152 results about "Reverse modeling" patented technology

The present invention belongs to the technical field of digital mine safety, and particularly relates to a blasting area surface morphology inversion method based on an unmanned aerial vehicle. The method comprises: S01, on-site data collection; S02, blasting area morphology inversion; S03, a muck pile throw distance; and S04, a muck pile surface fragmentation distribution. In the present invention, oblique photography by an unmanned aerial vehicle is used, and three-dimensional model reconstruction is performed by capturing a blasting area image, so that a feasible aerial survey scheme is formulated, and the integrity of collected data is good; and reverse modeling of the blasting area is performed by means of the steps of feature point extraction, spatial information conversion, point cloud generation, grid generation, etc.; voxel grid downsampling, point cloud matching and error detection are used to perform registration on point clouds of a target area before and after blasting, so that a good effect is achieved; and a color-based region growing algorithm is used to perform coarse segmentation of point cloud features on an ore-rock block on the surface of a muck pile, and a PointNet++ algorithm is used to perform fine segmentation of point cloud features on the ore-rock block on the surface of the muck pile, so that the muck pile throw distance and the muck pile surface fragmentation distribution are calculated.

Provided is a robot posture optimization and follow-up control method and system for freeform surface repair. The system includes a worn surface reverse modeling module, a worn surface initial normal vector calculation module, an initial machining trajectory and normal vector extraction module, a normal vector rotation angle polynomial regression denoising module, a machining trajectory position and posture NURBS fitting module, a position and posture trajectory curvature adaptive segmentation module, a segmented trajectory position and posture synchronization acceleration and deceleration look-ahead module, and a robotic motion and laser process coordinated control module. The method and the system realize posture optimization and follow-up control in a cladding process of the robot, and ensures the processing quality of laser repair.

The invention provides a geophysical gravity and magnetic anomaly source model construction and rapid forward and reverse modeling method, and relates to the technical field of intelligent three-dimensional geological modeling and simulation. According to geological information of a research area, source body modeling parameters of a gravity and magnetic anomalous field are set for the research area, and a three-dimensional model matrix M capable of describing a plurality of underground anomalous bodies is obtained; constructing a fast forward modeling network, establishing nonlinear mapping from the three-dimensional model matrix to the simulated abnormal data through the fast forward modeling network, and calculating forward modeling response of the three-dimensional model matrix; and constructing an inversion network based on a concurrent module CFTBlock and combining a CNN and a Transform, and establishing nonlinear mapping from the gravity and magnetic abnormal data to a three-dimensional model matrix. The method has the advantages of fast and accurate forward modeling, high-resolution inversion and the like, and is suitable for better interpretation of actually measured gravity and magnetic data.

The invention provides a three-coordinate radar reverse modeling-based penetration aircraft detected probability calculation method, relates to the technical field of three-coordinate radar reverse modeling, and provides a multipath propagation factor dynamic correction model and an adaptive clutter suppression method through reverse modeling ship-borne radar power distribution characteristics and an environment coupling effect. And the calculation precision of the detection probability in a complex electromagnetic environment is improved. Based on a directional diagram propagation factor quantization radar wave attenuation law, and in combination with a sub-beam system constant inversion technology, the dependence of a traditional model on confidential parameters is broken through, and high-reliability simulation based on public parameters is realized. Through pre-generation of a typical scene database and cubic spline interpolation, dynamic response of a penetration strategy is supported, a multi-radar networking cooperative detection correction model is introduced, and a global detection blind area is identified.

The invention discloses an adaptive edge detection iterative denoising point cloud reconstruction method and system. A regularization parameter and a kernel bandwidth are automatically set through point cloud normalization and local covariance noise estimation; an implicit curved surface is fitted based on a parameterized Gaussian field, and initial curved surface construction without a normal direction is realized. Edge detection is carried out by utilizing Voronoi covariance measurement, and the edge detection is continuously mapped into a projection weight, so that feature details of the point cloud are reserved in an acute angle region, and smooth denoising is realized in a flat region. The regularization intensity is dynamically adjusted through residual trend analysis to enhance detail representation, and a triangular mesh is extracted and output in combination with octree discretization and contour surface extraction. The method has unsupervised adaptivity, has outstanding performance in the aspects of edge fidelity, noise robustness and complex structure adaptability, can effectively process point cloud data with high noise, missing normal direction or irregular structure, and is suitable for the fields of engineering survey, reverse modeling, cultural relic digitization and the like.

