point cloud density adaptive adjustment to carry out the preprocessing of the point cloud data; constructing a voxel octree structure for the preprocessed point cloud data, and performing semantic classification on the point cloud; geometric modeling is carried out based on the segmented point cloud subsets, and a fitting algorithm is adopted to carry out shape completion on a point cloud area; semantic annotation is carried out on the components subjected to geometric reconstruction, a corresponding relation between component types and spatial attributes is constructed, fusion features based on a point feature histogram and a local curvature are adopted, and classification is carried out; a standard BIM component family is converted, and a three-dimensional BIM model is constructed through the mapping relation. According to the method, the voxel octree data structure and the deep semantic segmentation neural network model are combined, division and semantic recognition are performed on the point cloud data, the intelligent degree of the model is improved, and manual intervention is reduced.

A solid structure deformation and damage analysis method based on a quasi-bond finite element method comprises: carrying out geometric modeling on a target structure body, and distribution and subdivision to generate a grid of a traditional finite element method; dividing the target structure body into a finite element region and a quasi-bond region, and calculating a finite element region system stiffness matrix and a quasi-bond region system stiffness matrix to obtain an overall stiffness matrix of the target structure body; setting a boundary condition for the target structure body, applying an external load, and calculating a system force matrix under current load and boundary state; and judging a quasi-bond breakage condition according to a node trial displacement, then calculating a node displacement of the structure body and an equivalent damage parameter at each node, and outputting cloud charts of a displacement field and an equivalent damage field.

The invention provides a spacecraft full-cycle monitoring and operation and maintenance decision-making system based on digital twinning, and belongs to the field of spacecraft full-life-cycle intelligent operation and maintenance. Structural data and environmental data are monitored in real time through a multi-source sensor network deployed on a spacecraft structure; fusing physical entity monitoring data and damage evolution rule virtual data in a twin database, constructing a structure damage resistance and mechanical property evaluation model, and executing geometric modeling, physical attribute analysis, behavior response simulation and damage evolution rule modeling; based on a simulation result of the virtual model, life prediction and reusability evaluation are carried out, and an operation and maintenance decision instruction is generated; and feeding back the operation and maintenance decision instruction to the physical entity to execute control, and updating state data in the twin database to perform iterative optimization. According to the method, full-scene coverage from design demonstration to scrap recovery is supported, the problem of stage splitting in the traditional technology is solved, and a closed-loop optimization mechanism is formed through real-time interaction between the physical entity and the virtual model.

The invention discloses a water conservancy facility full-period informatization management method and system based on digital twinning, and relates to the technical field of water conservancy informatization management, and the method comprises the steps: collecting water conservancy facility data, constructing a water conservancy facility digital twinning model, constructing an interactive structure body through employing three-dimensional geometric modeling, topological coding, material attribute and operation state fields, and constructing a water conservancy facility digital twinning model. Node mapping, attribute inheritance and time evolution rules are established; on-site progress, quality and deviation data are collected through a construction period sensing device, a state-driven mapping mechanism is designed, various data are dynamically mapped to a digital twin model of the water conservancy facility, and a structure-environment collaborative sensing mechanism is constructed in an operation stage; based on the digital twinborn model data of the water conservancy facility, a risk identification model is established, and the dam break risk, gate clamping stagnation, pump station failure and channel clogging are predicted. According to the method, linkage of water conservancy facility multi-source sensing, digital twin mapping and risk identification is realized, and the operation safety monitoring precision and the regulation and control efficiency are 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 curve tunnel deformation monitoring data fusion processing method based on a multi-station robot, and belongs to the technical field of tunnel measurement, and the method comprises the steps: obtaining tunnel original point cloud data collected by a plurality of mobile robots and corresponding initial pose data, and constructing a multi-station dynamic unified coordinate system; performing preliminary registration based on a tunnel structure feature point set in the extracted tunnel original point cloud data to generate a preliminary fusion point cloud; performing weighted fusion on the preliminary fusion point cloud according to the fusion error distribution parameter to generate a final fusion point cloud; performing geometric modeling on the final fusion point cloud to generate a deformation monitoring reference model; performing comparative analysis on the deformation monitoring reference model and the tunnel design model to obtain a deformation distribution diagram; and generating a deformation trend prediction report. A unified coordinate system is constructed, multi-source point clouds are subjected to weighted fusion, and time sequence prediction is carried out, so that high-precision three-dimensional modeling and dynamic deformation trend early warning of the curve tunnel can be realized.

