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<article-meta><doi>187</doi>
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<article-title>Structural Damage Detection Using Time Series Models and Cepstral Distances</article-title>
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<author>K. Lakshmi<sup>a</sup>  and A. Rama Mohan Rao<sup>b</sup>  </author>

<aff>Academy of Scientific and Innovative Research, CSIR-SERC, Chennai, TN, India.  </aff>

<email><a href="mailto:lakshmik@serc.res.in"><sup>a</sup>lakshmik@serc.res.in</a></email>

<email><a href="mailto:arm@serc.res.in "><sup>b</sup>arm@serc.res.in </a></email>

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<title>ABSTRACT</title>
<p>A novel damage detection algorithm for structural health monitoring(SHM) using time series model is presented. The proposed algorithm uses output only acceleration time series obtained from sensors on the structure which are fitted using Auto-regressive moving-average with eXogenous inputs (ARMAX) model. The algorithm uses cepstral distances between the ARMAX models of decorrelated data obtained from healthy and current conditions of the structure as the damage indicator. The effectiveness of the proposed method is validated using the benchmark data of 8 DOF system made available to public by Engineering Institute of LANL. The results of the studies indicate that the proposed algorithm is robust in identifying the damage.  </p>
<p><i>Keywords: </i>Structural health monitoring, Damage detection, Time series models, ARMAX, <br /> 8 DOF benchmark validation. </p>
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