Development of fragility functions as a damage classification/prediction method for steel moment‐resisting frames using a wavelet‐based damage sensitive feature

SUMMARY Fragility functions are commonly used in performance-based earthquake engineering for predicting the damage state of a structure subjected to an earthquake. This process often involves estimating the structural damage as a function of structural response, such as the story drift ratio and the peak floor absolute acceleration. In this paper, a new framework is proposed to develop fragility functions to be used as a damage classification/prediction method for steel structures based on a wavelet-based damage sensitive feature (DSF). DSFs are often used in structural health monitoring as an indicator of the damage state of the structure, and they are easily estimated from recorded structural responses. The proposed framework for damage classification of steel structures subjected to earthquakes is demonstrated and validated with a set of numerically simulated data for a four-story steel moment-resisting frame designed based on current seismic provisions. It is shown that the damage state of the frame is predicted with less variance using the fragility functions derived from the wavelet-based DSF than it is with fragility functions derived from an alternate acceleration-based measure, the spectral acceleration at the first mode period of the structure. Therefore, the fragility functions derived from the wavelet-based DSF can be used as a probabilistic damage classification model in the field of structural health monitoring and an alternative damage prediction model in the field of performance-based earthquake engineering. Copyright © 2011 John Wiley & Sons, Ltd.

[1]  Vitelmo V. Bertero,et al.  Earthquake Engineering: From Engineering Seismology To Performance-Based Engineering , 2020 .

[2]  Andrew S. Whittaker,et al.  Prediction and validation of sidesway collapse of two scale models of a 4‐story steel moment frame , 2011 .

[3]  R. Y. Chiang,et al.  Structural modeling and identification using neural networks , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[4]  Hoon Sohn,et al.  A review of structural health monitoring literature 1996-2001 , 2002 .

[5]  Ahsan Kareem,et al.  Wavelet Transforms for System Identification in Civil Engineering , 2003 .

[6]  Calyampudi Radhakrishna Rao,et al.  Linear Statistical Inference and its Applications , 1967 .

[7]  E. Miranda,et al.  Performance-Based Earthquake Engineering , 2004 .

[8]  Satoshi Yamada,et al.  EXPERIMENTAL PROCEDURE AND ELASTIC RESPONSE CHARACTERISTICS OF SHAKING TABLE TEST , 2009 .

[9]  Curt B. Haselton,et al.  Assessing seismic collapse safety of modern reinforced concrete moment frame buildings , 2006 .

[10]  Zhikun Hou,et al.  Application of Wavelet Approach for ASCE Structural Health Monitoring Benchmark Studies , 2004 .

[11]  Jerome P. Lynch,et al.  A summary review of wireless sensors and sensor networks for structural health monitoring , 2006 .

[12]  Farzad Naeim,et al.  AUTOMATED POST-EARTHQUAKE DAMAGE ASSESSMENT OF INSTRUMENTED BUILDINGS , 2006 .

[13]  Min Liu,et al.  Life cycle cost oriented seismic design optimization of steel moment frame structures with risk-taking preference , 2004 .

[14]  Farzad Naeim,et al.  AUTOMATED POST-EARTHQUAKE DAMAGE ASSESSMENT AND SAFETY EVALUATION OF INSTRUMENTED BUILDINGS , 2005 .

[15]  R. Ghanem,et al.  Structural-System Identification. I: Theory , 1995 .

[16]  Chung Bang Yun,et al.  Substructural identification using neural networks , 2000 .

[17]  Dimitrios Vamvatsikos,et al.  Incremental dynamic analysis , 2002 .

[18]  W. J. Hall,et al.  Recommended Seismic Design Criteria for New Steel Moment-Frame Buildings , 2001 .

[19]  Matthew P. Wand,et al.  Kernel Smoothing , 1995 .

[20]  James L. Beck,et al.  Structural identification using linear models and earthquake records , 1980 .

[21]  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 .

[22]  Chan Ghee Koh,et al.  Substructural and progressive structural identification methods , 2003 .

[23]  H. Hartley.  The Modified Gauss-Newton Method for the Fitting of Non-Linear Regression Functions by Least Squares , 1961 .