The invention discloses a mobile robot path planning method and system based on a circular trajectory control obstacle function, and aims to realize trajectory smooth control in an obstacle avoidance process. Firstly, an envelope circle is used for modeling an obstacle, an actual boundary is approached in a continuous and simple geometric form, and the calculation complexity of collision detection is reduced. Secondly, designing a control obstacle function based on a circular trajectory, constructing a derivable constraint in combination with a geometrical relationship between a tangent line and an obstacle boundary, and achieving trajectory smoothing, reducing speed fluctuation and prolonging the service life of an execution mechanism while guaranteeing a safe distance. For disturbance caused by factors such as ground unevenness, historical data are learned by using a Gaussian process, the disturbance trend is predicted in real time, and the motion stability is improved. And finally, through nonlinear optimization solution, generating control input with safety, continuity and disturbance adaptive capability. According to the method, geometric modeling, safety constraint, disturbance prediction and a dynamic adjustment mechanism are fused, and the safety and adaptability of robot path planning are remarkably enhanced.

The invention relates to the technical field of precision machining, and particularly discloses a complex curved surface precision machining method based on tool path optimization, which comprises the following steps: S1, acquiring a geometric model of a curved surface to be machined and tool kinetic parameters; s2, the optimal machining step length, the cutter roll angle and the feeding speed are calculated in real time according to the geometric features of the curved surface and the dynamic parameters of the cutter; s3, generating a self-adaptive tool path based on the dynamic optimization parameters in the step S2; s4, synchronously monitoring the cutting load in the machining process, and dynamically correcting cutter path parameters according to load feedback; and S5, outputting the optimized tool path instruction to the numerical control machine tool to execute machining. By calculating the Gaussian curvature and the average curvature of the curved surface in real time, dynamically adjusting the machining step length and the feeding speed, and automatically reducing the step length and reducing the feeding speed in a curvature sudden change area, the residual height of a steep area is controlled within a precise standard range, and the surface roughness is reduced by more than 30% compared with that of a traditional method; and the consistency of machining precision of each area of the complex curved surface is ensured.

The invention provides a reservoir bank slope deformation body instability volume prediction method, which comprises the following steps: respectively acquiring earth surface displacement and rock mass internal deformation data through a millimeter wave radar and a tilt angle sensor, and after processing through an adaptive noise decomposition algorithm, identifying a key deformation area and generating a data set. And performing space-time alignment on the data by using the engineering coordinate system and the topological relation to generate a fusion matrix. And reconstructing a potential slip crack surface geometric model in combination with slip crack surface features of historical cases, and calculating instability volume probability distribution by adopting Monte Carlo simulation. And finally, inputting the multi-dimensional data into the space-time prediction model, and outputting an instability volume prediction result with probability distribution. According to the invention, the accuracy and reliability of the prediction result can be improved, and scientific basis and technical support are provided for safety monitoring and disaster early warning of the reservoir bank slope.

The invention relates to the technical field of CAD drawing optimization, and discloses a CAD drawing optimization method based on parameterized design. The method comprises the steps that a design constraint condition set is received, and geometric constraint parameters and engineering constraint parameters in the design constraint condition set are extracted; generating an initial geometric topological structure according to the geometric constraint parameters, and performing parameterized mapping on the structure in combination with the engineering constraint parameters to form a parameterized geometric model; identifying key feature nodes in the model, dynamically associating the key feature nodes with engineering constraint parameters, and constructing a parameter-driven relation network; and iteratively optimizing the parameterized geometric model through the network to generate an optimized geometric model meeting a design constraint condition set. According to the method, close association of geometry and engineering constraints is achieved, repeated design modification is reduced, efficiency and accuracy are improved, the design standardization degree can be improved, collaborative design is facilitated, and the method is suitable for CAD drawing design of complex products.

