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Smart Structures and Systems Volume 32, Number 1, July 2023 , pages 23-35 DOI: https://doi.org/10.12989/sss.2023.32.1.023 |
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Corroded and loosened bolt detection of steel bolted joint based on improved you only look once network and line segment detector |
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Youhao Ni, Jianxiao Mao, Hao Wang, Yuguang Fu and Zhuo Xi
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| Abstract | ||
| Steel bolted joint is an important part of steel structure, and its damage directly affects the bearing capacity and durability of steel structure. Currently, the existing research mainly focuses on the identification of corroded bolts and corroded bolts respectively, and there are few studies on multiple states. A detection framework of corroded and loosened bolts is proposed in this study, and the innovations can be summarized as follows: (i) Vision Transformer (ViT) is introduced to replace the third and fourth C3 module of you-only-look-once version 5s (YOLOv5s) algorithm, which increases the attention weights of feature channels and the feature extraction capability. (ii) Three states of the steel bolts are considered, including corroded bolt, bolt missing and clean bolt. (iii) Line segment detector (LSD) is introduced for bolt rotation angle calculation, which realizes bolt looseness detection. The improved YOLOv5s model was validated on the dataset, and the mean average precision (mAP) was increased from 0.902 to 0.952. In terms of a lab-scale joint, the performance of the LSD algorithm and the Hough transform was compared from different perspective angles. The error value of bolt loosening angle of the LSD algorithm is controlled within 1.09%, less than 8.91% of the Hough transform. Furthermore, the proposed framework was applied to fullscale joints of a steel bridge in China. Synthetic images of loosened bolts were successfully identified and the multiple states were well detected. Therefore, the proposed framework can be alternative of monitoring steel bolted joints for management department. | ||
| Key Words | ||
| "corroded and loosened bolt detection; improved YOLOv5s; linear segment detector; steel bolted joints; vision transformer" | ||
| Address | ||
| "(1) Youhao Ni, Jianxiao Mao, Hao Wang, Zhuo Xi: Key Laboratory of C&PC Structures of Ministry of Education, Southeast University, Nanjing, 211189, China; (2) Youhao Ni, Jianxiao Mao, Hao Wang, Zhuo Xi: School of Civil Engineering, Southeast University, Nanjing 211889, China; (3) Yuguang Fu: School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore." | ||