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Abdalla, A, Li, X and Yang, F (2024) Expatriate construction professionals' performance in international construction projects: The role of cross-cultural adjustment and job burnout. Journal of Construction Engineering and Management, 150(03).

Chen, S, Chen, D, Li, L, Miramini, S and Zhang, L (2024) Optimized bridge maintenance strategies: A system reliability-based approach to enhancing road network performance. Journal of Construction Engineering and Management, 150(03).

Do, Q, Le, T and Le, C (2024) Uncovering critical causes of highway work zone accidents using unsupervised machine learning and social network analysis. Journal of Construction Engineering and Management, 150(03).

Gu, J and Guo, F (2024) Promoting digital sustainability through project digital responsibility implementation: An empirical analysis. Journal of Construction Engineering and Management, 150(03).

Guo, J and Kato, H (2024) Role of government equity investment in capital structure of project finance: Global evidence from PPP projects in developing countries. Journal of Construction Engineering and Management, 150(03).

Halder, A and Batra, S (2024) Navigating the ethical discourse in construction: A state-of-the-art review of relevant literature. Journal of Construction Engineering and Management, 150(03).

Harode, A, Thabet, W and Leite, F (2024) Formulation of feature and label space using modified Delphi in support of developing a machine-learning algorithm to automate clash resolution. Journal of Construction Engineering and Management, 150(03).

Heydari, M, Heravi, G, Raeisinafchi, R and Karimi, H (2024) A dynamic model to assess the role of site supervision systems in the safety performance of construction projects. Journal of Construction Engineering and Management, 150(03).

Ibrahim, A, Nnaji, C, Namian, M and Shakouri, M (2024) Evaluating the impact of hazard information on fieldworkers' safety risk perception. Journal of Construction Engineering and Management, 150(03).

Ko, T, Lee, J and David Jeong, H (2024) Project requirements prioritization through NLP-driven classification and adjusted work items analysis. Journal of Construction Engineering and Management, 150(03).

Lee, D, Nie, G Y and Han, K (2024) Automatic and real-time joint tracking and three-dimensional scanning for a construction welding robot. Journal of Construction Engineering and Management, 150(03).

Li, Q, Yang, Y, Yao, G, Wei, F, Xue, G and Qin, H (2024) Multiobject real-time automatic detection method for production quality control of prefabricated laminated slabs. Journal of Construction Engineering and Management, 150(03).

Oguz Erkal, E D, Hallowell, M R, Ghriss, A and Bhandari, S (2024) Predicting serious injury and fatality exposure using machine learning in construction projects. Journal of Construction Engineering and Management, 150(03).

Qureshi, A H, Alaloul, W S, Murtiyoso, A, Hussain, S J, Saad, S and Musarat, M A (2024) Automated scaling of point cloud rebar model via aruco-supported controlled markers. Journal of Construction Engineering and Management, 150(03).

Rajabi Asadabadi, M and Zwikael, O (2024) Unrealistic project goals: Detection and modification. Journal of Construction Engineering and Management, 150(03).

Sadeghi, N, Dehghani, M S and Ingolfsson, A (2024) Choice of probability distributions for activity durations in project networks with limited sample size. Journal of Construction Engineering and Management, 150(03).

Seo, W, Kim, B, Bang, S and Kang, Y (2024) Identifying key financial variables predicting the financial performance of construction companies. Journal of Construction Engineering and Management, 150(03).

Tarekegn Gurmu, A and Mahmood, M N (2024) Critical factors affecting quality in building construction projects: Systematic review and meta-analysis. Journal of Construction Engineering and Management, 150(03).

Withrow, J, Dadi, G, Nassereddine, H and Sturgill, R (2024) Asphalt material e-ticketing workflow: Qualitative and quantitative analysis. Journal of Construction Engineering and Management, 150(03).

Zhang, Y, Ren, X, Zhang, J and Ma, Z (2024) A method for deformation detection and reconstruction of shield tunnel based on point cloud. Journal of Construction Engineering and Management, 150(03).

  • Type: Journal Article
  • Keywords: building information model; deformation detection; point clouds; reconstruction; shield tunnel
  • ISBN/ISSN: 0733-9364
  • URL: http://doi.org/10.1061/JCEMD4.COENG-14225
  • Abstract:
    Detecting deformation and segment assembly quality in the construction or as-built phase of the shield tunnel is crucial and significant to ensure structural safety. The traditional detection methods consume much cost and are prone to errors. This study applies point cloud to develop robust algorithms for the deformation detection and reconstruction of shield tunnels. The methodology initially extracts the tunnel axis, serving as the base for deformation detection and reconstruction. A segmentation algorithm for continuous slice point clouds along the tunnel axis is proposed, and the deformation of the section is evaluated by ellipse fitting. In addition, a novel method of creating a binary image using the unrolled point cloud is adopted based on the extracted tunnel axis, and the segmentation of the segment point cloud is realized via image processing. This process is based on the geometric features of the unrolled point cloud, avoiding tedious parameter adjustment. Finally, a novel segment point cloud fitting method is used to create the as-built model of the tunnel in the BIM platform. To evaluate the performance of the proposed method, we select the shield tunnel case for experimental verification. The results show that (1) using point cloud information can realize an automated solution to complete the tunnel deformation detection task and meet accuracy requirements; and (2) the reconstruction method adopted in this study can realize the visualization of segment dislocation and has better efficiency and accuracy than previous algorithms. The work of this study has a certain guiding significance for the automated detection of the shield tunnel.