An efficient image-based damage detection for cable surface in cable-stayed bridges

Abstract

Since cable members are the major structural components of cable bridges, they should be properly inspected for surface damage and inside defects such as corrosion and/or breakage of wires. This study introduces an efficient image-based damage detection system that can automatically identify damages to the cable surface through image processing techniques and pattern recognition. The damage detection algorithm combines image enhancement techniques with principal component analysis (PCA) algorithm. Images from three cameras attached to a cable climbing robot are wirelessly transmitted to a server computer located on a stationary cable support. To improve the overall quality of the images, this study utilizes an image enhancement method together with a noise removal technique. Next the input images are projected into PCA sub-space, the Mahalanobis square distance is used to determine the distances between the input images and sample patterns. The smallest distance is found to be a match for an input image. The proposed damage detection algorithm was verified through laboratory tests on three types of cables. Results of the tests showed that the proposed system could be used to detect damage to bridge cables.