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Health monitoring of time-varying stochastic structures
by latent components and fuzzy expert system

M. M. Ettefagh and M. H. Sadeghi

Vibration and Modal Analysis Laboratory, Department of Mechanical Engineering, University of Tabriz, Tabriz 51666, Iran

Abstract: In this paper, a novel parametric model-based decomposition method is proposed for structural health monitoring of time-varying structures. For this purpose, the advanced Functional-Series Time-dependent Auto Regressive Moving Average (FS-TARMA) technique is used to estimate the parameters and innovation variance used in the parametric signal decomposition scheme. Additionally, a unique feature extraction and reduction method based on the decomposed signals, known as Latent Components (LCs), is proposed. To evaluate the efficiency of the proposed method, numerical simulation and an experimental study in the laboratory were conducted on a time-varying structure, where various types of damage were introduced. The Fuzzy Expert System (FES) was used as a classification tool to demonstrate that the proposed method successfully identifies different structural conditions when compared with other methods based on non-reduced and ordinary feature extraction.

Keywords: parametric modeling; signal decomposition; feature extraction/reduction; fuzzy classification


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Copyright© 2009 IEM. Journal of Earthquake Engineering and Engineering Vibration. All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except as described below, without written permission from the Publisher. Copying of articles is not permitted except for personal and internal use, to the extent permitted by national copyright law, or under the terms of a license issued by the National Reproduction Rights Organization of China.