The invention provides a reverse modeling design method for a passive device and a computer readable medium, and the method comprises the steps: generating samples of different layout sizes of the passive device, and building a performance data set; establishing and pre-training by taking the geometric parameters and the working frequency as input parameters and the performance parameters as output parameters to obtain a forward model; constructing a reverse neural network model; dividing a parameter space of the whole performance data set into a plurality of sub-training domains, and respectively establishing and training a reverse sub-model in each sub-training domain; after training is completed, all the reverse sub-models are integrated to form a final reverse neural network model, and the reverse neural network model is used for outputting geometric parameter solutions meeting conditions according to the specified working frequency and performance parameters. According to the method, a high-confidence data set is constructed by using a forward model, and then the data set is divided based on the uniqueness of output parameters and the reverse sub-models are obtained respectively, so that rapid and accurate mapping from target performance parameters to geometric parameters is realized.

The invention discloses an underground medium multi-scale forward and reverse modeling method and system based on a decoupling neural network, and belongs to the technical field of underground multi-physics field coupling. The underground medium multi-scale forward and reverse modeling method based on the decoupling neural network comprises the following steps: generating a spatio-temporal evolution data set of multiple physical field variables; a physical field decoupling physical information neural network architecture is constructed, the architecture comprises three special sub-networks, each sub-network takes time-space coordinates as basic input and dynamically receives output of other sub-networks as auxiliary input features, and strong coupling modeling between physical fields is realized through feature sharing and a joint loss function; executing a two-stage training strategy; and executing forward intelligent prediction or key physical property parameter inversion based on the trained neural network architecture. According to the method, a unified neural network framework composed of a plurality of special sub-networks is constructed, physical consistency and data-efficient cross-scale modeling from a rock core scale to a site scale are realized, and forward simulation and parameter inversion are synchronously supported.

The invention provides a method and a device for installing, positioning and monitoring a laminated slab in a beam. Relates to the technical field of building construction. According to the specific implementation scheme, the method comprises the steps that reverse modeling is conducted on a prefabricated laminated slab component through laser scanners placed at multiple target positions, and a point cloud model is generated; inputting preset data of the prefabricated laminated slab component into the building information model to generate a target preset model; and the point cloud model is matched with a target preset model, and when it is detected that the matching degree of the point cloud model and the target preset model is smaller than a first preset threshold value, multiple installation point positions for beam-entering installation of the prefabricated laminated slab component and normal state parameters of the multiple installation point positions are determined based on the point cloud model and the target preset model. According to the technical scheme, the accuracy and construction efficiency of installation and positioning of the laminated slab into the beam can be improved, structural hidden dangers caused by installation dislocation are avoided, it is guaranteed that the laminated slab and the beam form a reliable overall stress system, and the stability and safety of a building structure are enhanced.

The invention discloses a modeling method and a processing device for a lattice structure gear filled with a three-period minimal curved surface, and the method comprises the following steps: writing an implicit function equation of the three-period minimal curved surface by using Matlab numerical analysis software, and generating an stl format model; using Geomagic reverse modeling software to perform reverse modeling on the three-period minimal curved surface cell elements to produce an stp format model; using Matlab numerical analysis software to generate data points, and importing Proe software to generate a gear model; after operations of mirroring, arraying and the like are carried out on the curved surface cell element model by using SolidWorks, a lattice structure is obtained by using a curved surface thickening command; according to the method, SolidWorks is used for dividing the gear into three parts, namely a gear tooth design area, a hub design area and a spoke design area, the spoke design area intersects with a lattice structure Boolean and then is combined with the gear tooth area Boolean and the hub area Boolean, and therefore the lattice structure gear filled with the three-period minimal curved surface is constructed, and a new thought and method are provided for lightweight design of the gear.

