Damage identification of a large cable-stayed bridge with novel cointegrated Kalman filter method under changing environments
Damage identification of a large cable-stayed bridge with novel cointegrated Kalman filter method under changing environments
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变化环境下大型斜拉桥损伤识别新型协整卡尔曼滤波方法
DOI：
10.1002/stc.2152
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发表时间：
2018-05-01
影响因子：
5.4
通讯作者：
Liang, Yabin
中科院分区：
文献类型：
--
作者：
Huang, Jie-zhong;Li, Dong-sheng;Liang, Yabin
损伤识别是结构健康监测后续应用中不可缺少的一部分。然而，在实际应用中，随时间变化的环境和操作条件，如温度和外部载荷，往往压倒了微妙的结构变化所造成的损害。因此，从实际的结构损伤中去除那些由外界影响引起的结构变化（损伤特征）具有重要意义。本文提出了一种基于卡尔曼滤波和协整（KFC）的损伤识别方法，通过卡尔曼滤波系数的协整过程消除环境因素对损伤指标的影响。首先利用增广的Dickey-Fuller检验和Johansen方法建立了结构频率之间的协整关系。然后利用协整系数构造卡尔曼滤波（KF）状态向量，并利用递推KF过程在线估计结构状态的变化。为了提高新观测值在KF中的重要性，我们在传统KF中引入了自适应衰落因子。通过对一桁架桥的数值模拟，验证了所提出的KFC方法在温度变化条件下，即使在10%噪声条件下，对结构损伤识别的有效性。最后，将KFC方法应用于国内某斜拉桥（天津永和大桥），成功识别出了两种结构损伤场景。KFC方法的优点是能够消除环境温度的影响和在线识别结构损伤。
Damage identification is an indispensable part for successive applications of structural health monitoring. In practical applications, however, time-varying environmental and operational conditions, such as temperature and external loadings, often overwhelm the subtle structural changes caused by damage. It is therefore of great significance to remove those structural changes (damage features) caused by external influences from actual structural damage. In this paper, a new damage identification method based on Kalman filter and cointegration (KFC) is developed, and the environmental effects on damage indicator are removed by the cointegration process of the Kalman filtered coefficients. The cointegration relationship between structural frequencies is first established with augmented Dickey-Fuller test and Johansen procedure. The cointegration coefficients are then used to constitute the Kalman filter (KF) state vector, and the recursive KF process is intrigued to on-line estimate the change of structure states. To enhance the importance of incoming new observations in the KF, we introduce an adaptive fading factor into the conventional KF. Numerical simulation of a truss bridge is used to validate the effectiveness of the proposed KFC method for damage identification under varying temperature, even with 10% noise. Finally, the KFC method is applied to a cable-stayed bridge built in China (Tianjin Yonghe Bridge), and two structural damage scenarios are successfully identified. The advantages of the proposed KFC method are its ability to eliminate ambient temperature influences and identify structural damage on-line.