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Description

An electric railway vehicle is supplied with electricity by an OCL (Overhead Contact Line) through the contact strip of its pantograph. This transmitted electricity is then used to power the electrical equipment of the railway vehicle. This contact strip wears out due to contact with the OCL. In particular, deformations due to chipping and material loss occur because of friction with the fittings on the OCL. These deformations on the contact strip affect its power transmission quality because of contact loss with the OCL. However, it is difficult to monitor the contact strip during operation and judge its condition in order to implement accident prevention measures. Thus, in this study, we developed a contact strip monitoring method based on image processing for inspection. The proposed method measures the deformation in the contact strip based on an algorithm that determines the wear on the deformed contact strip using deep learning and image processing. The image of the contact strip is acquired by installing a camera and laser to capture the pantograph as it passes the setup. The proposed algorithm is able to determine the wear size by extracting the edges of the laser line using deep learning and estimating the fitted line of the deformations based on the least squares method.