1367 results about "Geometric modeling" patented technology

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 relates to the technical field of computer-aided engineering, in particular to a nonlinear efficient iterative solving method for thermal strain load, which is used for solving an obtained finite element equation by using a modified Newton-Raphson method and comprises the following steps of: firstly, establishing a geometric model to be analyzed and performing grid division; the method comprises the following steps: firstly, setting a model to be analyzed, then setting boundary conditions and temperature field change conditions of the model to be analyzed, finally, inputting the conditions into an algorithm solver, solving a nonlinear equation set, iteratively inputting a load continuously according to a modified Newton-Raphson method in the solving process, calculating node displacement until convergence, and solving stress-strain conditions in the welding process according to a material constitutive relation. In the solving process, by judging the size of the two norms of the displacement increment obtained in the adjacent increment step heuristic stage, the convergence of nonlinear solving of the structure is enhanced through the calculation mode, and the solving speed of the nonlinear problem in the thermal elastic-plastic constitutive structure is increased.

The invention relates to the field of computer graphics, reverse engineering and additive manufacturing, discloses a multi-modal fusion and physical constraint three-dimensional point cloud geometric modeling system and method, and aims at overcoming the defects that traditional three-dimensional reconstruction entity attributes are missing, key features are prone to being lost, semantic understanding does not exist, and process automation is low. The system comprises a point cloud preprocessing module, a semantic segmentation and recognition module, a mixed geometric reconstruction module, a multi-component assembly and physical constraint solution module and an entity model output module. The method comprises the following steps: denoising and sampling an original point cloud, realizing semantic and instance double segmentation through a Point Net + + network, endowing a geometry-function composite label, completing hybrid reconstruction through improved Poisson reconstruction, parameterized B-Rep fitting and standard component library matching, and outputting a multi-format engineering available model after physical constraint verification and automatic correction of a violation model. According to the method, automatic, high-fidelity and high-practicability conversion from the point cloud to the engineering-level entity model is realized, and the method is adaptive to multiple industrial application scenes.

The invention discloses a tire finite element modeling and multidirectional rigidity optimization method and system based on characteristic lines. The method comprises the following steps: extracting tire section characteristic lines from a three-dimensional digital model; introducing the tire section characteristic line into a finite element analysis environment, generating a three-dimensional tire geometric model by rotationally scanning the characteristic line, and performing grid division on the model; setting tire material attributes, performing zoning setting on the model according to a tire crown, a tire shoulder and a tire side wall, and setting tire thickness based on zoning; applying a constraint boundary condition at the center of the tire, and establishing a contact form of the tread and the ground; a progressive inflation pressure load is applied, the deformation state of the inflated tire is calculated, and longitudinal rigidity, radial rigidity and lateral rigidity calculation and analysis steps are set; the tire elasticity modulus and the cord fabric thickness are used as design variables, and an optimization algorithm is adopted to solve a multi-objective optimization function. The method has the advantages of being simple in modeling method and high in practical operability, the tire modeling threshold can be lowered, and the fund and time cost of refined modeling is reduced.

The invention discloses an automobile electronic wire harness insulation sheath crack detection system based on computer vision, and the system comprises a multi-channel input module which is used for obtaining and preprocessing multi-channel original data frames; the double-domain feature extraction module is used for extracting a double-domain feature pyramid; the double-domain fusion module is used for executing cross-domain attention and mutual information consistent weighting and inhibiting mirror surface highlight pseudo response; the topological structure output module is used for outputting a preliminary crack structuring result through the multi-head crack structure prediction head set; the communication repair module is used for carrying out breakpoint bridging and conflict rollback on the preliminary crack structuring result; and the geometric measurement module is used for measuring crack data and forming a structured detection report. According to the method, polarization reflection suppression and flattening geometric modeling are fused, a double-domain crack detection network is constructed, accurate identification and quantitative measurement of sheath cracks are achieved, and the method has the advantages of being high in reflection resistance, stable in topology and traceable in result.

The invention discloses a three-dimensional target detection method based on double-point cloud enhancement and fusion, and relates to the technical field of automatic driving. The method comprises the following steps: firstly, respectively extracting local features of a laser radar point cloud and a pseudo point cloud generated by a front view image in a candidate region by using the laser radar point cloud and the pseudo point cloud; the features of the false point cloud are enhanced through residual geometric modeling, depth separable convolution and a space-channel attention mechanism, and a three-layer cascade adaptive unit is constructed for further optimization; the original point cloud RoI features and the pseudo point cloud RoI features are mapped to a unified space, a bidirectional attention mechanism is adopted to realize fine-grained cross-modal fusion, and complementary fusion features are generated; and finally, outputting a category confidence coefficient and a 3D bounding box through a multi-branch detection head and a multi-task loss function. According to the method, the problem of point cloud sparseness is effectively relieved, the detection precision is improved, the bottlenecks of roughness, alignment difficulty and the like of a traditional fusion method are overcome, and the perception robustness and accuracy of an automatic driving system in a complex scene are remarkably enhanced.

