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Title |
Automatic Detection and Visualization of Loosened Bolts in Steel Structures using Pattern Recognition-Based 3D Point Cloud Data Analysis
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Authors |
김민수(Minsu Kim) ; 강성근(Seong Keun Kang) ; 황순규(Soonkyu Hwang) |
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DOI |
https://doi.org/10.11112/jksmi.2025.29.6.142 |
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Keywords |
강구조물 접합부; 볼트 풀림 정량화; 볼트 풀림 시각화; 점군 데이터; Depth Vision; 패턴인식 Steel structure joints; Bolt Loosening Quantification; Bolt Loosening Visualization; Point Cloud Data; Depth Vision; Pattern recognition |
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Abstract |
This introduction proposes a pattern recognition-based point cloud data processing technique for the automated detection and visualization of bolt loosening in steel structures. The proposed technique detects loosening by quantifying bolt height based on distance information acquired from a depth vision camera. The automated detection of bolt joint loosening proceeds by first extracting the bolt joint region from point cloud data based on depth data. Subsequently, to ensure data quality, a planarization process is performed using Principal Component Analysis (PCA). Finally, to facilitate the recognition of the bolt region, a coordinate transformation is applied relative to the steel plate, thereby aligning the data. To detect bolt loosening, we quantified bolt height using a k-d tree-based radius search and the DBSCAN algorithm, and subsequently visualized the loosening. The proposed algorithm minimizes noise and distortion caused by on-site environmental variables, thereby enabling reliable inspection results even in outdoor field environments. Implemented using a portable inspection hardware system, the proposed method was experimentally validated on bolted joints of steel structures, demonstrating its ability to quantitatively detect and visualize bolt loosening with a a Root Mean Square (RMS) error within 1 mm.
Furthermore, lab-scale experiments were conducted to evaluate the accuracy of bolt loosening detection across a range of separation distances (100 mm to 500 mm) and measurement angles (30° to 90°), thereby establishing the reliability of the technique for practical field applications.
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