The invention relates to the technical field of transformer simulation, in particular to a simulation system and method for a temperature rise field of a dry-type transformer. The method comprises the following steps: acquiring geometric parameters of an iron core lamination of the dry-type transformer to be simulated, spatial arrangement information of a winding and a positioning relation of an insulating component to form structural design data; the method comprises the following steps: constructing three-dimensional geometric modeling data based on structural design data, importing the three-dimensional geometric modeling data into a finite element electromagnetic simulation platform, setting a power-on condition of an excitation winding, and applying rated current or voltage, so as to obtain local magnetic flux density distribution data at each iron core lamination position in a whole operation period. According to the method, on the basis of three-dimensional structure data, three physical processes of an electromagnetic field, a thermal field and a fluid field are fused, a high-precision local heat source model and a dynamic temperature rise prediction model are constructed, and geometry-material-boundary all-parameter modeling is achieved from the whole structure of an iron core lamination, a winding and an insulation assembly.

The invention provides a grouting simulation method and system based on time sequence interaction and self-adaptive grid reconstruction, and relates to the technical field of grouting engineering.The grouting simulation method comprises the steps that monitoring data of the grouting construction process are obtained, the monitoring data are input into a grouting diffusion prediction model, a grouting pressure prediction value is output, and a series of prediction responses are conducted based on the grouting pressure prediction value. Obtaining a grouting pressure predicted value, a boundary point set of the grouting diffusion area, the area and the volume of the grouting diffusion area and a diffusion response result of the pressure distribution diagram; constructing a geometric model of the grouting area based on the diffusion response result, and performing grid unit division and grouting diffusion area mapping on the geometric model; and performing local grid encryption and reconstruction on the grid units according to a density control rule to obtain a structured grid data model, adaptively updating the structured grid data model by using real-time monitoring data, and performing real-time visual grouting optimization control. According to the invention, the high-precision prediction response of grouting is improved.

The invention belongs to the technical field of geometric pretreatment in computer aided engineering (CAE), and particularly relates to a dirty geometry restoration method for a complex three-dimensional geometric model, which comprises a dirty geometry detection and restoration module based on heuristic rules and geometric topology analysis. By means of a multi-model collaborative alignment and bonding mechanism, high-precision assembly between parts is achieved through geometric feature matching and adjacent domain self-adaptive adsorption; acquiring material attributes provided by the simulation platform, and performing accurate cutting and boundary reconstruction on an intersection domain based on an intersection domain intelligent segmentation algorithm of the material attributes to ensure correct mapping of boundary conditions of a physical field; a geometric Boolean processing engine iterative learning mechanism of a general merging algorithm is integrated, and a high-quality model for simulating a grid is generated through multi-round iterative optimization. According to the method, double challenges of internal dirty geometry of a single model and derivative dirty geometry of intersection / adjacent areas among multiple bodies are solved, and key physical attributes and topological continuity of electromagnetic signal links are ensured and are completely reserved during repair.

The invention provides an automatic operation process management method and device based on multi-sensor fusion, and relates to the technical field of automatic processes, and the method comprises the steps: constructing an instrument pose flow and operation field geometric model under a unified coordinate system through unified timestamp alignment and spatial geometry solution of multi-source sensor data; semantic segmentation and three-dimensional reprojection are combined to generate a shielding probability graph, cross-channel compensation reconstruction is carried out, and the image integrity is improved. And forming a conflict risk set through voxel field discretization and short-time prediction, and performing combined solution with standardized operation process constraints to generate a scheduling instruction and a safety time window. And finally, mapping the image, the pose and the physiological signal to a knowledge graph, and outputting consistency judgment and deviation correction suggestions in combination with a time sequence attention recognition process node. According to the method, the problem that the operation process management is not accurate enough due to the problems of view overlapping and the like of multi-source sensor data can be solved.

The invention relates to the technical field of automobile design, and particularly discloses an automobile wind resistance optimization design method based on a machine learning model, and the method comprises the steps: collecting data of different automobile types, and carrying out the cleaning and standardization processing; constructing a wind resistance prediction model, training the model by using the preprocessed data, and minimizing a prediction error by adjusting model parameters; key design variables are selected, the variation range of the key design variables is determined, and a parameterized model is constructed; selecting sample points in a design variable space, generating a corresponding geometric model, calculating a wind resistance coefficient and establishing a sample point database; dividing sample point data into a training set and a test set, optimizing a machine learning model, searching an optimal solution in combination with an optimization algorithm, and iteratively updating the model by increasing sample points until the precision requirement is met; an optimal design variable combination is determined, an optimized automobile geometric model is generated, CFD simulation verification is carried out, and a design scheme containing detailed parameters and optimization results is output.

