In this study, an automated cable non-destructive test (NDT) system was proposed to monitor the steel cable. Magnetic Flux Leakage (MFL) method was applied for the cable inspection. A multi-channel MFL sensor head was fabricated using Hall sensors and permanent magnets. A wheel based Cable climbing robot was used to improve the accessibility to cable. In addition, remote data transmission and robot control were possible by applying the Wireless LAN communication. Finally, developed element techniques were integrated to MFL based Cable Climbing NDT system, and the field applicability of the integrated cable NDT system was verified through a field test.

Since cable members are the major structural components in cable bridges, they should be properly inspected for surface damage as well as inside defects such as corrosion and/or breakage of wires. Starting from August 2010, a new research project supported by Korea Ministry of Land, Transportation Maritime Affairs (MLTM) was initiated to develop the cable inspection robot. In this study, only the vision-based surface damage detection system based on image processing techniques is addressed. The damage detection algorithm combines some image enhancement techniques with principal component analysis (PCA) to detect damages on cable surface. The images from three cameras attached to the cable climbing robot are wirelessly transmitted to the server computer at the cable support. They are processed with image enhancement method together with noise removal technique to improve overall image quality. Then they are projected into PCA sub-space. Finally, the Mahalanobis square distances of the projected images to all sample patterns are calculated. The smallest distance is found to be the match for the input image. The proposed damage detection algorithm was verified through laboratory tests on three types of cables.