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原文传递 Near-Real-Time Hybrid System Identification Framework for Civil Structures with Application to Burj Khalifa

题名：	Near-Real-Time Hybrid System Identification Framework for Civil Structures with Application to Burj Khalifa
正文语种：	英文
作者：	Yanlin Guo, M.ASCE; Dae Kun Kwon, M.ASCE;Ahsan Kareem, Dist.M.ASCE
作者单位：	Univ, of Notre Dame
关键词：	System identification; Real time; Transient/nonstationary; Web-enabled; Structural health monitoring; Structural identification.
摘要：	This study proposes a near-real-time hybrid framework for system identification (SI) of structures using data from structural health monitoring systems. To account for both stationary/weakly nonstationary response under normal conditions (e.g., extratropical winds and/or ambient excitations) and transient/highly nonstationary response under transient events (e.g., earthquakes, windstorms, or time-varying traffic loadings), a hybrid framework is introduced by integrating a new nonstationary SI scheme based on wavelets in tandem with transformed singular value decomposition, and a robust stationary SI scheme called covariance-driven stochastic subspace identification. Extensive numerical simulations as well as analysis of full-scale data are conducted to evaluate the efficacy of the scheme. To facilitate expeditious and convenient utilization of this framework in a practical application, a web-enabled approach and its workflow concerning measurements of the world's tallest building, Buij Khalifa, are presented. This web approach facilitates automated hybrid SI in near real time as an Intemet of Things service, which remotely provides end users (e.g., building owners, managers, engineers, and other stakeholders) with timely information on structural performance and ultimately supports the user's need in decision maki ng regarding structural operation. It is dem on strated that natural frequencies and damping ratios are successfully identified from the streaming data in near real time under both winds and earthquakes. The identified system properties are very useful for tracking the structure's health condition in its lifecycle. The resulting probabilistic characterization of the system properties can be used to enhance performance-based structural design and retrofitting. DOI: 10.1061/(ASCE) ST.1943-541X.0001402. © 2015 American Society of Civil Engineers.
出版日期：	2016.02
出版年：	2016
期刊名称：	Journal of Structural Engineering
卷：	Vol.142
期：	NO.02
页码：	04015132