The invention discloses a soft tissue constitutive parameter calibration method in a soft tissue-skeleton bird body model for bird strike simulation, and the method comprises the construction of a soft tissue-skeleton bird body finite element model and finite element reverse analysis based on flat bird strike. Dividing wing bones, leg bones and head and neck parts in the bones of the bird body into hexahedral unit grids, dividing wishbones, pecking bones, fossil protrusions and ribs into shell units, and dividing soft tissues into SPH particles; further obtaining bone elastic-plastic constitutive parameters through a static compression test, and endowing the bone units with the bone elastic-plastic constitutive parameters; an objective function is set as a mean square error between a flat plate center point pressure-time curve obtained by a real bird body impact flat plate test and corresponding curve data calculated by soft tissue-skeleton bird body impact flat plate finite element simulation, and soft tissue constitutive model parameters are inversely calibrated by adopting a genetic algorithm; and model and material parameter support is provided for bird strike simulation of a high-fidelity aircraft structure.

The invention discloses a method for generating a workpiece model based on point cloud data, and aims to automatically generate a high-precision workpiece model through reverse modeling. The method comprises the following steps: dynamically adjusting a data acquisition amount through a line structure light sensor, and obtaining workpiece surface point cloud data; preprocessing the point cloud, including three-dimensional effective area cutting, uniform downsampling and radius filtering to remove interference data and reduce data volume; carrying out clustering segmentation on the preprocessed data by utilizing a point cloud region growing method, separating a bottom surface part from a non-bottom surface part, extracting contour points of each plane region, calculating normal lines, generating vertexes by fitting contour edges and solving intersection points, and forcibly closing unclosed contours to construct complete geometric features; and finally, generating a workpiece model by combining the point, line and surface information packaged by the open source library. According to the method, the low-error and high-precision model can be directly generated for the model-free non-standard workpiece, limitation of manual modeling or model presetting is avoided, and programming time consumption is remarkably reduced.

The invention provides a casting joint line polishing method based on vision, and belongs to the crossing field of mechanical manufacturing automation and intelligent manufacturing, and the casting joint line polishing method comprises the following steps: obtaining template surface point cloud of a standard casting, carrying out reverse modeling on the template surface point cloud to obtain first template point cloud, and obtaining first measurement point cloud of a casting to be polished; performing rough matching and fine matching on the first template point cloud in sequence, and converting the original joint line model into a new joint line model; points, closest to track points of the template track, in the new joint line model are obtained, for each closest point, the point, having the largest vertical distance from the plane where the new joint line model is located, in the neighborhood of the closest point is obtained, and all the points having the largest distances form a path planning point cloud; and traversing all planning points in the path planning point cloud according to the machining direction, selecting a machining mode according to the machining allowance corresponding to each planning point, and generating a final machining track. The grinding precision, the grinding quality and the grinding efficiency of the joint line can be improved, and the grinding device is also applicable to complex curved surfaces.

The invention discloses a reverse BIM modeling method, system and equipment for an existing building space rod system composite structure, and belongs to the technical field of BIM modeling. In order to solve the problem that in the prior art, point cloud processing software lacks a special recognition and reconstruction tool for a'ball node-rod piece 'class space rod system combined structure, and efficient and accurate reverse generation of a rod piece axis is difficult to achieve, through curvature analysis, DBSCAN clustering, RANSAC spherical surface fitting and other technologies, the position of a ball node is accurately recognized from actually measured point cloud data; and finally generating a high-precision BIM model of a space rod system combined structure according with engineering practice by combining a two-stage geometric filtering strategy according to a sphere center connecting line of sphere nodes and the space constraint of the rod piece point cloud data. According to the method, the problem that actually measured point cloud data is discrete and difficult to process is effectively solved, and reliable technical support is provided for health monitoring, digital filing and accurate modeling of the existing building space rod system composite structure.