The invention discloses a virtual assembly and anti-collision simulation method for a double-swing-head five-axis numerical control machine tool, and the method comprises the following steps: S1, building a geometric model of the double-swing-head five-axis numerical control machine tool based on a machine tool kinematic model, and the geometric model comprises parameterized three-dimensional models of a main shaft part, a swing head mechanism, a workbench and a machine tool body; s2, according to the constraint relation of the kinematic chains of the machine tool, an assembly hierarchical relation is established in the virtual environment, and virtual assembly of all parts is achieved through dynamic constraint driving; s3, on the basis of a machine tool kinematics forward and inverse solution algorithm, simulating the motion trail of the double swing heads in the five-axis linkage process; s4, through a real-time collision detection algorithm, detecting interference conditions among the cutter, the swing head, the workpiece, the clamp and the machine tool body, and generating an anti-collision early warning signal; and S5, optimizing a motion path of the machine tool in combination with a simulation result, and outputting a collision-free machining code. The assembly precision can be improved, and the physical debugging cost can be reduced.

The invention discloses an aircraft pose vision measurement method based on key points, and relates to the field of vision measurement, and the method comprises the steps: obtaining an aircraft image through machine vision; on the basis of the YOLO-v7 network, constructing an attention-enhanced target detection network; inputting the aircraft image into the attention-enhanced target detection network to obtain bounding box information; cutting the aircraft image by using the bounding box information to obtain an aircraft target image; constructing a key point extraction network; inputting the aircraft target image into the key point extraction network to obtain a key point coordinate; constructing a pose measurement network; and inputting the key point coordinates into the pose measurement network to obtain an aircraft pose measurement result. According to the invention, geometric modeling and end-to-end characteristics can be unified, the measurement precision is improved, and the ideal effect of balance between precision and robustness can be achieved.

The invention belongs to the technical field of simulation analysis, and particularly relates to a medium-high voltage switch cabinet internal humidity inversion calculation method based on simulation analysis, which comprises the following steps: establishing a geometric model of a switch cabinet, importing the geometric model into finite element simulation software to obtain a simulation analysis model, adding each physical field and computational domain and boundary conditions thereof, and calculating the internal humidity of a medium-high voltage switch cabinet. All the physical fields are coupled, and mesh generation is carried out; performing numerical solution on the simulation analysis model by using a transient solver to obtain a temperature and humidity distribution condition in the switch cabinet; the simulation analysis model is optimized, a simulation data set is constructed, and a PINN is trained; based on the environment temperature and humidity and the operation current collected in the actual operation of the switch cabinet, the trained PINN is used for prediction, and the steady-state relative humidity of the current transformer is obtained. According to the invention, based on the limited boundary monitoring data, efficient and accurate reconstruction of the humidity field of the key area in the switch cabinet is realized, and a feasible path is provided for equipment state sensing and condensation risk early warning.

The invention provides a self-adaptive spraying mechanical arm based on multi-mode perception and a control method of the self-adaptive spraying mechanical arm. The method comprises the steps that multi-source perception data of a to-be-repaired area is obtained through a dual-mode vision system and a laser scanning device, a two-dimensional repairing area segmentation map is generated, and space registration and local geometric modeling are achieved in combination with three-dimensional point cloud; on the basis of local geometric features extracted by the model, retrieving matched process parameters from the knowledge graph, generating a digital spraying instruction set containing tracks, postures and dynamic process parameters, and performing simulation verification in a digital twin environment; the mechanical arm state and the virtual model are synchronized in real time in the execution process, the paint film thickness is dynamically monitored, and compensation adjustment is triggered; and after spraying is completed, the coating quality is detected, and a result is fed back to the knowledge graph to update the parameter mapping relation. According to the method, closed-loop control from sensing, decision making, execution, evaluation to learning is achieved, and the spraying uniformity, the self-adaptability and the intelligent level under the complex working condition are improved.

The invention provides a method and a system for actively monitoring, regulating and controlling a clean room, which are characterized in that environmental parameters in the clean room and spatial state information of a dynamic object are acquired through cooperation of a fixedly arranged sensor and a sensor carried by a mobile device, and the environmental parameters comprise airflow velocity, temperature and humidity, pressure difference, particulate matter concentration, illuminance and the like; the dynamic objects comprise positions of the personnel and the equipment and geometric models of the personnel and the equipment. And cleaning and fusing the collected data to generate a standardized parameter sequence with a time label, and constructing a three-dimensional dynamic environment model by combining a clean room structure and dynamic object information to realize grid mapping and visual management of environment parameters in the model. And on the basis of the model, an environment state change trend is predicted, risk grade evaluation is executed, a hierarchical regulation and control instruction is generated, closed-loop regulation and control and parameter adaptive adjustment of the clean room environment are finally realized, and the intelligent and refined level of clean room environment regulation and control is improved.

