Yazar "Bettemir O.H." seçeneğine göre listele

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    Detection of railway track from image by heuristic method
    (Institute of Electrical and Electronics Engineers Inc., 2015) Bettemir O.H.
    Defects on the railway track occur due to the abrasive effects of time and usage. As the magnitude of the defects increases, uncomfortable travel appears. If the defects progress further they may cause derailment of the train. Detection of the defects are performed by manual inspection of the track, which cause ignorance of some of the defects. In this study a heuristic algorithm, which detects railway track from the images acquired by unmanned vehicle, is developed. Rails and sleepers of the railway track is detected with high accuracy from the images acquired in nadir direction. Images are de-noised by Gauss filter and edges are detected by Prewitt Edge Detection algorithm. By considering the geometric properties of the railway track and the brightness values of the edges, the Heuristic algorithm decides on which edges belong to railway track. In this study, inspection of railways is proposed by the images acquired by unmanned aerial vehicles and the automated detection of railway elements are realized as the first step of the railway inspection. © 2015 IEEE.
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    Quality and safety assurance of railway tracks by UAV
    (American Society of Mechanical Engineers (ASME), 2015) Bettemir O.H.
    Safety assurance of railway tracks is an important task because defects on the railway track may cause trains to be derailed. Unfortunately, there are many fatal train crashes reported in Turkey, Spain and India caused by derailment of the trains. Besides the fatalities, derailment of the trains causes significant economic losses, delay of the timetables and discomfort. Manually investigating the railway tracks are substantially time consuming and expensive. In addition to this, it is human dependent so that the task is prone to error, which may end up without noticing important defects. In this study, a robust and economical method, which automates the investigation of railway tracks, is proposed. The proposed method scans the railway track by a high-resolution optic camera mounted on an UAV. Obtained optic images of the railway track are georeferenced by automatically extracting the Ground Control Points (GCP). The railway track is extracted from the optic image by edge detection. Afterward, any defect on the railway track such as missing bolt or damage on the sleepers and any impropriety of ballasts can be detected by performing image analysis techniques. Advantages of the optic system are its lightweight, higher georeferencing accuracy, and low power consumption. Sony HX300 DSLR camera with 20.4 MP resolution is calibrated on the ground and optical images are obtained at similar imaging geometry. For this reason, flight altitude is fixed as 12 foot above the railway track. The optical camera is mounted on quadcopter, which has 6 kg of maximum take-off weight. The system is tested in Pittsburgh and satisfactory initial test results are obtained. Consequently, site tests showed that the proposed robust and economic system is a good candidate to be implemented for monitoring the railway tracks. © Copyright 2015 by ASME.