Mr. Yu-Wei Liu Profile

Yu-Wei Liu

at Taiwan Semiconductor Manufacturing Co Ltd

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Publications (2)

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Proceedings Article | 3 April 2018 Presentation

2D and 3D PCD algorithms for deformation monitoring of reinforced concrete structural elements (Conference Presentation)

Tsung-Chin Hou, Yu-Min Su, Jen-Wei Liu, Tien-Yo Wu, Peng-Tu Wang, Cheng-Yan Wu, Yu-Wei Liu, Hsuan-Teh Hu

Proceedings Volume 10602, 106020A (2018) https://doi.org/10.1117/12.2300503

KEYWORDS: Laser scanners, Clouds, 3D scanning

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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.

Proceedings Article | 22 April 2016 Paper

Geometric identification and damage detection of structural elements by terrestrial laser scanner

Tsung-Chin Hou, Yu-Wei Liu, Yu-Min Su

Proceedings Volume 9804, 98041A (2016) https://doi.org/10.1117/12.2222298

KEYWORDS: Chemical elements, Damage detection, Laser scanners, 3D scanning, Clouds, Detection and tracking algorithms, Structural monitoring, Data modeling, 3D modeling, Fuzzy logic, Reflection, Civil engineering, RGB color model

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In recent years, three-dimensional (3D) terrestrial laser scanning technologies with higher precision and higher capability are developing rapidly. The growing maturity of laser scanning has gradually approached the required precision as those have been provided by traditional structural monitoring technologies. Together with widely available fast computation for massive point cloud data processing, 3D laser scanning can serve as an efficient structural monitoring alternative for civil engineering communities. Currently most research efforts have focused on integrating/calculating the measured multi-station point cloud data, as well as modeling/establishing the 3D meshes of the scanned objects. Very little attention has been spent on extracting the information related to health conditions and mechanical states of structures. In this study, an automated numerical approach that integrates various existing algorithms for geometric identification and damage detection of structural elements were established. Specifically, adaptive meshes were employed for classifying the point cloud data of the structural elements, and detecting the associated damages from the calculated eigenvalues in each area of the structural element. Furthermore, kd-tree was used to enhance the searching efficiency of plane fitting which were later used for identifying the boundaries of structural elements. The results of geometric identification were compared with M3C2 algorithm provided by CloudCompare, as well as validated by LVDT measurements of full-scale reinforced concrete beams tested in laboratory. It shows that 3D laser scanning, through the established processing approaches of the point cloud data, can offer a rapid, nondestructive, remote, and accurate solution for geometric identification and damage detection of structural elements.

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