This study explored the potential of combining point cloud data (PCD) and 2D/3D PCD algorithms for deformation monitoring of common reinforced concrete (RC) structural elements. The RC specimens tested in the laboratory include three beam (30x50x400 cm) elements and three slab (150X15X350 cm) elements under uniaxial loading. PCDs of each specimen were acquired by 3D laser scanner over the loading processes and used to extract the deformation at each loading step. Deformation monitoring was also accompanied with traditional LVDT instrumentations for later comparison with the PCD ones. Each specimen was loaded with several steps till failure; within each interval the PCDs of RC specimens were scanned. 2D edge extractions and direct 3D surface fittings were used as the PCD algorithms for extracting the deformation information of the specimens at each loading step. By comparing the results with LVDT readings, it was shown that PCD algorithms can enhance the accuracy of laser scanner for deformation monitoring of RC structural elements and give comparable results with LVDTs. It is also shown that the enhanced measuring accuracy is subjected to the PCD algorithms. Nevertheless, this study successfully demonstrated the applicability of 2D/3D PCD algorithms for whole field deformation monitoring of RC structural elements.
Tsung-Chin Hou, Yu-Min Su, Jen-Wei Liu, Tien-Yo Wu, Peng-Tu Wang, Cheng-Yan Wu, Yu-Wei Liu, and Hsuan-Teh Hu, "2D and 3D PCD algorithms for deformation monitoring of reinforced concrete structural elements (Conference Presentation)," Proc. SPIE 10602, Smart Structures and NDE for Industry 4.0, 106020A (Presented at SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring: March 05, 2018; Published: 3 April 2018); https://doi.org/10.1117/12.2300503.5763115403001.
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