Real time implementation for fault diagnosis and condition monitoring approach using image processing in railway switches

Abstract

Today, railway transportation is one of the transport modes commonly used. Compared to other transport modes, railway traffic is highly critical. Multiple railway vehicles run constantly on one or two lines. Rail switch passages are used to prevent locomotives from colliding with one another and avoid traffic disruptions. Through switch passages, locomotives pass from one line to another. Friction between rail and wheels on switch passages is considerably high. This friction leads to failures on switch passages. Unless these failures are diagnosed early and remedied, significant accidents emerge.   In this study, a new approach based on image processing has been presented for detection of rail switch passages on railway lines. A test vehicle has been created in order to test the proposed approach and apply it on a real-time system. Railway line is monitored by digital cameras fixed on this test vehicle. Image-processing approach is developed on the real-time images captured from the railway line and the switch passages on the line are detected. In addition, by specifying the train route, the fault which occurring at the point of the switches is detected. The image-processing approach consists of three main parts including pre-processing, feature extraction and processing of the features obtained. At the pre-processing stage, the basic image processing methods are used. At the feature extraction stage, Canny edge extraction algorithm is used and hence the edges in the image are detected. Hough transform method is used at the stage of processing of the extracted features. Following Hough transform stage, straight lines and angles of these lines are obtained on the image. Taking into account the angle of each straight line, the junction points of the lines are calculated. Thus, rail switch passage and switch types are detected. The proposed image-processing approach is highly fast and real time-based. Compared to the existing studies in the literature, it is seen that the proposed method gives fast and successful results. This study intends to diagnose the failures on switch passages early and prevent potential accidents.