The invention provides a multi-modal alignment and cross-scale structure attention-based remote sensing image building extraction method, which comprises the following steps of: performing radiation correction and geometric correction on an original hyperspectral satellite image, and performing voxelization, normalization and registration with a hyperspectral corrected image on LiDAR point cloud data to respectively obtain the hyperspectral corrected image and LiDAR corrected data; deep features of the two types of correction data are extracted through a special encoder, and after dimension unification and channel attention screening, fusion features are obtained through fusion of a weighting and gating mechanism; multi-scale features are extracted from the fusion features through multi-receptive field convolution branch, and cross-scale enhancement features are obtained by combining cross attention and geometric modeling; a prediction edge graph is generated based on cross-scale enhancement features, high-resolution guide features are combined to compensate tiny building information, and the extraction precision is improved through edge loss optimization; and carrying out denoising, edge repairing and adhesion separation on the optimized result to obtain a final building extraction result.

The invention provides a left heart data analysis method and system based on image segmentation, and relates to the technical field of medical image processing. Comprising the following steps: acquiring cardiac ultrasound image data and preprocessing; performing image segmentation on the preprocessed image data to obtain a segmentation result including a left ventricle, a left ventricular wall and a left atrium; searching a boundary line of the left ventricle and the left atrium, selecting two boundary points corresponding to the minimum and maximum abscissas in the boundary line as left and right mitral valve ring points respectively, and establishing a long axis based on the mitral valve ring midpoint and the cardiac apex point; modeling the ventricle into a structure formed by superposing a plurality of discs along the long axis direction, and obtaining the diameter of the corresponding disc; based on the obtained diameters of the corresponding discs, the left ventricular volumes in the diastolic period and the systolic period are calculated respectively, and the left ventricular ejection fraction is calculated. According to the method, image segmentation and geometric modeling are fused to achieve accurate calculation of the cardiac ejection fraction, meanwhile, the accuracy of cardiac structure image segmentation is improved, and an interpretable ejection fraction estimation process is achieved.

The invention provides a finite difference-based rapid calculation method and system for an electromagnetic regulation and control roller shape and a rolling condition optimization method and system, and belongs to the field of rolling control. The roller shape rapid calculation method comprises the steps that size parameters, an electromagnetic rod loading form, a regulation mode, regulation parameters and rolling working condition environment parameters of an electromagnetic regulation roller to be regulated are obtained, a geometric model of the electromagnetic regulation roller is established, and the electromagnetic rod loading form, the regulation mode, the regulation parameters and the rolling working condition environment parameters are set in the geometric model; grid division is conducted on the geometric model of the roller, the finite difference theory is introduced, an electromagnetic regulation and control roller shape rapid calculation model is constructed, and temperature field distribution is rapidly solved and calculated through an LU decomposition method; and the roller shape is calculated according to the electromagnetic regulation and control roller shape rapid calculation model and the temperature field distribution. According to the method, online dynamic regulation and control of the electromagnetic regulation and control roller shape under parameter optimization is achieved, and the real-time performance and accuracy of the electromagnetic regulation and control roller shape are improved.

The invention relates to a method for verifying a Mars sky radiance simulation result based on a Mars real-shot photo, and belongs to the technical field of Mars sky background radiance. Comprises: image acquisition; performing radiation calibration; correcting dark current; performing flat field correction; converting a radiation value; and geometric correction. The Mars sky radiance simulation method breaks through the dependence of an existing model on idealized hypothesis, performs dynamic verification by using actual shot image data, remarkably improves the authenticity and reliability of a Mars sky radiance simulation result, and effectively solves the problem of systematic deviation under a specific wave band; by constructing a complete process from image acquisition, radiation calibration, geometric modeling to brightness inversion and comparison verification, dynamic feedback and closed-loop correction of a theoretical radiation model are realized, model adaptability is improved, and fine modeling under multi-temporal and multi-meteorological conditions is supported; the method can be applied to an existing Mars rover navigation camera and an image processing link of the Mars rover navigation camera, does not need additional modification, has good engineering practicability and task compatibility, and is convenient to popularize and apply.

