A Fault Diagnosis Approach for Rail Surface Anomalies Using FPGA in Railways

Year 2017, Special Issue (2017), 42 - 46, 24.09.2017

Orhan Yaman , Mehmet Karakose , Erhan Akin

https://doi.org/10.18100/ijamec.2017SpecialIssue30469

Cited By: 2

Abstract

Railway transport is a widely used means of transportation for passenger and cargo transportation. In recent years, more emphasis has been placed on railway transport. With the development of high-speed trains, it has become important for passenger transport. Due to the heavy construction of the train, continuous failures occur in the railway line. Various methods of inspection are available to detect these failures. In case of early fault detection and repair of major accidents can be prevented. In this study, an FPGA based method is proposed for rail surface inspection and fault diagnosis. The proposed method is realized by image processing with FPGA. The image is taken on the railway line with the camera attached to the FPGA development board. Pre-processing is performed on the obtained image. Edge extraction is applied to the image after pre-processing. The rail surface is detected using the image obtained as a result of edge extraction. The proposed method works in real time to monitor and diagnose faults. It detects many defects on the track surface. In addition, the proposed method measures the size of the fault on the rail surface. In this study, FPGA based condition monitoring device was developed. An architecture has been developed for implementing the proposed method with FPGA.  This work using FPGA technology is low cost and fast compared to other methods. The proposed method is quite advantageous because of its real-time operation.

Keywords

Railway , Rail surface detection , Condition monitoring , Embedded system , Image processing

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