基于BIM和点云重建的既有空间网架结构承载力自动化预测OA
Automated prediction of load-bearing capacity of existing spatial grid structures based on BIM and point cloud reconstruction
为实现大型体育馆空间网架结构承载力自动化预测,提出了一种基于建筑信息模型和三维点云重建的自动化预测算法.使用最小二乘法和 RANSAC算法建立了焊接球节点的三维点云拟合算法,采用RANSAC-PCA联合算法建立了圆钢管杆件的三维点云拟合算法;以海南大学综合体育馆为例,结合Dynamo可视化编程重建网架结构的建筑信息模型和有限元模型,对比分析了设计模型和重建模型的静力承载力预测值.结果表明:该结构的焊接球节点竖向位置偏差为(-70~+60)mm,球节点外径拟合偏差为(-20~+10)mm,偏差率不超过 6.67%;杆件最大拟合偏差率为 21.19%,占比 0.51%,78.85%的杆件外径偏差集中在(-6~+6)mm区间;同时考虑节点位置偏差和杆件弯曲挠度的既有网架结构承载力相较设计值下降了 13.00%,节点偏差缺陷对结构静力承载力的影响远大于杆件弯曲变形产生的影响.该结论可为既有网架结构的安全评估与加固设计提供关键参考.
To enable automated prediction of the load-bearing capacity of large-span stadium spatial grid structures,thsi study proposes an algorithm integrating Building Information Modeling with 3D point cloud reconstruction.First,a 3D point cloud fitting algorithm for welded spherical joints is established using the least squares and RANSAC methods,while a combined RANSAC-PCA algorithm is developed for circular steel pipe members.Subsequently,taking the Hainan University Comprehensive Gymnasium as a case study,the BIM and finite element enable of its grid structure are reconstructed via Dynamo visual programming.Finally,the static load-bearing capacities of the designed model and the reconstructed models are compared.The results show that the vertical position deviation of the welded spherical joints ranges from(-70~+60)mm,and the diameter fitting deviation ranges from(-20~+10)mm,with a maximum deviation rate of 6.67%.The maximum fitting deviation rate of members is 21.19%,accounting for 0.51%of all members,while 78.85%of member diameters fall within a deviation range of(-6~+6)mm.Considering both joint position deviations and member bending deflection,the actual load-bearing capacity of the existing grid structure is 13.00%lower than the design value.Futhermore,the influence of joint deviation defects on static load-bearing capacity of the structure is much greater than that of member bending deformation.This findings provide critical references for the safety assessment and reinforcement design of existing spatial grid structures.
侯鑫焱;张天龙;汤爱平;胡安奎
海南大学 土木建筑工程学院,海南 海口 570228海南大学 土木建筑工程学院,海南 海口 570228海南大学 土木建筑工程学院,海南 海口 570228西华大学 能源与动力工程学院,四川 成都 610039
社会科学
既有网架结构BIM点云重建承载力自动化预测
existing grid structurebuilding information modelingpoint cloud reconstructionbearing capacityautomatic prediction
《海南大学学报(自然科学版中英文)》 2026 (2)
217-227,11
本文得到海南省自然科学基金项目(520QN232)、天津大学-海南大学自主创新基金项目(RZ2100003553)和横向项目(HD-KYH-2024061)的支持. This study was supported by the Hainan Provincial Natural Science Foundation(520QN232),the Tianjin University-Hainan University Independent Innovation Foundation Project(RZ2100003553),and the Hainan University Horizontal Project(HD-KYH-2024061).
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