| Author: | Zhang, Boyu |
| Title: | 3D-laser-scan-based automated assessment of appearance quality of precast concrete components : a standardized BIM framework |
| Advisors: | Shen, Qiping Geoffrey (BRE) |
| Degree: | Ph.D. |
| Year: | 2022 |
| Subject: | Precast concrete construction -- Evaluation Three-dimensional imaging Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Building and Real Estate |
| Pages: | xx, 191 pages : color illustrations |
| Language: | English |
| Abstract: | Precast concrete components are popularly adopted in buildings and infrastructures as they provide well-controlled quality, reduced construction time, and fewer environmental impacts. To ensure the performance of precast concrete structures, the appearance quality of precast concrete components should be assessed before assembly to avoid possible assembly difficulties or structural failures. Currently, the assessment of appearance quality of precast concrete components still relies on manual inspection, which is time-consuming and labour-intensive. Some inspection items, such as the roughness parameter of the joint surface of concrete components, cannot be assessed at construction sites with traditional methods. In addition, manual inspection is error-prone and unreliable. Thus, automated, accurate and effective detection methods for assessment of appearance quality are desired. Currently, three-dimensional (3D) laser scanning has gained a considerable amount of attention because of efficiently creating digital models of real objects. As the assessment of appearance quality focuses on the surface features of precast concrete components, it is possible to develop automatic detection methods by analysing the point clouds of precast concrete components created by a 3D laser scanner. The development of Building Information Modeling (BIM) offers the possibility to automatically match the design information, quality control requirements and detection results for a more effective assessment of appearance quality and management process. To address the above-mentioned research questions, the primary aim of this research was to develop automatic detection techniques for appearance quality assessment of concrete components, which can be applied in all required assessment phases, and to build an automated and standardized BIM framework based on the developed techniques to enable assessment and management of appearance quality of precast concrete components on BIM system. The specific objectives of this research are described as follows: (1) To develop an automated roughness detection technique for commonly used rough concrete surfaces, which accuracy, feasibility, and efficiency are validated. (2) To develop an automated shear key detection technique based on ontological analysis of the standard requirements and mechanical property of shear keys and to validate its accuracy and feasibility in real construction sites. (3) To develop and validate a dimensional quality detection technique with sufficient accuracy to meet the requirements of standards. (4) To design a standardized framework that enables assessment and management of appearance quality of precast concrete components on a BIM platform and to validate the applicability of the working process. The study developed three automated detection techniques for three representative inspection items—roughness parameter of a joint surface of concrete components, quality of shear keys and dimensional quality of precast concrete components—using 3D scan data from a handheld 3D laser scanner. In the development of each technique, first, the research gap was identified to verify the necessity. Second, a unique technique was developed by processing 3D scan data of small test blocks in a labouratory to solve the research problems and achieve specific assessment functions. Last, the accuracy, effectiveness and applicability of the proposed techniques are validated by different means, including cross-validation, testing on 3D-printed standard specimens and testing on precast concrete components at construction sites. The 3D-laser-scan-based roughness detection technique has been awarded as Patent for Invention in China (CN109612412B). Based on the developed detection techniques, a BIM framework for assessment of appearance quality and management was built. First, a standard BIM-based detection process of a single inspection item for a specified component was proposed. This process is applicable for not only the developed detection techniques in this research but also the automatic detection techniques to be developed in the future. Second, a standard sampling method for inspecting a large amount of precast concrete components was developed. This method can reduce the inspection workload while ensuring the quality of the whole inspection lot. Third, the system structure and key functions of the BIM framework were designed. The proposed BIM framework was developed and tested in a real construction project to verify its applicability and effectiveness. Last, the system error analysis and correction methods that have been developed for the three techniques offer a standard solution for other studies on the application of 3D laser scanners. In regard to the development process of the three detection techniques for assessment of appearance quality of precast concrete components using 3D data from handheld laser scanners, this research contributes to the body of knowledge by providing not only particular techniques but also a standard workflow and information flow for assessment of appearance quality, a method for analysing and correcting the system error of 3D laser scanners and a method for analysing key parameters for detection from basic design information by an ontological approach. The research also fills a current knowledge gap by developing a BIM framework for assessment of appearance quality and management, which enables a new application area of BIM technology. In addition, the application of handheld laser scanners overcomes the space limitations at construction sites, which renders automatic detection applicable in real construction projects. Moreover, the developed detection techniques and BIM framework are proved to be practicable and effective in real construction projects for reducing time and labour costs and avoiding cheating in quality assessment. |
| Rights: | All rights reserved |
| Access: | open access |
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