The invention aims to provide a high-precision design and optimization method for an EMI (Electro-Magnetic Interference) filter aiming at the corresponding defects in the prior art, a mixed neural network architecture model is constructed by combining a feedforward neural network and a convolutional neural network, and the filter is subjected to reverse modeling by utilizing the mixed neural network architecture model, so that the filtering precision is improved. According to the method, the predicted value, the topological structure and the element parameters of the filter are obtained, then the element parameters are subjected to multi-objective optimization by using a multi-objective genetic algorithm to obtain the optimized element parameters, and the optimized element parameters and the topological structure of the filter jointly form an optimization scheme of the filter, so that the design efficiency and the optimization precision of the EMI filter can be remarkably improved; and the design period of the EMI filter is shortened, and the market demand of rapid iterative updating of current high-frequency electronic equipment can be met.

The invention belongs to the technical field of filter modeling, and relates to a reverse modeling method of a microwave coupling filter, which comprises the following steps: acquiring a design target of the microwave coupling filter, defining an ideal coupling matrix, and obtaining a plurality of coupling matrix samples to construct a sample set; calculating an S parameter of each coupling matrix sample at a set frequency point to construct a condition set; the sample set and the condition set serve as input of a diffusion model, the diffusion model is trained, and multiple sets of initial coupling parameters are obtained; obtaining an S parameter corresponding to each group of initial coupling parameters according to the forward model; calculating and screening mean square errors of the target S parameter and the corresponding S parameter to obtain a plurality of groups of optimal coupling parameters; and clustering the multiple groups of optimal coupling parameters to obtain coupling parameter distribution so as to realize reverse modeling of the microwave coupling filter. According to the invention, reverse modeling of the microwave coupling filter can be realized.

The invention provides a multi-source constraint reverse modeling method and system for ancient lake water chemical condition evolution, and relates to the technical field of mineral resource exploration, and the method comprises the steps: rock core element scanning, ore-bearing section XRD analysis, and obtaining of ancient lake water ion composition; judging the water chemical type of the ancient lake based on the water ion composition of the ancient lake, and determining the basic evolution path of the water chemical condition; measuring carbon, oxygen and sulfur isotopes, and analyzing isotope fractionation characteristics and control factors; a multiphase fluid mixing model is defined, a Monte Carlo algorithm is adopted to solve the mixing proportion, and reaction network initialization is carried out; dividing time steps of fresh water injection, evaporation concentration, salt precipitation critical periods and the like, carrying out dynamic simulation calculation, constructing a loss function between actual measurement and simulation results, carrying out back propagation correction by adopting an Adam optimizer, and verifying and optimizing the simulation results. The method has good applicability to the numerical simulation of the chemical condition evolution process of the ancient lake water.

The invention provides a steel truss girder quality detection method and device, electronic equipment and a storage medium, and relates to the technical field of engineering detection. The method comprises the steps that the position of each scanning site is determined according to size information of a steel truss girder and scanning parameters of a three-dimensional scanning device; determining the position of each target according to the position of each scanning site and a preset target setting strategy; obtaining point cloud data sets scanned by the three-dimensional scanning device at the scanning sites, and registering the point cloud data sets according to the point cloud data corresponding to the target to obtain a point cloud model of the steel truss girder; and constructing a three-dimensional model of the steel truss girder based on the point cloud model, performing feature extraction on the three-dimensional model to obtain target features, and obtaining a quality detection result based on the target features. According to the method, efficient reverse modeling and three-dimensional reconstruction are carried out on the steel truss girder, the automation level of quality detection is effectively improved, errors and time cost of manual measurement are reduced, and the efficiency and accuracy of quality detection of the steel truss girder are improved.

