铁路轨道智能诊断与维护系统

Erdem Balcı, Tunay Uzbay Yelce, Ertan Yalçin, N. Bezgin
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摘要

近年来,人工智能(AI)、物联网(IoT)、大数据等先进技术日益凸显。这些技术在各个部门都有广泛的应用领域。铁路系统作为人员和货物运输的重要组成部分,应该通过整合新技术来改进。成功发现轨道故障并完成相应的运行维护任务,对铁路运行安全至关重要。目前,通过机器学习应用程序进行图像处理和模式识别通常用于自动轨道检查。然而,铁路轨道与现有技术的完美结合是不可能的。本文介绍了传统的轨道检测维护方式与智能的轨道检测维护方式的区别。指出了先进技术应用于铁路轨道的不足,并讨论了进一步改进的措施。最后,对智能系统的使用对结构生命周期的影响进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Diagnosis And Maintenance Systems For Railway Tracks
: In recent years, advanced technologies such as artificial intelligence (AI), the internet of things (IoT), and big data came into prominence. These technologies found an extensive area of utilization in various sectors. Railway systems as an important part of the transportation of people and goods should be improved by the integration of novel technologies. Successful detection of track faults and operating maintenance tasks accordingly are essential for the safety of railway operations. Currently, image processing and pattern recognition via machine learning applications are in common use for automated track inspections. However, it is not possible to claim that railway tracks are integrated with current technology perfectly. In this work, differences between the traditional way and the smart way of track inspection and maintenance are presented. Shortcomings of the application of advanced technologies into railway tracks are detected and required actions for further improvements are discussed. Lastly, the effects of the use of smart systems on the life cycle of the structures are evaluated.
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