Image processing-based method for detecting shear damage in bridge rubber bearings
LIANG Dong
ZHANG Shaojie
ZHOU Yinxiao
WANG Lianxiang
ZHANG Qiang
LIU Yuefei
Abstract：Addressing the complexities presented by the beam and bridge plate rubber bearings,in-cluding their challenging accessibility because of deep location and the intricate measurement of shear deformation angles,this study introduces an automated method for shear angle calculation and shear damage assessment based on image analysis.Firstly,a U-Net network integrated with depth-wise separable convolution and an Multi-scale Attention Module(MAM)is employed to identify and segment the bearings within the images.Secondly,the binary image of the segmented bearings is used for extracting bearing contour lines through a simplified Alpha Shapes algorithm.Then the con-vex packet detection is performed to extract the convex packet points and their respective coordi-nates.Finally,the least-squares method is utilized to fit the convex packet points into straight lines,quantifying the degree of shear damage through the calculation of the shear angle between these lines.The research results show that the improved U-Net model for bearing segmentation demon-strates F1 scores and Intersection over Union(IoU)exceeding 95%.In a bridge inspection con-ducted in Tianjin,this paper's method is utilized to compare angle calculations from camera-captured bearing images with manual measurements.The maximum error between the two is re-corded at a mere 1.3 °,and shear damage level classification produces consistent results.This paper's method paves the way for non-contact,automatic shear damage detection in rubber bearings,pro-viding valuable insights for practical engineering applications.
Keywords：bridge engineeringplate rubber bearingshear damageimage processingU-Net
Publication Date：2023-10-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 16-24 )