Smart Structures and Systems

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A case study of damage detection in four-bays steel structures using the HHT approach

  • Hsu, Wen-Ko (Research Center for Hazard Mitigation and Prevention, National Central University) ;
  • Chiou, Dung-Jiang (Research Center for Hazard Mitigation and Prevention, National Central University) ;
  • Chen, Cheng-Wu (Department of Maritime Information and Technology, National Kaohsiung Marine University) ;
  • Liu, Ming-Yi (Department of Civii Engineering, Chung Yuan University) ;
  • Chiang, Wei-Ling (Department of Civil Engineering, National Central University) ;
  • Huang, Pei-Chiung (Department of Civil Engineering, National Central University)
  • Received : 2013.04.14
  • Accepted : 2013.10.20
  • Published : 2014.10.25
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Abstract

This study aims to investigate the relationship between structural damage and sensitivity indices using the Hilbert-Huang transform (HHT) method. Two damage detection indices are proposed: the ratio of bandwidth (RB), and the ratio of effective stiffness (RES). The nonlinear four bays multiple degree of freedom models with various predominant frequencies are constructed using the SAP2000 program. Adjusted PGA earthquake data (Japan 311, Chi-Chi 921) are used as the excitations. Next the damage detection indices obtained using the HHT and the fast Fourier transform (FFT) methods are evaluated based on the acceleration responses of the structures to earthquakes. Simulation results indicate that, the column of the 1 st floor is the first yielding position and the RB value is changed when the RES<90% in all cases. Moreover, the RB value of the 1 st floor changes more sensitive than those from the top floor. In addition, when the structural response is nonlinear (i.e., RES<100%), the RB and the RES curves indicate the incremental change in the HHT spectra. However, the same phenomenon can be found from FFT spectra only when the stiffness reduction is large enough. Therefore, the RB estimated from the smoothed HHT spectra is an effective and sensitive index for detecting structural damage.

Keywords

Acknowledgement

Supported by : National Science Council

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