The invention relates to a node semi-rigid modeling-based complex curved surface reticulated shell multi-objective form optimization method. According to the method, through integration of parametric modeling, numerical simulation and a multi-objective optimization algorithm, efficient optimization design of the irregular boundary free-form surface latticed shell structure is achieved. The control point coordinate matrix of the NURBS curved surface is used for generating a geometric model of the complex curved surface reticulated shell, and high-quality grid division is automatically generated; semi-rigid mechanical behaviors of nodes are simulated through combination of a rigid beam and a spring in a numerical model, semi-rigid characteristics of the nodes are integrated into a rod piece unit, and the mechanical performance of the structure is accurately evaluated; and a non-dominated sorting genetic algorithm is adopted, the minimization of the total strain energy of the structure, the minimization of the total weight of the structure and the maximization of the minimum node configuration degree serve as objective functions, and the multi-objective form optimization design of the complex curved surface reticulated shell is completed. The method is suitable for a single-layer latticed shell structure with any node form and any special-shaped contour boundary, and has wide applicability and good transportability.

The invention discloses a low-scattering support system design and optimization method for large-scale target external field measurement, the support system comprises a support and a low-scattering end cap, and the low-scattering end cap is connected with the top of the support; the method comprises the following steps: S1, constructing a bracket geometric model based on a low-scattering shape design formula, and evaluating the bearing capacity of a bracket; s2, performing electromagnetic solution on the bracket by using a non-conformal region decomposition area integral equation method, and optimizing a bracket geometric model; s3, constructing a low-scattering end cap based on a low-scattering shape design formula; and S4, placing the low-scattering end cap at the top of the bracket to form a low-scattering support system, and evaluating the composite backscattering of the low-scattering support system by using a non-conformal region decomposition area integral equation. According to the low-scattering supporting system, high bearing capacity and good low-scattering performance are both considered, and reliable supporting guarantee can be provided for external field measurement of a large target.

The invention discloses an intelligent detection method and system for a flat curbstone disease based on linear continuity constraint. The method comprises the following steps: acquiring a road video stream and a vehicle dynamic parameter; extracting the area of the flat curbstone and the surrounding road surface from the road video stream to obtain two-dimensional image information; converting the two-dimensional image information into a visual mimicry geometric model which has a space proportion and represents a three-dimensional geometric contour; constructing a three-dimensional reference model conforming to the actual road alignment based on the visual mimicry geometric model; comparing the spatial difference between the visual mimicry geometric model and the three-dimensional reference model, and calculating and identifying potential diseases to obtain a residual error type, a residual error value and geometric parameters; classifying diseases, evaluating risk levels, and generating maintenance suggestions. By implementing the method provided by the invention, intelligent identification, classification and degree evaluation of the flat curbstone diseases can be realized, the accuracy and automation level of flat curbstone disease detection are improved, and road maintenance is promoted to develop towards a more intelligent and refined direction.

The invention relates to the technical field of ocean current data analysis, in particular to a multi-scale modeling and verification method and system based on ocean current spring layer structure analysis. And obtaining the thermocline and halocline parameters of the target sea area and carrying out abnormal value elimination and spatial interpolation to form a thermocline data set. A convolutional neural network is used to extract spring layer space structure features, and based on Gaussian curvature quantification boundary complexity, a thermocline and halocline equivalent geometric model is constructed. On the basis, taking the equivalent geometric model as a boundary condition, and performing multi-scale decomposition on the Navier-Stokes equation set to generate a dynamic approximate equation; and then inputting the approximate equation and the equivalent geometric model into a physical information neural network for constraint training to obtain a multi-scale flow field prediction model, and comparing the multi-scale flow field prediction model with actually measured flow field data to complete verification. According to the method, automation, refinement and multi-scale coupling of spring layer structure modeling are achieved, and scientificity and engineering applicability of ocean current modeling are improved.

The invention provides a part lightweight design method based on a random forest model, and the method comprises the steps: defining a design variable and a response target, and generating a sample point through a test design sampling method; geometric modeling and updating, finite element preprocessing, solving calculation and result extraction are automatically completed through parameterized scripts, and a sample data set is formed; independently training a random forest regression model for each performance response by using the sample data set, and constructing a quality rapid calculation model; verifying the random forest agent model until all agent models meet preset precision requirements; on the basis of the proxy model, constructing an optimization problem, carrying out optimization solution by adopting a multi-objective optimization algorithm, and outputting a Pareto optimal solution set; and selecting a candidate design scheme from the Pareto optimal solution set, executing high-precision finite element simulation, comparing a prediction result and a simulation result of the proxy model, and if an error is within an acceptable range and all performances meet design requirements, determining a final lightweight design scheme.

