Three-dimensional reconstruction method of rail corrugation based on the vision detection

Abstract

In order to realise the visual identification of the three-dimensional geometric characteristics of the rail corrugation, the three-dimensional reconstruction method of rail corrugation based on vision detection is developed in the present paper. The acquisition equipment is firstly designed to acquire the images of rail corrugation and corresponding depth information. Then, the image preprocessing method is proposed to achieve the automatic segmentation of rail corrugation images. The fitting equation between the image and depth of rail corrugation is obtained, which allows the three-dimensional reconstruction of rail corrugation. Furthermore, based on the finite element model of the wheel-rail system and the wear calculation model, the practicality and effectiveness of the three-dimensional reconstruction method are verified. Results show that the depth-grayscale correlation equation is well fitted with the coefficient of determination of 0.94 and the root mean square error of 0.02. The three-dimensional reconstruction method has an error of 2.63% at the maximum wear depth. When the three-dimensional reconstruction method is applied to the wear prediction of rail corrugation, the wear prediction of rail corrugation with the three-dimensional reconstruction is approximately the same as the actual wear distribution, which has an error of 5.02% at the maximum wear depth. The above results demonstrate the effectiveness of the three-dimensional reconstruction method of rail corrugation based on the vision detection.