The invention provides a time sequence prediction task-oriented basic model construction method, which comprises the following steps of: constructing a Patch division layer which is used for cutting an input time sequence by adopting a context window adaptive mechanism combining time domain and frequency domain statistical characteristics to generate overlapped time periods; an embedded layer is constructed and used for converting the processed time sequence into embedded representation and generating an embedded Token through linear projection processing; constructing a forward and reverse frequency domain enhanced bidirectional state space module which is used for outputting forward and reverse modeling results by taking the input sequence and the time reversal sequence thereof as input, and fusing the forward and reverse modeling results to obtain a final fusion result; constructing a feed-forward layer which is used for taking the final fusion result as input to encode a time dependency relationship; and constructing an output and projection layer for mapping the coded time sequence to a predicted future value through linear projection. The method can adapt to various time series data under zero sample setting, and has good modeling robustness and cross-variable modeling capability.

The invention discloses a point cloud-based reverse modeling curved surface generation method and system, and relates to the field of electric digital data processing, and the method comprises the steps: obtaining three-dimensional point cloud data of a to-be-processed engineering design product, and projecting the three-dimensional point cloud data to a preset cutting plane to obtain a two-dimensional projection point set; and performing dimension reduction processing on each projection point, calculating a local geometrical relationship between the projection point and a neighborhood point, and mapping the local geometrical relationship to a one-dimensional parameter space to obtain a one-dimensional parameter value. Clustering analysis is conducted on the two-dimensional projection point set based on the one-dimensional parameter values, the two-dimensional projection point set is divided into a plurality of point cloud clusters, and each point cloud cluster corresponds to one geometric feature curve. And sorting the projection points in each point cloud cluster according to a spatial position relationship to obtain an ordered point sequence. And identifying the geometric feature type of each ordered point sequence, performing curve fitting, and extracting parameter information to obtain the feature parameters of the engineering design product. And generating an accurate curved surface model according to the characteristic parameters. By implementing the method, the accuracy of point cloud clustering can be improved.

The invention relates to a flat shell and an efficient printing method thereof, and belongs to the technical field of additive manufacturing. According to the invention, the axis of the flat shell is parallel to the substrate, and the support is arranged between the flat shell and the substrate; the substrate is divided into a region A and a region B; the area A is quadrilateral and is located in the center of the substrate, the side length of the area A is 55-65% of the side length of the substrate, and the area B is the remaining area obtained by subtracting the area A from the substrate; through analogue simulation, pre-printing and local reverse modeling, the deformation of the area A is controlled within + / -2mm; the deformation amount of the area B is controlled within + / -3 mm; the area A and the area B adopt different printing parameters, and the laser power and the scanning speed of the area A are both higher than those of the area B; and carrying out heat treatment to obtain the flat shell. And meanwhile, it is guaranteed that the deformation of the obtained flat shell is smaller than or equal to + / -0.5 mm, the tensile strength is 1000 MPa or above, and the yield strength is 800 MPa or above.

The invention discloses a deepwater bank protection unit row construction error reverse modeling correction method and device, and relates to the field of data processing. Obtaining water body profile data of a target construction area where the deepwater bank protection unit row is located; according to the water body profile data, constructing a hydrological state tensor; inputting the hydrological state tensor into the prediction correction model, and constructing a layered water resistance field and a non-uniform sinking path dynamic response equation of the unit drainage body; determining a prediction result based on the stratified water resistance field and the non-uniform sinking path dynamic response equation; obtaining an attitude response vector flow sent by the sensor equipment after the unit row body enters water; dynamically matching the attitude response vector flow with a prediction result, and outputting an arrangement path correction value and a pitching attitude adjustment suggested amount; and dynamically correcting the attitude and the sinking path of the unit row body based on the arrangement path correction value and the pitching attitude adjustment suggested amount. The construction precision of the deepwater revetment unit row in a complex hydrological scene can be improved conveniently.

