Abstract

Mode shapes are sensitive to the structural condition of bridges but a reasonable estimate of such changes require several accelerometers, which can be resource intensive. This paper obviates this problem through a novel structure health monitoring (SHM) approach for estimating modal parameters of bridges, including damage-induced changes of boundary conditions by using progressively re-deploying sensors along a monitored bridge. This concept of re-deployable sensors and subsequent use of a series of measurements allow extracting data from different bridge segments and also to get an indication of the condition of the bridge through frequency domain decomposition. Data from different segments are combined to estimate the global mode shape of the bridge and its gradient is observed to be indicative of support stiffness change. The concept is successfully tested through a full-scale field trial on a railway bridge in the Republic of Ireland, before and after the rehabilitation of its supports. The results are expected to guide future on-site measurement of damages due to flooding, scour, and other natural hazards, along with the effectiveness of intervention actions like repair and rehabilitation, providing a clear evidence base for practical value of SHM.

摘要

振型对桥梁的结构状况很敏感，但对这种变化的合理估计需要几个加速度计，这可能是资源密集型的。本文通过一种新的结构健康监测 (SHM) 方法解决了这个问题，该方法用于估计桥梁的模态参数，包括通过使用沿监测桥梁逐步重新部署的传感器导致的边界条件的损伤引起的变化。这种可重新部署的传感器的概念和随后使用一系列测量允许从不同的桥段中提取数据，并通过频域分解获得桥梁状况的指示。来自不同部分的数据被组合以估计桥梁的整体模式形状，并观察到其梯度以指示支撑刚度的变化。该概念通过在爱尔兰共和国的一座铁路桥上进行全面的现场试验，在其支撑修复前后进行了成功的测试。该结果有望指导未来对洪水、冲刷和其他自然灾害造成的损害进行现场测量，以及修复和恢复等干预行动的有效性，为 SHM 的实用价值提供明确的证据基础。