[24]  Helmut Krawinkler,et al.  Deterioration Modeling of Steel Components in Support of Collapse Prediction of Steel Moment Frames under Earthquake Loading , 2011 .

[25]  Rune Brincker,et al.  Vibration Based Inspection of Civil Engineering Structures , 1993 .

[26]  Ahmed Ghobarah,et al.  Performance-based design in earthquake engineering: state of development , 2001 .

[27]  Sukun Kim,et al.  Health Monitoring of Civil Infrastructures Using Wireless Sensor Networks , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[28]  Farzin Zareian,et al.  A Simplified Procedure for Performance-Based Design , 2007 .

[29]  Boleslaw K. Szymanski,et al.  Some Properties of the Gaussian Kernel for One Class Learning , 2007, ICANN.

[30]  H. Noh,et al.  On the use of wavelet coefficient energy for structural damage diagnosis , 2002 .

[31]  Mohammad Noori,et al.  Wavelet-Based Approach for Structural Damage Detection , 2000 .

[32]  Dimitrios G. Lignos,et al.  Sidesway collapse of deteriorating structural systems under seismic excitations , 2008 .

[33]  Curt B. Haselton,et al.  Seismic Collapse Safety and Behavior of Modern Reinforced Concrete Moment Frame Buildings , 2007 .

[34]  Hoon Sohn,et al.  Damage diagnosis using time series analysis of vibration signals , 2001 .

[35]  R. Ghanem,et al.  A WAVELET-BASED APPROACH FOR THE IDENTIFICATION OF LINEAR TIME-VARYING DYNAMICAL SYSTEMS , 2000 .

[36]  Chen Qiao-sheng,et al.  A Brief Introduction of FEMA P695—Quantification of Building Seismic Performance Factors , 2013 .

[37]  Anne S. Kiremidjian,et al.  A modular, wireless damage monitoring system for structures , 1998 .

[38]  Robert E. Bachman,et al.  Creating Fragility Functions for Performance-Based Earthquake Engineering , 2007 .

[39]  K. Park,et al.  Second-order structural identification procedure via state-space-based system identification , 1994 .

[40]  Farzin Zareian,et al.  Assessment of probability of collapse and design for collapse safety , 2007 .

[41]  M. Kupperman.  Linear Statistical Inference and Its Applications 2nd Edition (C. Radhakrishna Rao) , 1975 .

[42]  Charles R. Farrar,et al.  Applying the LANL Statistical Pattern Recognition Paradigm for Structural Health Monitoring to Data from a Surface-Effect Fast Patrol Boat , 2001 .

[43]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[44]  Carlos Marcelo Ramirez.  Building-specific loss estimation methods & tools for simplified performance-based earthquake engineering , 2009 .

[45]  A. K. Pandey,et al.  Damage Detection in Structures Using Changes in Flexibility , 1994 .

[46]  Anne S. Kiremidjian,et al.  A wavelet‐based damage diagnosis algorithm using principal component analysis , 2012 .

[47]  Dimitrios G. Lignos,et al.  Use of Wavelet-Based Damage-Sensitive Features for Structural Damage Diagnosis Using Strong Motion Data , 2011 .

[48]  Jerome P. Lynch,et al.  Embedding damage detection algorithms in a wireless sensing unit for operational power efficiency , 2004 .

[49]  L. Ibarra.  Global collapse of frame structures under seismic excitations , 2003 .

[50]  Deborah Estrin,et al.  A wireless sensor network For structural monitoring , 2004, SenSys '04.

[51]  David Polidori,et al.  Determination of Modal Parameters from Ambient Vibration Data for Structural Health Monitoring , 1994 .

[52]  W. Iwan,et al.  Improvement of Nonlinear Static Seismic Analysis Procedures , 2005 .

[53]  J. Hong,et al.  Determination of the optimal Gabor wavelet shape for the best time-frequency localization using the entropy concept , 2004 .

[54]  K. Law,et al.  Time series-based damage detection and localization algorithm with application to the ASCE benchmark structure , 2006 .

[55]  R. Medina,et al.  Seismic Demands for Nondeteriorating Frame Structures and Their Dependence on Ground Motions , 2003 .