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Early Warning of Abnormal Train-Induced Vibrations for a Steel-Truss Arch Railway Bridge: Case Study

机译:桁架拱形铁路桥梁列车振动异常预警:案例研究

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Considering the new challenges for high-speed railway bridges, the early warning of abnormal train-induced vibrations is necessary for ensuring the operation safety of both the bridge structures and the trains on the bridge. In this study, an online monitoring system for detecting abnormal train-induced vibration responses is developed, and the Dashengguan Yangtze River Bridge is used for illustration. First, to accurately investigate the influence of different train lanes and the number of carriages on train-induced vibrations, the speed-acceleration (train speed-bridge acceleration) correlations under different loading cases are obtained using an online identification method. Then, a twostage method for early warning of abnormal train-induced acceleration responses of the bridges is developed using wavelet packet decomposition and interval estimation theory. Finally, the early warning method for identifying abnormal train-induced transverse vibrations is presented. The results show that (1) the train lane and the number of carriages affect the speed-acceleration correlations, and the identification of loading cases is needed for the accurate monitoring of speed-acceleration correlations; (2) by using wavelet packet decomposition, the median line of speed-acceleration correlations can be optimally extracted, and the early warning thresholds for abnormal train-induced acceleration responses can be properly determined using the interval estimation theory compared with the point estimation theory; and (3) the train running parameters of the Dashengguan Yangtze River Bridge are all within safe limits, but the wheel unloading rate and derailment coefficient have reached 60% of the limits due to the train-induced transverse vibrations. The effects of train-induced transverse vibration on the train running stability is worthy of attention. (C) 2017 American Society of Civil Engineers.
机译:考虑到高速铁路桥梁的新挑战,为确保桥梁结构和桥梁上列车的运行安全,必须对列车异常振动的早期预警。在这项研究中,开发了一种用于检测列车异常振动响应的在线监测系统,并以大胜关长江大桥为例进行了说明。首先,为了准确研究不同车道和车厢数量对列车引起的振动的影响,使用在线识别方法获得了不同载荷情况下的速度-加速度(列车速度-桥梁加速度)相关性。然后,利用小波包分解和区间估计理论,提出了桥梁异常列车加速度响应异常预警的两阶段方法。最后,提出了识别异常列车引起的横向振动的预警方法。结果表明:(1)列车车道和车厢数量影响速度-加速度相关性,准确识别速度-加速度相关性需要识别装货情况; (2)通过小波包分解,可以最优地提取速度加速度相关性的中线,并可以采用区间估计理论与点估计理论相比较的方法,适当地确定列车产生的加速度响应异常的预警阈值; (3)大胜关长江大桥的列车运行参数均在安全范围内,但由于列车产生的横向振动,车轮的卸荷率和脱轨系数已达到限值的60%。列车引起的横向振动对列车运行稳定性的影响值得关注。 (C)2017年美国土木工程师学会。

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