System identification of a full‐scale five‐story reinforced concrete building tested on the NEES‐UCSD shake table

Summary This paper presents the identification of modal properties of a full-scale five-story reinforced concrete building fully outfitted with nonstructural components and systems (NCSs) tested on the NEES-UCSD shake table. The fixed base building is subjected to a sequence of earthquake motions selected to progressively damage the structure and NCSs. Between seismic tests, ambient vibration response is recorded. Additionally, low-amplitude white noise (WN) base excitation tests are conducted during the test protocol. Using the vibration data recorded, five state-of-the-art system identification (SID) methods are employed, including three output-only and two input-output. These methods are used to estimate the modal properties of an equivalent viscously-damped linear elastic time-invariant model of the building at different levels of damage and their results compared. The results show that modal properties identified from different methods are in good agreement and that the estimated modal parameters are affected by the amplitude of excitation and structural/nonstructural damage. Detailed visual inspections of damage performed between the seismic tests permit correlation of the identified modal parameters with the actual damage. The identified natural frequencies are used to determine the progressive loss of apparent global stiffness of the building, and the state-space models identified using WN test data are employed to investigate the relative modal contributions to the measured building response at different damage states. This research provides a unique opportunity to investigate the performance of different SID methods when applied to vibration data recorded in a real building subjected to progressive damage induced by a realistic source of dynamic excitation. Copyright © 2015 John Wiley & Sons, Ltd.

[1]  Erik A. Johnson,et al.  Phase I IASC-ASCE Structural Health Monitoring Benchmark Problem Using Simulated Data , 2004 .

[2]  Joel P. Conte,et al.  System Identification of Alfred Zampa Memorial Bridge Using Dynamic Field Test Data , 2009 .

[3]  Joel P. Conte,et al.  Landmark Data Set from the Building Nonstructural Components and Systems (BNCS) Project , 2016 .

[4]  Michele Dilena,et al.  Dynamic testing of a damaged bridge , 2011 .

[5]  Andrea Belleri,et al.  Damage assessment through structural identification of a three‐story large‐scale precast concrete structure , 2014 .

[6]  D. Giraldo,et al.  Modal Identification through Ambient Vibration: Comparative Study , 2009 .

[7]  E. Peter Carden,et al.  Vibration Based Condition Monitoring: A Review , 2004 .

[8]  Thomas G. Carne,et al.  The Natural Excitation Technique (NExT) for modal parameter extraction from operating wind turbines , 1993 .

[9]  Charles R. Farrar,et al.  Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review , 1996 .

[10]  Joel P. Conte,et al.  Influence of the construction process and nonstructural components on the modal properties of a five‐story building , 2016 .

[11]  Masayoshi Nakashima,et al.  Seismic Damage Detection of a Full-Scale Shaking Table Test Structure , 2011 .

[12]  Jer-Nan Juang,et al.  An eigensystem realization algorithm for modal parameter identification and model reduction. [control systems design for large space structures] , 1985 .

[13]  Glauco Feltrin,et al.  Damage Identification Using Modal Data: Experiences on a Prestressed Concrete Bridge , 2005 .

[14]  Charles R. Farrar,et al.  Structural Health Monitoring Studies of the Alamosa Canyon and I-40 Bridges , 2000 .

[15]  Richard W. Longman,et al.  Identification of observer/Kalman filter Markov parameters - Theory and experiments , 1991 .

[16]  Alessandro De Stefano,et al.  Comparative study of vibration‐based parametric identification techniques for a three‐dimensional frame structure , 2012 .

[17]  François M. Hemez,et al.  Uncertainty analysis of system identification results obtained for a seven‐story building slice tested on the UCSD‐NEES shake table , 2014 .

[18]  Akira Mita,et al.  Damage identification of full scale four-story steel building using multi-input multi-output models , 2011, Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[19]  John T. DeWolf,et al.  Ambient Vibration Monitoring of a Highway Bridge Undergoing a Destructive Test , 2006 .

[20]  Rune Brincker,et al.  Modal identification of output-only systems using frequency domain decomposition , 2001 .

[21]  Mohammad Noori,et al.  System Identification of Base-Isolated Building using Seismic Response Data , 2005 .

[22]  Jonathan P. Stewart,et al.  Observed Behavior of Seismically Isolated Buildings , 1999 .

[23]  Carlos E. Ventura,et al.  Damping estimation by frequency domain decomposition , 2001 .

[24]  Pizhong Qiao,et al.  Vibration-based Damage Identification Methods: A Review and Comparative Study , 2011 .

[25]  Yozo Fujino,et al.  Dynamic Characteristics of an Overpass Bridge in a Full-Scale Destructive Test , 2013 .

[26]  Filipe Magalhães,et al.  Continuous dynamic monitoring of a lively footbridge for serviceability assessment and damage detection , 2012 .

[27]  Satish Nagarajaiah,et al.  Response of Base-Isolated USC Hospital Building in Northridge Earthquake , 2000 .

[28]  Tomohiro SASAKI,et al.  NEES / E-Defense Base-Isolation Tests : Effectiveness of Friction Pendulum and Lead-Rubber Bearings Systems , 2012 .

[29]  B. Peeters,et al.  Stochastic System Identification for Operational Modal Analysis: A Review , 2001 .

[30]  Joel P. Conte,et al.  Finite-Element Model Updating for Assessment of Progressive Damage in a 3-Story Infilled RC Frame , 2013 .

[31]  Guido De Roeck,et al.  One-year monitoring of the Z24-Bridge : environmental effects versus damage events , 2001 .

[32]  Joel P. Conte,et al.  System Identification Study of a 7-Story Full-Scale Building Slice Tested on the UCSD-NEES Shake Table , 2011 .