Structural Engineering and Mechanics

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Structural health monitoring for pinching structures via hysteretic mechanics models

  • Rabiepour, Mohammad (Department of Mechanical Engineering, University of Canterbury) ;
  • Zhou, Cong (Department of Civil Aviation, Northwestern Polytechnical University) ;
  • Chase, James G. (Department of Mechanical Engineering, University of Canterbury) ;
  • Rodgers, Geoffrey W. (Department of Mechanical Engineering, University of Canterbury) ;
  • Xu, Chao (School of Astronautics, Northwestern Polytechnical University)
  • Received : 2021.04.30
  • Accepted : 2022.01.23
  • Published : 2022.04.25
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Abstract

Many Structural Health Monitoring (SHM) methods have been proposed for structural damage diagnosis and prognosis. However, SHM for pinched hysteretic structures can be problematic due to the high level of nonlinearity. The model-free hysteresis loop analysis (HLA) has displayed notable robustness and accuracy in identifying damage for full-scaled and scaled test buildings. In this paper, the performance of HLA is compared with seven other SHM methods in identifying lateral elastic stiffness for a six-story numerical building with highly nonlinear pinching behavior. Two successive earthquakes are employed to compare the accuracy and consistency of methods within and between events. Robustness is assessed across sampling rates 50-1000 Hz in noise-free condition and then assessed with 10% root mean square (RMS) noise added to responses at 250 Hz sampling rate. Results confirm HLA is the most robust method to sampling rate and noise. HLA preserves high accuracy even when the sampling rate drops to 50 Hz, where the performance of other methods deteriorates considerably. In noisy conditions, the maximum absolute estimation error is less than 4% for HLA. The overall results show HLA has high robustness and accuracy for an extremely nonlinear, but realistic case compared to a range of leading and recent model-based and model-free methods.

Keywords

Acknowledgement

This research did not receive any specific grant from funding agencies in the commercial, public, or not-for-profit sectors.

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