An approach for monitoring prefabricated building construction based on feature extraction and point cloud segmentation
Engineering, Construction and Architectural Management
ISSN: 0969-9988
Article publication date: 30 August 2022
Issue publication date: 28 November 2023
Abstract
Purpose
Construction schedule delays and quality problems caused by construction errors are common in the field of prefabricated buildings. The effective monitoring of the construction project process is one of the key factors for the success of a project. How to effectively monitor the construction process of prefabricated building construction projects is an urgent problem to be solved. Aiming at the problems existing in the monitoring of the construction process of prefabricated buildings, this paper proposes a monitoring method based on the feature extraction of point cloud model.
Design/methodology/approach
This paper uses Trimble X7 3D laser scanner to complete field data collection experiments. The point cloud data are preprocessed, and the prefabricated component segmentation and geometric feature measurement are completed based on the PCL platform. Aiming at the problem of noisy points and large amount of data in the original point cloud data, the preprocessing is completed through the steps of constructing topological relations, thinning, and denoising. According to the spatial position relationship and geometric characteristics of prefabricated frame structure, the segmentation algorithm flow is designed in this paper. By processing the point cloud data of single column and beam members, the quality of precast column and beam members is measured. The as-built model and as-designed model are compared to realize the visual monitoring of construction progress.
Findings
The experimental results show that the dimensional measurement accuracy of beam and column proposed in this paper is more than 95%. This method can effectively detect the quality of prefabricated components. In the aspect of progress monitoring, the visualization of real-time progress monitoring is realized.
Originality/value
This paper proposed a new monitoring method based on feature extraction of the point cloud model, combined with three-dimensional laser scanning technology. This method allows for accurate monitoring of the construction process, rapid detection of construction information, and timely detection of construction quality errors and progress delays. The treatment process based on point cloud data has strong applicability, and the real-time point cloud data transfer treatment can guarantee the timeliness of monitoring.
Keywords
Acknowledgements
The authors' special thanks go to all survey participants and reviewers of the paper, and appreciation to National Natural Science Foundation of China (72071043), Natural Science Foundation of Jiangsu Province (BK20201280), and the Ministry of Education of Humanities and Social Science Project in China (20YJAZH114).
Data availability statement: Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Citation
Xu, Z., Liang, Y., Lu, H., Kong, W. and Wu, G. (2023), "An approach for monitoring prefabricated building construction based on feature extraction and point cloud segmentation", Engineering, Construction and Architectural Management, Vol. 30 No. 10, pp. 5302-5332. https://doi.org/10.1108/ECAM-11-2021-0985
Publisher
:Emerald Publishing Limited
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