Adaptive extended Kalman filter for parameter tracking of base-isolated structure under unknown seismic input

T. Mu, L. Zhou, J. N. Yang
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引用次数: 3

Abstract

Base isolation systems have been widely used in civil structures as protective devices against earthquakes, hurricanes, etc., and the state assessment using vibration data for the safety, reliability and integrity of base-isolated structures is very important in structural health monitoring. In the case of field engineering applications, external excitations, such as seismic inputs, wind inputs, etc., usually could not be measured, or even could not be measurable. Herein, an adaptive extended Kalman filter approach for structural parameter tracking under unknown seismic input, which is referred to as AEKF-UI approach, is developed to on-line track the base-isolated structural time-varying parameters, including the damping, stiffness, nonlinear hysteretic parameters, etc., and identify the unmeasured seismic input. The experimental results of vibration tests demonstrate the fact that the AEKF-UI method developed is able to achieve real-time parameter tracking of base-isolated structure under unknown seismic input, leading to the on-line identification of structural damages.
未知地震输入下基础隔震结构参数跟踪的自适应扩展卡尔曼滤波
基础隔震系统作为地震、飓风等的防护装置广泛应用于民用结构中,利用振动数据对基础隔震结构的安全性、可靠性和完整性进行状态评估是结构健康监测的重要内容。在现场工程应用中,外界激励,如地震输入、风输入等,通常是无法测量的,甚至是无法测量的。本文提出了一种用于未知地震输入下结构参数跟踪的自适应扩展卡尔曼滤波方法,即AEKF-UI方法,用于在线跟踪基础隔震结构的时变参数,包括阻尼、刚度、非线性滞回参数等,并识别未测地震输入。振动试验结果表明,所开发的AEKF-UI方法能够实现未知地震输入下基础隔震结构的实时参数跟踪,从而实现结构损伤的在线识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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