The invention discloses an electric arc additive lamination parameter real-time regulation and control system and method based on reverse modeling, and the method comprises the steps: obtaining data in an additive process through a data obtaining unit, carrying out the comparison with a theoretical model, obtaining defect data in an additive, carrying out the analysis, recognizing the defect type and severity, and carrying out the real-time regulation and control of the parameters. And in combination with information such as molten pool parameters, temperature field parameters, melt channel defects and component forming deviation, follow-up electric arc additive lamination parameters are corrected through parameter self-adaptive adjustment, and real-time automatic regulation and control of the lamination parameters in the electric arc additive process are achieved. The method has good generalization ability, is suitable for large complex components, and improves the stability of the electric arc additive process, reduces the defects of the electric arc additive component and improves the performance and quality of the electric arc additive component by automatically regulating and controlling parameters in the electric arc additive process in real time.

The invention discloses a tower structure defect identification and three-dimensional space positioning method based on multi-source fusion. The method comprises the following steps: constructing multi-dimensional acquisition data; unifying multi-dimensional data to the same coordinate system; establishing an enhanced data set based on the multi-dimensional data after unifying the coordinate system; constructing an independent single tower point cloud model, and carrying out reverse modeling to form a vectorized single tower three-dimensional DXF format model; detecting and analyzing the difference between the vectorized single tower three-dimensional DXF format model and the manually designed tower three-dimensional DXF format model by using a projection dimension reduction comparison method; and outputting the spatial position of the tower structure difference found in the matching process, and performing mapping association with the enhanced data set to realize defect identification and positioning of the tower structure. The method breaks through the subjectivity of a traditional method and the one-sidedness of single-source data, constructs a full-process automation system of data fusion, reverse modeling, intelligent comparison and visual positioning, and achieves the precise diagnosis of the three-dimensional deviation before the operation of the tower.

The invention discloses a large metal thin-wall component manufacturing method based on stress distribution state management, which comprises the following steps of: aiming at the configuration of a large metal thin-wall component to be manufactured, constructing a manufacturing process combining reverse modeling analysis and forward process design; the reverse modeling analysis starts from the working step at the tail end of the manufacturing process, the stress distribution state between the working steps serves as a transmission and control element, and in the direction from the tail end to the front end, each working step proposes the final stress distribution state meeting the most simplified requirement of the manufacturing scheme of the working step for the previous working step; and based on the result of the reverse modeling analysis, on the basis of the final stress state determined by the previous step, the tool and the forming process of each step are determined, so that the final stress distribution state of the component manufactured by the step meets the requirements of the next step. The problems that the forming precision of a large metal thin-wall component welding component is poor, the precision coordination consistency of all procedures is poor, and the component manufacturing quality is difficult to guarantee are solved.

The invention discloses a reverse modeling method and device for rapidly evaluating and counting turbine blade profile deviation and a medium, and the method comprises the steps: obtaining coordinate data of a limited section through three-coordinate measurement, and processing key areas such as a film hole and a trailing edge in a data processing stage to form measurement point data of a complete section; according to the multiple pieces of section coordinate data, curved surface modeling is conducted through a curved surface reconstruction mode fitting method, and a complete machined blade shape is obtained; comparing the actually processed blade with the designed blade to obtain the deviation between the two blades, and finally obtaining the deviation of the processing model; the key parameters are adjusted through blade grid modeling software to be fitted with the machined blade, and then the variable quantity of the key design parameters is obtained; through statistics of batch blades, the change range of key design parameters of the blades is obtained, a machining deviation blade profile is generated, and a turbine cooling blade entity is generated, so that pneumatic, heat transfer and strength analysis is carried out according to a turbine blade entity model sample.

The invention discloses a method for reversely establishing an electromechanical pipeline BIM model based on a three-dimensional laser point cloud, and the method employs a three-dimensional laser scanning technology to obtain an on-site electromechanical pipeline point cloud, and improves the efficiency and precision of on-site data collection. A point cloud processing algorithm is combined, a point cloud reverse modeling scheme is designed, CV-Filter, DR-RANSAC, MC-RANSAC, SW-DBSCAN and a pipeline axis optimization algorithm based on feature iteration are provided, and electromechanical pipeline reverse modeling is carried out. The electromechanical pipeline reverse modeling method has higher automation level, reduces the workload, improves the accuracy of electromechanical pipeline reverse modeling, and solves the problems of slow speed, large workload, low model accuracy and the like of a traditional manual electromechanical pipeline reverse modeling mode.