A digital twin holography monitoring and self-healing system for wind turbines, characterized by the fact that it comprises sequentially connected components: a physical plane, including the body of the wind turbines (1), the multi-source sensor network deployed on it and the execution device; a data acquisition and transmission layer for acquiring and transmitting data from the aforementioned multi-source sensor network; Digital twin model layer for creating and running virtual twins that are synchronized with the physical entity layer, including geometric models, physical models, behavioral models, rule models, and data model fusion modules; Holographic monitoring and diagnostic layers for visualizing plant condition, health assessment, fault prediction, and diagnosis based on the digital twin layer; and A fault self-healing regulation layer serves to independently generate and execute regulation strategies based on diagnostic results, which are returned to the execution organization of the physical entity layer.

The invention provides a three-coordinate measuring machine metering detection method and system, and relates to the field of three-coordinate measurement, and the method comprises the steps: obtaining the geometric model data of a to-be-measured workpiece, and analyzing the geometric model data to determine the local geometric features of the workpiece; according to the method, path information and measuring head attitude information used for measurement are generated according to local geometric features, and based on the path information and the measuring head attitude information, the contact condition of a measuring needle and the surface of the workpiece is simulated, so that the purity and reliability of a data source are remarkably improved, and the measurement data of which abnormal trigger signals are removed are accurately measured. Fine processing is carried out according to local geometric features to eliminate deviation in measurement data, geometric information of key geometric details of the workpiece is maintained, it is ensured that geometric information of key features such as tiny chamfers and sharp edges is not damaged, the accuracy, reliability and efficiency of the three-coordinate measuring machine in measurement and detection of the complex curved surface workpiece are improved, and the measurement precision is improved. The problem that the existing data acquisition efficiency is not high is effectively solved.

The invention provides a time domain and frequency domain combined impact resistance analysis method and device for a ship stern tube, and the method comprises the steps: building geometric models of all parts in the stern tube through three-dimensional modeling software according to an actual engineering drawing of the stern tube, carrying out virtual assembly on the geometric model of each component according to the actual assembly relation of each component to obtain a geometric model of the tail shaft tube; importing the geometric model of the tail shaft tube into finite element software, endowing each component with material attributes, and carrying out grid division on the geometric model by adopting an overall network size control method; and performing static analysis on the geometric model after grid division to obtain static working stress, performing dynamic analysis on the geometric model after grid division to obtain dynamic impact stress, and synthesizing the static working stress and the dynamic impact stress into total stress. According to the method, time domain and frequency domain combined shock resistance response calculation is carried out for the tail shaft tube as a core component of the ship propulsion system, and the accuracy of shock resistance response calculation is improved.

The invention relates to the technical field of engineering monitoring, in particular to a bridge structure state monitoring method and system based on digital twinning, and the method comprises the steps: building a multi-source monitoring data matrix based on a data timestamp; establishing a geometric model, a material attribute model and a load model of a bridge structure based on the multi-source monitoring data matrix, and fusing to obtain a bridge digital twin initial model; and carrying out structural mechanical analysis based on the bridge digital twin initial model to obtain stress distribution data of each region of the bridge. Through real-time acquisition and analysis of multi-source monitoring data, the method can dynamically evaluate the structural state of the bridge and timely identify potential safety hazards, so that the safety of the bridge is improved; and through calibration of the initial model, the obtained digital twin precise model reflects the real state of the bridge, and a more accurate data basis is provided for subsequent structural analysis.

The present invention relates to the technical field of electrodeposition, and relates to a simulation method for flow field distribution and deposition morphology in ultrafast laser-assisted electrochemical deposition. The steps of the method comprise: constructing, in multiphysics simulation software, a two-dimensional axisymmetric multiphysics coupled field model for heat transfer, solid and fluid heat transfer, tertiary current distribution, and laminar flow; constructing a geometric model of a deposition cell and a substrate, and setting laser properties, material physical parameters, and electrodeposition properties in the multiphysics simulation software; constructing an ultrafast laser heat transfer model on the basis of a two-temperature equation; setting initial and boundary conditions of the ultrafast laser heat transfer model, and constructing an electrodeposition field; coupling the ultrafast laser heat transfer model with the electrodeposition field to construct an ultrafast laser-assisted electrochemical deposition model; delineating a grid; and performing calculation and analysis. In the present invention, ultrafast laser is incorporated to perform multiphysics coupling of a thermal field, a flow field, an electric field, etc., and a two-temperature equation and tertiary current distribution are incorporated to the model, thereby achieving the accuracy and comprehensiveness of prediction models.

