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Vibration and Impact Monitoring of Tram Operations

有轨电车运营的振动和冲击监测

基本信息

批准号：
1946489
负责人：
金额：
--
依托单位：
University of Cambridge
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1946489
关键词：
Vibration Impact Monitoring Tram Operations

项目摘要

This project aims to develop a system for monitoring the condition of railway track using sensors mounted on in-service trains and trams, as part of the infrastructure and urban systems theme. The surface roughness of railway track increases during service. Along with other forms of deterioration, such as settlement at rail joints, this leads to an increase in the level of vibration generated as a vehicle runs along the track. From its origin at the wheel-rail interface, vibration propagates through the track structure, through the ground and into nearby buildings, where it may then cause disturbance as perceptible vibration and/or re-radiated noise. A significant portion of railways in the UK run through densely populated urban areas. The proximity to residential properties, and sensitive buildings such as concert halls and hospitals, means that groundborne vibration is a major concern of urban railway operators, who must work continuously at track maintenance to keep noise and vibration within acceptable levels. Currently, this work relies on manual track inspections, typically undertaken fortnightly, to identify areas of deterioration before they become a significant source of vibration. Such inspections are time consuming and costly. There is a clear need for a more efficient monitoring method.This research aims to develop a track condition monitoring system that can be permanently installed on service rail vehicles running on an operational network. It builds on recent prior work that saw five axlebox accelerometers and associated data acquisition and positioning equipment fitted to one of Midland Metro's CAF Urbos 3 trams. This equipment has been collecting useful data over Midland Metro's rail network since 10th August 2016. Similar equipment may be fitted to one of London Underground Limited's trains in the near future to provide a second source of data for this research. The main objective is to derive the wheel-rail interface force spectrum and the railhead's roughness spectrum from the measurements of vertical axlebox acceleration and vehicle location and speed, and relate these spectra to the amount of groundborne noise injected into the ground as the vehicle runs over the rail. This requires the entire mechanical system between the rail and the axlebox to be considered. Inherent challenges in the signal processing include separating out the vibration caused by wheel roughness, and the necessary correction for vehicle speed, both of which enable measurements from different passes over the same rail section to be compared directly. The next objective is to create a virtual condition map of the network. The track will be divided into short segments over each of which the roughness spectrum is computed and presented. Peak and/or average levels at each track segment will be plotted over location for the entire network to give the operator an overview of the condition of the network. Further research is required into the most appropriate segment lengths that offer a useful compromise between wavelength resolution and spatial resolution along the track. A networked system will be developed that automatically collects vibration data from the vehicles by means of wireless communication, and updates a virtual condition map in real time. Algorithms will be developed to identify vibration transients (caused by misaligned turnouts, crossings, poor rail joints etc.) in addition to exceedances in railhead roughness levels. It is anticipated that the levels of vibration will be monitored in order to schedule rail maintenance before these levels rise above a certain limit.

该项目旨在开发一种使用安装在运行中的火车和有轨电车上的传感器来监测铁路轨道状况的系统，作为基础设施和城市系统主题的一部分。铁路轨道在使用过程中表面粗糙度会增加。连同其他形式的恶化（例如铁轨接头处的沉降），这会导致车辆沿轨道行驶时产生的振动水平增加。振动从轮轨界面的起源开始，通过轨道结构传播，通过地面传播到附近的建筑物，然后可能会造成可察觉的振动和/或再辐射噪声的干扰。英国很大一部分铁路穿过人口稠密的城市地区。靠近住宅区以及音乐厅和医院等敏感建筑，意味着地面振动是城市铁路运营商的主要关注点，他们必须持续进行轨道维护工作，将噪音和振动保持在可接受的水平。目前，这项工作依赖于手动轨道检查，通常每两周进行一次，以在恶化区域成为重要的振动源之前识别它们。此类检查既耗时又昂贵。显然需要一种更有效的监测方法。本研究旨在开发一种轨道状态监测系统，可以永久安装在运行网络上运行的服务轨道车辆上。它建立在最近的先前工作的基础上，该工作在米德兰地铁的一辆 CAF Urbos 3 有轨电车上安装了五个轴箱加速度计以及相关的数据采集和定位设备。自 2016 年 8 月 10 日以来，该设备一直在米德兰地铁的铁路网络上收集有用数据。在不久的将来，类似的设备可能会安装到伦敦地铁有限公司的一列火车上，为本次研究提供第二个数据源。主要目标是从垂直轴箱加速度以及车辆位置和速度的测量中得出轮轨界面力谱和轨头粗糙度谱，并将这些谱与车辆在轨道上行驶时注入地面的地面噪声量相关联。这就需要考虑钢轨和轴箱之间的整个机械系统。信号处理中固有的挑战包括分离出车轮粗糙度引起的振动，以及对车辆速度进行必要的校正，这两者都使得可以直接比较同一轨道部分上不同路径的测量结果。下一个目标是创建网络的虚拟条件图。轨迹将被分成短段，在每个段上计算并呈现粗糙度谱。每个轨道段的峰值和/或平均水平将在整个网络的位置上绘制出来，以便操作员了解网络状况。需要进一步研究最合适的段长度，以在沿轨道的波长分辨率和空间分辨率之间提供有用的折衷。将开发一个网络系统，通过无线通信自动收集车辆的振动数据，并实时更新虚拟状况图。除了轨头粗糙度水平超标之外，还将开发算法来识别振动瞬态（由未对准的道岔、交叉口、不良钢轨接头等引起）。预计将监测振动水平，以便在振动水平超过一定限度之前安排铁路维护。