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Damage detection of moment frames using ensemble Empirical Mode Decomposition and clustering techniques

  • Structural Engineering
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Abstract

Most of the damage detection methods implement dynamic response of linear structures for indication of damage. Time-frequency methods employ signal processing techniques to detect temporal changes in frequency characteristics of vibration response of the system. However, most of these techniques fail facing with nonlinear systems due to consecutive changes in stiffness that lead to fake damage indications. This study is divided into two parts. First, the Empirical Mode Decomposition method (EMD) is compared to Ensemble EMD (EEMD) to clarify the capability of these methods as signal processing tools. For this reason, the acceleration responses of a nonlinear steel moment frame are extracted by EMD and EEMD. Second, Hilbert transform based on EEMD is employed in conjunction with a density-based clustering technique to classify the changes in frequency and amplitude patterns to identify and estimate the extent of damage. Simulation results demonstrate that frequency is not an appropriate parameter to determine the extent of damage for nonlinear systems.

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Authors and Affiliations

  1. Center of Excellence for Fundamental Studies in Structural Engineering, School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran, 16846, Iran

    Gholamreza Ghodrati Amiri

  2. Civil Engineering Dept., Iran University of Science and Technology, Tehran, 16846, Iran

    Ehsan Darvishan

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  1. Gholamreza Ghodrati Amiri
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  2. Ehsan Darvishan
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Correspondence to Gholamreza Ghodrati Amiri.

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Amiri, G.G., Darvishan, E. Damage detection of moment frames using ensemble Empirical Mode Decomposition and clustering techniques. KSCE J Civ Eng 19, 1302–1311 (2015). https://doi.org/10.1007/s12205-015-0415-z

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  • DOI: https://doi.org/10.1007/s12205-015-0415-z

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