Research on intelligent inspection method for buildings based on 3D vision

被引:0
|
作者
Feng C. [1 ]
Liu Y. [1 ,2 ]
Yue Y. [1 ]
Fan J. [1 ,2 ]
Zhang J. [3 ]
Wang C. [4 ]
机构
[1] Department of Civil Engineering, Tsinghua University, Beijing
[2] Key Laboratory of Civil Engineering Safety and Durability of China Ministry of Education, Tsinghua University, Beijing
[3] Beijing Urban Construction Group Co., Ltd, Beijing
[4] Beijing Urban Construction Real Estate Development Co., Ltd, Beijing
关键词
3D vision; building inspection; component classification; point cloud registration; reconstruction identification; risk assessment;
D O I
10.14006/j.jzjgxb.2023.0038
中图分类号
学科分类号
摘要
Illegal reconstruction of self-built buildings in urban and rural areas occurs from time to time, which is a hidden danger that cannot be ignored. Traditional building inspection mainly relies on manual methods, which have problems such as low efficiency and high subjectivity, thus affecting the reliability of inspection results. This paper proposes an intelligent method for building inspection based on 3D vision. Based on the technology of fusion SLAM, the point cloud data are collected in real time. Multiple inspection data are registered, and the radius search method based on kd-tree is used to identify the increase or decrease parts of the point cloud and find out the reconstructed parts. The reconstructed parts are segmented by region growing algorithm and the OBB bounding boxes of them are obtained, and simple component classification is performed according to the geometry information of the bounding boxes. Furthermore, the surface area change rate parameter is defined considering the importance of the components, which can preliminarily evaluate the safety of the reconstructed structure. Taking the inspection of a self-built building as an example, the results demonstrate that the method outlined above can efficiently and quickly obtain point cloud data of the building facade to be inspected. This enables effective identification of any altered parts of the building and allows for an assessment of the danger of the building based on the characteristics of the components, thus realizing the automation and intelligence of the inspection process. © 2024 Science Press. All rights reserved.
引用
收藏
页码:133 / 142
页数:9
相关论文
共 30 条
  • [1] LIU Jun, YANG Quanquan, Analysis of the influence of openings in shear wall on structural safety of a commercial and residential building, Construction Quality, 36, 1, pp. 80-82, (2018)
  • [2] SONG Chunlei, JIN Chunfeng, Safety analysis and reinforcement design of a high-rise residential building after wall opening [J], Shanxi Architecture, 46, 11, pp. 48-50, (2020)
  • [3] WANG Heng, YE Yanhua, GE Hairong, Et al., Numerical simulation on collapse of infill walls with different length-height ratios and opening in the wall, Journal of Nanjing Tech University(Natural Science Edition), 35, 6, pp. 74-78, (2013)
  • [4] DONG Yu, PEI Zhongqing, LI Jingming, Seismic response analysis of a frame structure after the addition of a tower to the roof, Green Building, 14, 4, pp. 85-87, (2022)
  • [5] DAWOOD Thikra, ZHU Zhenhua, ZAYED Tarek, Computer vision-based model for moisture marks detection and recognition in subway networks [J], Journal of Computing in Civil Engineering, 32, 2, (2018)
  • [6] GUO Jianying, ZHENG Hao, NI Xuechen, Et al., Innovative research on safety inspection and dynamic monitoring of urban old dangerous residential buildings, Intelligent City, 5, 9, pp. 9-11, (2019)
  • [7] XU J, YAN C, SU Y, Et al., Analysis of high-rise building safety detection methods based on big data and artificial intelligence [J], International Journal of Distributed Sensor Networks, 16, 6, (2020)
  • [8] ZHANG S, TEIZER J, LEE J, Et al., Building information modeling (BIM) and safety: automatic safety checking of construction models and schedules [J], Automation in Construction, 29, pp. 183-195, (2013)
  • [9] YOU Y, ZHENG Y, CHEN X., Civil engineering simulation and safety detection of high-rise buildings based on BIM[J], Mobile Information Systems, 31, (2022)
  • [10] BAE J, LEE J, JANG A, Et al., SMART SKY Eye system for preliminary structural safety assessment of buildings using unmanned aerial vehicles [J], Sensors, 22, 7, (2022)