Image analysis for detecting the transverse profile of worn-out rails

G. Parla, M. Guerrieri, D. Ticali
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引用次数: 6

Abstract

Over its useful life a railway track is subject to many mechanical and environmental stresses which gradually lead to its deterioration. Monitoring the wear condition of the railway superstructure is one of the key points to guarantee an adequate safety level of the railway transport system; in this field, the use of high-efficiency laser techniques has become consolidated and implemented in diagnostic trains (e.g. the “Archimede train” and the “Talete train” ) which allow to detect the track geometric parameters (gauge, alignment, longitudinal level, cross level, superelevation defect, etc.) and the state of rail wear (vertical, horizontal, 45-degree etc.) with very high accuracy. The objective of this paper is to describe a new nonconventional procedure for detecting the transverse profile of worn-out rails by means of image-processing technique. This methodological approach is based on the analysis of the information contained in high-resolution photographic images of rails and on specific algorithms which allow to obtain the exact geometric profile and the measurement of the relevant deviations compared to new rails of the same typology. The analyses and the first results, obtained from laboratory researches, concern rails cross sections taken from railway lines under upgrading. The procedure has shown high precision in the wear evaluation as well as great rapidity in being performed.
图像分析用于检测磨损钢轨的横向轮廓
铁路轨道在其使用寿命期间受到许多机械和环境应力的影响,逐渐导致其老化。监测铁路上层建筑的磨损状况是保证铁路运输系统安全水平的关键之一;在这一领域,高效激光技术的使用已经在诊断列车(例如“阿基米德列车”和“Talete列车”)中得到巩固和实施,这些列车允许以非常高的精度检测轨道几何参数(轨距,对准,纵向水平,交叉水平,超仰角缺陷等)和轨道磨损状态(垂直,水平,45度等)。本文的目的是描述一种利用图像处理技术检测磨损轨道横向轮廓的新方法。这种方法是基于对铁轨高分辨率摄影图像中包含的信息的分析和特定算法,这些算法允许获得精确的几何轮廓和与相同类型的新铁轨相比的相关偏差的测量。从实验室研究中获得的分析和初步结果涉及正在升级的铁路线的铁轨横截面。结果表明,该方法具有较高的计算精度和计算速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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