PURPOSES: The purpose of this study is to evaluate different types of Ground Penetrating Radar (GPR) testing for characterizing the road cavity detection. The impulse and step-frequency-type GPR tests were conducted on a full-scale testbed with an artificial void installation. After analyzing the response signals of GPR tests for detecting the road cavity, the characteristics of each GPR response was evaluated for a suitable selection of GPR tests. METHODS: Two different types of GPR tests were performed to estimate the limitation and accuracy for detecting the cavities underneath the asphalt pavement. The GPR signal responses were obtained from the testbed with different cavity sizes and depths. The detection limitation was identified by a signal penetration depth at a given cavity for impulse and step-frequency-type GPR testing. The unique signal characteristics was also observed at cavity sections. RESULTS: The impulse-type GPR detected the 500-mm length of cavity at a depth of 1.0 m, and the step-frequency-type GPR detected the cavity up to 1.5 m. This indicates that the detection capacity of the step-frequency type is better than the impulse type. The step-frequency GPR testing also can reflect the howling phenomena that can more accurately determine the cavity. CONCLUSIONS : It is found from this study that the step-frequency GPR testing is more suitable for the road cavity detection of asphalt pavement. The use of step-frequency GPR testing shows a distinct image at the cavity occurrences.

Steel cables are frequently used for various infrastructures. Especially the steel cables in long span bridges are critical members Damage at cable members can occur in the form of cross sectional loss caused by corrosion and fracture. Therefore, NDE of steel cable is needed to measure the cross-sectional damage. In this study, Total Magnetic Flux sensor system was applied to monitor the condition of cables. This system measures total magnetic flux to detect the loss of metallic cross section area(LMA) of steel cable. To verify the feasibility of this study, 2 types of steel bar were fabricated and their output values measured by the search coil in total flux sensor.

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. In this study, only the vision-based surface damage detection system based on image processing techniques is addressed. The damage detection programs are consist of real-time and post processing detection programs. The proposed damage detection programs were verified through laboratory tests on many types of cables.

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.