The invention discloses an ISAC angular domain energy imaging method and an ISAC angular domain energy imaging system based on actual measurement channel response calibration ray tracing, and mainly solves the problem that an imaging model faces serious channel mismatch and cross-scene generalization limitation due to the fact that simulation data lacks physical consistency constraint in the prior art. According to the scheme, the method comprises the steps that geometric features are extracted from public map data or laser point cloud data, and an ISAC scene environment geometric model is constructed; acquiring an actual measurement channel impulse response containing multipath information by using the communication and sensing integrated equipment; performing path matching on the actual measurement channel impulse response and the ray tracing simulation channel response, inverting environment propagation parameters and correcting scattering parameters; and inputting the calibrated parameters into a ray tracking model, counting energy contribution in each space direction under the condition of a single antenna, obtaining angular domain energy distribution and confidence coefficient, and mapping the angular domain energy distribution and confidence coefficient to a spherical grid to form an imaging result. According to the method, physical mismatch between simulation and real environments is effectively eliminated, low-cost and high-precision angular domain energy imaging and confidence evaluation are realized under the condition of a single antenna, and the method can be used for imaging reconstruction of an ISAC system, environmental perception and generation of a neural network training data set.

The invention relates to the technical field of machining simulation, in particular to a composite material ring piece low-stress machining method based on finite element analysis. The method comprises the following steps: constructing a two-dimensional finite element model of the composite material ring piece; grid division is carried out on the geometric model, and the structure is decomposed into units; setting boundary conditions and loads of the simulation model; defining material attributes including density, thermal conductivity, specific hot melting, elastic modulus, Poisson's ratio, plasticity and creep; setting processing and heat treatment parameters, including processing procedures, processing amount, heat treatment temperature and time; the simulation model is operated, and the response of the geometric model under the given boundary and loading condition is obtained; and analyzing an operation result, summarizing an influence rule of machining parameters and heat treatment setting on machining stress, and optimizing a machining scheme. According to the method, a stable component low-stress machining scheme can be rapidly obtained through an analogue simulation technology for the machining process of the composite material ring piece, and high-precision machining of the large-size fiber reinforced composite material ring piece is achieved.

The invention discloses an integrated core particle thermal performance prediction method driven by a physical information neural network, and the method comprises the steps: constructing a parameterized geometric model of a to-be-predicted integrated core particle system, and the parameterized geometric model comprises a solid domain geometric model and a fluid domain geometric model; based on the parameterized geometric model, design parameters of the to-be-predicted integrated core particle system are obtained, and the design parameters comprise geometric parameters of a solid domain and geometric parameters of a fluid domain; acquiring a plurality of space coordinates from the parameterized geometric model to obtain a target space coordinate; and inputting the design parameters and the target space coordinates into a trained thermal field physical information neural network model, so that the model outputs temperature field distribution of the to-be-predicted integrated core particle system under the design parameters through forward reasoning, the model is obtained by training based on a trained flow field physical information neural network model, design parameters and a preset thermal field loss function. According to the method, the prediction time can be shortened while the thermal performance prediction accuracy of the integrated core particles is improved.

The invention relates to a lithium ion battery multilayer metal foil and dissimilar metal connection optimization method in the technical field of new energy, and the method comprises the following steps: constructing a geometric model of multilayer metal foil and dissimilar metal connection by adopting a finite element simulation method according to initial interface bonding parameters, and applying a preset load condition in a simulation environment, determining an atomic-scale combined stress distribution diagram; for a heat balance state formed by metallurgical bonding, quantitative indexes, including shear strength and tensile strength, of connection point strength are extracted from a finite element simulation result, and a preliminary optimization data set of high-energy-density battery connection is obtained; and outputting a final metallurgical bonding formation parameter set according to a judgment result of a connection point strength stability threshold value, and applying the final metallurgical bonding formation parameter set to simulation verification of multi-layer metal foil connection so as to obtain an interface optimization scheme for improving the battery performance.

