Registration method for maintenance-work support based on augmented-reality-model generation from drawing data.

Autor: Won-Hyuk Lee, Kyung-Ho Lee, Jung-Min Lee, Byeong-Wook Nam
Předmět:
Zdroj: Journal of Computational Design & Engineering; Dec2020, Vol. 7 Issue 6, p775-787, 13p
Abstrakt: The importance of operations and maintenance (O&M) and piping inspection in shipbuilding and offshore plant industries has significantly increased recently. Therefore, this study proposes a system that uses augmented reality (AR) to support these operations. AR in O&M and inspection systems can increase work comprehension and efficiency by utilizing 3D graphics, instead of drawings, to describe specific work functions. To realize this improvement, the augmented model should correspond to the reality; if accurate registration is not achieved, it can disrupt the work functions. Therefore, marker-based AR is used to generate specific recognition objects and correct the location of the augmented model. However, owing to certain characteristics of the shipbuilding and offshore plant industries, the markers are likely to be damaged, and thus the cameras fail to clearly detect them. In this study, a 3D camera was used to generate a point cloud based on 3D image information. Accordingly, the area around the model to be detected was designated as the region of interest (ROI). Furthermore, it is difficult to support a high-end device environment because it is tested as a portable device that can be used in a working environment; therefore, superfluous data were removed by detecting the 3D edges in the ROI, thereby minimizing data operation. The scalability of this work was enhanced using the computer-aided design (CAD) file information extracted from the CAD tool (used in the shipbuilding industry) and converting it into a point cloud. The proposed system is expected to eliminate the issues related to understanding the O&M work by addressing registration errors that might occur in constrained environments and to improve the torsional phenomenon of the augmented models. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index