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Identification and Damage Detection of a Shear Frame Model Based on a Blind Source Separation Method

Abstract : Blind source separation methods have recently emerged as a competitive alternate structural identification method offering a number of advantages when compared to traditional methods. These include the plain underlying model, its computational ease, and its robustness to various types of excitations. The aim of this study, is to experimentally assess the effectiveness of a second order BSS method for the problems of output-only structural identification and damage detection, by its application on the vibration response data of a four-storey shear frame. The structure under study is subjected to various types of input excitation and is tested under its ''healthy'' and a number of simulated ''damaged'' states. The results of the study show great potential of the BSS method for the efficient treatment of both problems.
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https://hal.inria.fr/hal-01022976
Contributor : Anne Jaigu <>
Submitted on : Friday, July 11, 2014 - 12:40:14 PM
Last modification on : Thursday, May 27, 2021 - 1:54:05 PM
Long-term archiving on: : Saturday, October 11, 2014 - 12:06:56 PM

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Minas Spiridonakos, Nishant Yadav, Eleni Chatzi. Identification and Damage Detection of a Shear Frame Model Based on a Blind Source Separation Method. EWSHM - 7th European Workshop on Structural Health Monitoring, IFFSTTAR, Inria, Université de Nantes, Jul 2014, Nantes, France. ⟨hal-01022976⟩

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