The invention discloses a reaction steam turbine through-flow method and system based on variable reaction degree optimization, and belongs to the technical field of steam turbine through-flow design. The method comprises the steps that an initial geometric model of a steam turbine through-flow part and thermal boundary conditions of all stages are obtained; inputting the initial geometric model and the thermal boundary conditions into a flow field solver, and solving a flow control equation to obtain an original flow field solution; constructing a functional taking through-flow efficiency as a target, and deducing an adjoint equation corresponding to the flow control equation; solving the adjoint equation to obtain gradient information of the target functional to each level of reaction degree; inputting the gradient information into a sequential quadratic programming optimizer, and iteratively updating the reactance of each stage by combining the maximum equivalent stress upper limit of the moving blade and the lower limit of the through-flow throat area to generate a variable reactance distribution scheme; and adjusting molded line geometric parameters of each stage of stationary blade and moving blade, and outputting optimized three-dimensional molded line data and a digital model file for numerical control machining. According to the method, the in-stage flow loss is reduced, and the design robustness is enhanced.

The invention discloses a radar and deep learning-based road surface internal disease three-dimensional morphology identification method, which integrates a novel technical path of qualitative identification and quantitative reconstruction, provides a high-precision and quantifiable reference for subsequent non-damage assessment by constructing a disease three-dimensional geometric model and reversely calibrating radar map characteristic parameters, and improves the accuracy and the accuracy of the three-dimensional morphology identification of a road surface internal disease. The problem that the three-dimensional morphology characteristics of the internal diseases of the asphalt pavement are difficult to accurately obtain at present is solved, and a calibration method is provided for obtaining the three-dimensional morphology characteristics of the internal diseases of the pavement based on a ground penetrating radar technology. And meanwhile, geometric data support is provided for mechanical response analysis and performance attenuation law research of the existing asphalt pavement structure containing internal diseases.

The invention relates to the technical field of digital twinning, in particular to a steel processing equipment self-adaptive control method based on digital twinning, which comprises the following steps: acquiring real-time signals such as displacement, load, rotating speed and inter-unit tension of an actuating mechanism, inputting the real-time signals into a digital twinning model, and constructing an instantaneous dynamic geometric model to calculate an instantaneous feedback value of a controlled object; the influence coefficient between the first control loop and the second control loop is analyzed through virtual perturbation, and a partial derivative sensitivity matrix is generated; and then, inputting the instantaneous feedback value into a self-adaptive controller to obtain an original control increment, calculating a compensation control increment of a second execution mechanism in combination with an actually measured morphology deviation signal and an influence coefficient, and finally driving a controlled object to complete action response. A cyclic storage buffer area is established, and asynchronous timestamp alignment based on spatial displacement is executed. Through multi-physics field coupling and asynchronous correction, self-adaptive control over the steel machining equipment is achieved.

A numerical control cutting process digital twinning implementation method based on three-dimensional reconstruction comprises the steps that a digital twinning model and a physical logic twinning model of a numerical control machine tool and a geometric model of a workpiece and a cutter are constructed respectively, and real-time synchronization of a physical machine tool model and a digital twinning machine tool model is achieved by transmitting motion data and machine tool state data in real time; the cutting state of a workpiece and a cutter is calculated in real time through a cutting simulation algorithm, collision detection simulation is carried out, a workpiece model constructed based on a one-way line cluster model is converted into a standard STL triangular mesh model based on a three-dimensional reconstruction algorithm, and the triangular mesh model is mapped into a digital twinning monitoring scene through coordinate system conversion. According to the method, a high-precision digital twinborn model is constructed, real-time data synchronization and cutting process simulation are combined, and rapid conversion between a simulation data model and a display model is realized based on a composite block algorithm.

The invention belongs to the field of hoisting track planning, and particularly discloses a bridge girder erection machine double-hook collaborative hoisting track planning method considering space-time coupling constraint, which comprises the following steps: constructing a kinematic model of a bridge girder erection machine and a three-dimensional obstacle geometric model of a hoisting operation environment, and forming a multi-dimensional configuration space; generating a hoisting operation sequence according to the type attribute of the to-be-hoisted component; in the global path planning stage, a sampling-based global path planning algorithm is adopted to carry out search sampling in a multi-dimensional configuration space, and a double-hook kinematics cooperative constraint detection mechanism is implanted to obtain an initial collision-free path; in the local trajectory optimization stage, a trajectory smoothing model based on quadratic programming is constructed, and a smooth and synchronous time state trajectory is generated by minimizing jerk and introducing synchronization error hard constraint. The problems of space-time coordination and anti-swing control in double-hook hoisting operation are effectively solved, and the optimal balance of efficiency and safety is achieved.