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Image processing based fault detection approach for rail surface

机译:基于图像处理的轨道表面故障检测方法

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Railway transport is getting more and more preferred mode of transportation. Railway line should be established in a robust manner because of construction of used heavy vehicles. A small fault, which occurs in the railway line, can lead to serious accidents. Therefore, the railway line should be controlled at certain time intervals. Faults detected during the control process should be repaired and the required maintenance should be performed. In this study, an image processing based method has been proposed to detect the defects of rail surface. In the proposed method, the images were taken from two cameras, which of them were placed at different angles on the experimental setup. The preprocessing stage was made by applying OTSU method to obtained images. The rail surface is determined by using Canny edge detection and Hough transform. Faults occurred on the rail surface were detected by combining images taken from two camera. The accuracy of the proposed method was increased by using the images taken from two different cameras.
机译:铁路运输正越来越受到人们的青睐。由于二手重型车辆的建造,应该以稳健的方式建立铁路线。在铁路线上发生的小故障可能会导致严重的事故。因此,应该以一定的时间间隔控制铁路线。在控制过程中发现的故障应予以修理,并应进行必要的维护。在这项研究中,提出了一种基于图像处理的方法来检测轨道表面的缺陷。在所提出的方法中,图像是从两个相机拍摄的,它们在实验装置上以不同的角度放置。预处理阶段是通过使用OTSU方法获得的图像进行的。轨道表面通过使用Canny边缘检测和Hough变换确定。通过组合从两个摄像机拍摄的图像,可以检测出发生在轨道表面的故障。通过使用从两个不同的摄像头拍摄的图像,提高了所提方法的准确性。

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