Title: Application of vibration-based damage detection algorithms to experimental data from multi-storey steel structures

Authors: Yizheng Liao; Konstantinos Balafas; Anne S. Kiremidjian; Ram Rajagopal; Chin-Hsiung Loh

Addresses: Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA ' Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA ' Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA ' Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA ' Department of Civil Engineering, National Taiwan University, Taiwan

Abstract: Recently, there has been remarkable progress in the development of data acquisition systems and statistical damage detection algorithms in the field of vibration-based structural health monitoring (SHM). However, many of them have not been validated by experimental data. This paper presents and analyzes a shake table experiment of two three-story steel structures. The structural damage was introduced in a systematic and controlled way and the structures were tested with different levels of earthquakes. Three types of analyses were conducted. First, a wireless sensor system designed for SHM, SnowFort, was demonstrated to have the same accuracy as the conventional wired sensors. Second, the rotation algorithm is applied to estimate residual displacements in the structures and achieves excellent agreements with the displacement sensor measurements. At last, a continuous wavelet transform-based damage detector is applied to the experimental data. The results highlight that the wavelet model parameters are sensitive to the damage state.

Keywords: structural health monitoring; SHM; wireless sensor network; damage detection; experimental study; statistical pattern recognition; SPR.

DOI: 10.1504/IJSMSS.2020.109084

International Journal of Sustainable Materials and Structural Systems, 2020 Vol.4 No.2/3/4, pp.199 - 226

Received: 25 Mar 2019
Accepted: 10 Oct 2019
Published online: 19 Aug 2020 *

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