結(jié)合點云距離和角度雙閾值的 橋梁拉索表面缺陷精確檢測

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關(guān)鍵詞：橋梁拉索；表面缺陷檢測；點云；感興趣區(qū)域提??；法向量中圖分類號：TP391文獻標(biāo)志碼：ADOI：10.7652/xjtuxb202506016 文章編號：0253-987X（2025）06-0155-12

Precise Detection of Surface Defects in Bridge Cables Using Combined Point Cloud Distance and Dual-Threshold Angle Analysis

XIAXiaohua，ZHUYingshuo，QIU Fabo，CHENJian （Key Laboratoryof RoadConstruction Technologyand Equipmentof MOE，Chang'an University，Xi'an71oo64，China）

Abstract： To address the issues of mis-segmentation and high computational complexity in the application of point cloud segmentation algorithms to bridge cable surface defect detection，a precise detection method for bridge cable surface defects based on dual thresholds of point cloud distance and angle is proposed in this paper. First， a distance threshold was established between the cable surface points and the fitted cylindrical surface to facilitate preliminary defect detection. Then，a region of interest （ROI） extraction method for cable surface defects was designed， combining point cloud clustering and box filtering. Based on the preliminary detection results， the ROI was segmented using an improved Euclidean clustering algorithm coupled with box filtering. Finally，a defect boundary detection method was constructed based on the angle between the point cloud normal vector and the radial vector of the fitted cylinder. The defect points within the ROI were segmented by setting an angle threshold，enabling precise detection of the defect boundaries on the cable surface. Research results demonstrated that，compared with methods that do not perform ROI extraction or those that extract ROI without point cloud clustering，the proposed method reduced the point cloud data volume by more than 40% ，thereby shortening the detection time by over 15% . The average precision and recall rates for cable surface defect detection reached 96.83% and 94.42% ，respectively，with a F -score of 95.58% ， outperforming the comparative random sample consensus algorithm and the region growing algorithm. This validates the effectiveness and advancement of the proposed method.

Keywords： bridge cable；surface defect detection； point cloud; region of interest extraction； normalvector

拉索作為索承體系橋梁的關(guān)鍵受力構(gòu)件，其承重和傳遞荷載能力是橋梁安全運行的關(guān)鍵[1]。（剩余18881字）