The invention discloses a light beam vector calibration method for an on-machine measurement system of a spectral confocal sensor. The method comprises the following steps: establishing a coordinate system of the on-machine measurement system; calibrating the pose of the sensor; after calibration, a sensor is used for conducting standard ball surface scanning at a plurality of positions, and the zero point coordinate of the sensor at each position and the corresponding distance value measured by the sensor are recorded; establishing a calibration model and a nonlinear equation set according to the coordinate space relationship of the measurement points, and constructing a complete nonlinear optimization objective function to calibrate a light beam vector; and solving the target function by using a hybrid optimization algorithm, and finally obtaining an accurate sensor beam vector and a standard ball center coordinate. According to the light beam vector calibration method, the geometric model with the direction consistency constraint is introduced, the genetic algorithm and the L-M algorithm are used in a combined mode, the stability, robustness and calculation precision of the calibration method are improved, and the method is suitable for sensor pose calibration scenes in various on-machine measurement systems.

The invention relates to the technical field of torque converters, in particular to a hydrodynamic transmission power chain optimization method and system.The method comprises the steps that a hydrodynamic torque converter parameterized geometric model is built, and a pump impeller blade outflow angle, a guide wheel runner input / output angle, turbine blade geometric parameters and the relative position of a pump impeller and a turbine are set as design variables; based on CFD three-dimensional flow field simulation, a k-epsilon model is adopted for rapid analysis, an SST model is adopted for transient simulation, and simulation data under different variable combinations are obtained; training a BP neural network by using the simulation data, inputting each design variable, and constructing a multi-target optimization model with maximization of efficiency and minimization of noise as targets; a design variable combination is selected in the Pareto optimal solution set, a model is reconstructed, and an optimized hydraulic torque converter is obtained; according to the method, the problems that the design optimization efficiency of the hydraulic torque converter is low, the parameter adjusting period is long, and good compromise between the transmission efficiency and noise suppression is difficult to obtain can be solved.

The invention provides a construction method and system of a rock-soil shear strength parameter prediction model, and relates to the technical field of model construction.The construction method comprises the steps that CT scanning data of a real rock-soil sample is obtained and preprocessed, and an irregular three-dimensional particle set for geometric modeling is obtained; performing particle surface roughness modeling analysis on the three-dimensional particle body set to obtain a surface roughness coefficient set of the three-dimensional particle body set; performing particle size cumulative distribution function segmentation processing and fractal dimension control on the surface roughness coefficient set to obtain a structure grading sample set; constructing a THMC multi-field coupling model based on the structure grading sample set to obtain a working condition particulate matter physical response parameter set; and performing a simulation experiment on the working condition particle physical response parameter set, and performing deep neural network modeling processing based on an experiment result to obtain a strength response model capable of predicting the cohesive force and the internal friction angle of the rock-soil body under any working condition input. According to the invention, the prediction efficiency and accuracy are significantly improved.

The invention relates to an implicit voxel Boolean subtraction optimization method in five-axis machining simulation. According to the method, an implicit tool geometric expression model based on a symbolic distance function is constructed, and a dynamic voxel modeling technology with a layered structure is combined, so that efficient interactive modeling of a material removal process between a tool and a workpiece is realized. The whole process of the method comprises four key stages of spatial positioning, vertex interference detection, projection correction and grid reconstruction, and can cope with geometric modeling challenges caused by continuous motion of a multi-degree-of-freedom and multi-attitude cutter. A dynamic block loading mechanism and a local state synchronization strategy are introduced, so that the real-time response capability of Boolean subtraction operation under complex working conditions is effectively improved, and meanwhile, the continuity and integrity of machining geometric boundaries are kept. The method has good expandability and robustness, obviously reduces space-time complexity of calculation on the basis of keeping geometric surface continuity and topological correctness, realizes millisecond-level response time in an experiment, and has a good application prospect. The method is widely applied to virtual machining simulation and intelligent process verification systems of complex free-form surface parts such as aero-engine blades and automobile structural parts.