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, 30(10), pp. 5302-5332. ISSN 0969-9988
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | 3D point cloud; monitoring system; prefabricated building; prefabricated components segmentation |
| Index terms: | guarantee, experiment, accuracy, column, point cloud, laser scanning, construction project, progress monitoring, methodology, as-built model, construction process, construction quality, visualization, platform, schedule delay, frame structure, visual monitoring, monitoring, beam, prefabricated component, prefabricated building |
| Subjects: | quality assurance, project controls, building construction, production management, digital design, professional development, structural engineering, contract structure, design practice, research methods, analytical methods, technical documentation, control systems, design methods, data collection methods |
| Topics: | Research Practice, Project Management, Information Management, Engineering Principles, Procurement, Construction Technology, Quality Management, Design Practice, Digital Applications, Time Control, Site Management |
| Descriptive scope: | 4 PCTE |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here