Detection and quantification of bolt loosening using RGB-D camera and Mask R-CNN

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Bolt loosening is one of the most common types of damage for bolt-connected plates. Existing vision techniques detect bolt loosening based on the measurement of bolt rotation or the exposure of bolt threads. However, these techniques examine bolt tightness only in a qualitative manner, or require a reference measurement at the initially tightened state of the bolt for quantitative estimation. In this study, the exposed shank length of a bolt is quantitatively measured using an RGB-depth camera and a mask-region-based convolutional neural network but without requiring any measurement from the initial state of the bolt. The performance of the proposed technique is validated by conducting lab-scale experiments, in which the angle and distance of the camera are varied with respect to a target inspection area. The proposed technique successfully detects bolt loosening at exposed shank length over 3 mm with a resolution of 1 mm and 97% accuracy at different camera angles (40°–90°) and distances (up to 65 cm).
Publisher
TECHNO-PRESS
Issue Date
2021-05
Language
English
Article Type
Article
Citation

SMART STRUCTURES AND SYSTEMS, v.27, no.5, pp.783 - 793

ISSN
1738-1584
DOI
10.12989/sss.2021.27.5.783
URI
http://hdl.handle.net/10203/285301
Appears in Collection
CE-Journal Papers(저널논문)
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