An Automated Sensing System for Steel Bridge Inspection Using GMR Sensor Array and Magnetic Wheels of Climbing Robot

Abstract

Corrosion is one of the main causes of deterioration of steel bridges. It may cause metal loss and fatigue cracks in the steel components, which would lead to the collapse of steel bridges. This paper presents an automated sensing system to detect corrosion, crack, and other kinds of defects using a GMR (Giant Magnetoresistance) sensor array. Defects will change the relative permeability and electrical conductivity of the material. As a result, magnetic field density generated by ferromagnetic material and the magnetic wheels will be changed. The defects are able to be detected by using GMR sensor array to measure the changes of magnetic flux density. In this study, magnetic wheels are used not only as the adhesion device of the robot, but also as an excitation source to provide the exciting magnetic field for the sensing system. Furthermore, compared to the eddy current method and the MFL (magnetic flux leakage) method, this sensing system suppresses the noise from lift-off value fluctuation by measuring the vertical component of induced magnetic field that is perpendicular to the surface of the specimen in the corrosion inspection. Simulations and experimental results validated the feasibility of the system for the automated defect inspection.