The invention provides a building point cloud high-precision automatic registration method based on multi-source sensor fusion, and relates to the field of data processing. According to the method, building point clouds are obtained through multi-source sensor fusion, a time sequence and coordinates are unified, noise and transient targets are removed through density distribution and an occlusion relation, a three-state point cloud label is generated, rough registration and global and local joint optimization are carried out in combination with semantic classification and a cross-scale semantic association graph, and a high-precision registration result is obtained. And on this basis, dynamic difference labeling is executed to generate a component life cycle map, a result is mapped to a building information model, reverse modeling data with life cycle attributes and an engineering application data set are output, and high-precision modeling and application of the whole construction process are achieved. By implementing the technical scheme provided by the invention, high-precision automatic registration of the multi-source point cloud data is facilitated, so that the data set which can directly serve building information modeling and engineering application is mapped.

The invention relates to an intelligent green curtain wall reverse modeling method based on BIM-IoT fusion in the technical field of data processing and artificial intelligence. Comprising the following steps: acquiring BIM component data and IoT sensing data, and constructing a data set; performing node feature fusion and edge weight calculation based on the data set, and constructing a dynamic graph structure; constructing a geometric parameter prediction model based on machine learning, wherein the geometric parameter prediction model comprises a spatio-temporal feature encoder module, a spatio-temporal diagram convolutional network module, a multi-scale feature pyramid module and a physical constraint decoder module; inputting the dynamic graph structure into a geometric parameter prediction model based on machine learning, and carrying out iterative training; and constructing a real-time dynamic graph structure based on the basic BIM component data and the real-time IoT sensing data, inputting the real-time dynamic graph structure into the trained geometric parameter prediction model based on machine learning, outputting a predicted geometric parameter vector, and performing intelligent green curtain wall maintenance. And cooperative expression of static geometry and transient environment change of the component is realized.

The invention relates to a steel structure curved surface curtain wall mounting method based on a reverse modeling technology, which comprises the following steps of: performing spatial scanning on a steel structure to obtain a three-dimensional point cloud data set covering the geometric morphology and spatial position information of a curved surface; reverse modeling is carried out based on the three-dimensional point cloud data, and a three-dimensional digital model highly matched with the steel structure is constructed; the model is corrected; carrying out curtain wall design optimization based on the final model, and generating a digital processing drawing; and deepening the digital processing drawing of the curtain wall component, and carrying out field installation operation of the curtain wall component. According to the method, through space scanning and reverse modeling, secondary optimization is carried out on design and installation of the curtain wall based on a reverse modeling result, and by means of on-site curtain wall installation precision control and the like, the engineering problem of curtain wall installation of a complex steel structure is solved, and the measurement precision of the curtain wall in the early stage of installation is improved. The installation quality and efficiency of the curtain wall are improved, the cost is reduced, the construction period is shortened, and finally the aesthetics and functionality of a building are improved.

The invention relates to the technical field of building information data analysis, in particular to a building structure intelligent reverse modeling and analysis system based on BIM, and the system achieves the denoising of the point cloud data of a building structure through a data collection module, a downsampling module, a structural similarity classification module, a data denoising module and a model construction module. And completing the construction of the building structure BIM model. The system analyzes the minimum point cloud data selected in the RANSAC fitting process by using the reproduction structure in the building structure based on the reproducibility of the building structure, so as to determine the weight of each point cloud data belonging to a priori interior point in the point cloud set selected by each fitting, and distribute a corresponding error threshold to the weight, thereby screening out noise points, and improving the robustness of the system. The accuracy of a reverse modeling structure can be effectively improved, and the robustness of the model to noise is further improved.