Digital Detection Method Of Steel Structure Based On Laser Point Cloud

In recent years,there have been more and more steel structure buildings,which are made of steel structure components by welding and splicing.These steel structure components are generally processed in accordance with the design drawings in the workshop,and then welded at the construction site,but due to the adverse construction conditions,immature processing technology and shrinkage of the weld,the steel structure and design drawings after welding have A little difference.If the steel structure is deformed significantly after welding,it will cause difficulties in the later component installation,affect the construction schedule,and cause material loss.In order to ensure the construction efficiency and construction accuracy,the steel structure after welding needs to be inspected.In order to reduce the field workload and quickly obtain the steel structure data,the three-dimensional laser scanning technology is used to collect the steel structure data.Aiming at the problem of accurate detection between a large number of laser point clouds and design models.The main research contents arc as follows:(1)For the point uniformity of the point cloud and the design model,the improved adaptive genetic algorithm is applied to the uniformity of the benchmark between the large-scale steel structure point cloud and the design model.According to the degree of population evolution,cross operations are performed before the evolution Carry out mutation operations and increase the probability of crossover,reduce the probability of mutation,increase the probability of producing good individuals and avoid the destruction of good individuals;in the late evolution,perform the mutation operation first and then perform the crossover operation to reduce the probability of crossing and increase the mutation Probability,improve the diversity of the population,and avoid premature convergence into a local optimal situation.Combine roulette selection with optimal preservation strategy to improve the convergence speed of the algorithm.(2)Due to the large number of large-scale steel structure design models,in order to quickly and accurately determine the deviation between the welded steel structure and the design model,the topological relationship between the points,lines and surfaces of the design model is constructed by half-edge coding to improve calculation Efficiency;and put forward a point-surface correspondence model and a point-line correspondence model to determine the correspondence between the point cloud and the design model,and improve the accuracy of the deviation calculation;finally,the chromatogram is used to express the intuitive expression after welding The deviation distribution between the steel structure and the design model can obtain the overall deformation information of the steel structure.In this paper,the point cloud data and design model of a steel structure roof are used as research objects.The improved adaptive genetic algorithm is used to realize the unity of the benchmark of the point cloud and the design model,and the deviation between the point cloud and the design model is accurately calculated.The experimental results show that the improvement The adaptive genetic algorithm can converge to the global optimal solution,and the half-edge coding method improves the calculation efficiency and accuracy.Improve the efficiency and accuracy of digital detection.