Detecting corrugation defects in harbour railway networks using axle-box acceleration data

J. Heusel, B. Baasch, W. Riedler, Michael Roth, S. Shankar, J. Groos
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引用次数: 3

Abstract

Sea- and inner ports are intermodal traffic nodes that play an important role in transportation, especially in the transportation of goods. The appearance of track defects in a harbour railway network has a negative impact on safety, cost and comfort (for example due to noise emission). The analysis of data obtained by embedded acceleration sensors, which are installed at the axle box of an equipped in-service vehicle, allows for continuous condition monitoring of the track infrastructure. The German Aerospace Center (DLR) develops prototypical modular multi-sensor systems that are used in different operational environments, including on a shunter locomotive operating in an industrial harbour railway network in Braunschweig, Germany. Within the HavenZuG research project, extensive rail longitudinal profile and track geometry measurements have been performed using established inspection methods to obtain the true underlying condition of the railway network. In the present paper, methods for gaining relevant information from the axle-box acceleration (ABA) data are presented and validated with the given reference data. The focus is on detecting defects that are visible in the rail longitudinal profile, mainly rail corrugation. It can be shown that ABA data gathered during everyday shunting operation can be used for detecting corrugation and for inferring rail longitudinal profile parameters.
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利用轴箱加速度数据检测港口铁路网波纹缺陷
海港和内港是多式联运的枢纽,在运输特别是货物运输中起着重要的作用。海港铁路网轨道缺陷的出现对安全、成本和舒适度有负面影响(例如由于噪音排放)。嵌入式加速度传感器安装在现役车辆的轴箱上,通过对传感器获取的数据进行分析,可以对轨道基础设施进行持续状态监测。德国航空航天中心(DLR)开发了用于不同操作环境的原型模块化多传感器系统,包括在德国不伦瑞克的工业港口铁路网络中运行的分流机车上。在HavenZuG研究项目中,使用既定的检查方法进行了广泛的铁路纵剖面和轨道几何测量,以获得铁路网的真实基本状况。本文提出了从轴箱加速度(ABA)数据中获取相关信息的方法,并用给定的参考数据进行了验证。重点是检测在钢轨纵剖面上可见的缺陷,主要是钢轨波纹。结果表明,在日常调车作业中收集的ABA数据可用于检测波纹和推断轨道纵剖面参数。
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