In situ health monitoring for bogie systems of CRH380 train on Beijing-Shanghai high-speed railway
In situ health monitoring for bogie systems of CRH380 train on Beijing-Shanghai high-speed railway
复制标题
京沪高铁CRH380动车组转向架系统现场健康监测
DOI：
10.1016/j.ymssp.2013.11.017
复制
发表时间：
2014-04-04
影响因子：
8.4
通讯作者：
Cheng, Li
中科院分区：
文献类型：
--
作者：
Hong, Ming;Wang, Qiang;Cheng, Li
基于作者多年的研究工作，一个原位结构健康监测（SHM）技术，利用弹性导波已开发和部署通过在线诊断系统。该技术和系统最近在京沪高速铁路上运行的中国最新高速列车（CRH 380 CL）上实施。该系统集成了模块化的组件，包括主动传感器网络，主动波发生，多通道数据采集，信号处理，数据融合和结果显示。在CRH 380 CL的总装过程中，将“分散式标准传感”的传感器网络集成到转向架构架中，以产生和采集转向架引导的超声波，并从中提取大量的信号特征。通过诊断成像算法融合信号特征，以实时和直观的方式显示转向架的整体健康状态。现场实验涵盖了各种高速列车运行事件，包括启动，加速/减速，全速运行（300 km/h），紧急制动，轨道变化以及完全停止。贴在转向架上的模型损伤被定量识别并在图像中可视化。这种原位测试已经证明了所开发的SHM技术和系统在实际应用中的可行性、有效性、灵敏度和可靠性。(C)2013爱思唯尔有限公司保留所有权利。
Based on the authors' research efforts over the years, an in situ structural health monitoring (SHM) technique taking advantage of guided elastic waves has been developed and deployed via an online diagnosis system. The technique and the system were recently implemented on China's latest high-speed train (CRH380CL) operated on Beijing-Shanghai High-Speed Railway. The system incorporated modularized components including active sensor network, active wave generation, multi-channel data acquisition, signal processing, data fusion, and results presentation. The sensor network, inspired by a new concept-"decentralized standard sensing", was integrated into the bogie frames during the final assembly of CRH380CL, to generate and acquire bogie-guided ultrasonic waves, from which a wide array of signal features were extracted. Fusion of signal features through a diagnostic imaging algorithm led to a graphic illustration of the overall health state of the bogie in a real-time and intuitive manner. The in situ experimentation covered a variety of high-speed train operation events including startup, acceleration/deceleration, full-speed operation (300 km/h), emergency braking, track change, as well as full stop. Mock-up damage affixed to the bogie was identified quantitatively and visualized in images. This in situ testing has demonstrated the feasibility, effectiveness, sensitivity, and reliability of the developed SHM technique and the system towards real-world applications. (C) 2013 Elsevier Ltd. All rights reserved.