Share Email Print

Proceedings Paper

Physics based modeling for time-frequency damage classification
Author(s): Debejyo Chakraborty; Sunilkumar Soni; Jun Wei; Narayan Kovvali; Antonia Papandreou-Suppappola; Douglas Cochran; Aditi Chattopadhyay
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We have recently proposed a method for classifying waveforms from healthy and damaged structures in a structural health monitoring framework. This method is based on the use of hidden Markov models with preselected feature vectors obtained from the time-frequency based matching pursuit decomposition. In order to investigate the performance of the classifier for different signal-to-noise ratios (SNR), we simulate the response of a lug joint sample with different crack lengths using finite element modeling (FEM). Unlike experimental noisy data, the modeled data is noise free. As a result, different levels of noise can be added to the modeled data in order to obtain the true performance of the classifier under additive white Gaussian noise. We use the finite element package ABAQUS to simulate a lug joint sample with different crack lengths and piezoelectric sensor signals. A mesoscale internal state variable damage model defines the progressive damage and is incorporated in the macroscale model. We furthermore use a hybrid method (boundary element-finite element method) to model wave reflection as well as mode conversion of the Lamb waves from the free edges and scattering of the waves from the internal defects. The hybrid method simplifies the modeling problem and provides better performance in the analysis of high stress gradient problems.

Paper Details

Date Published: 3 April 2008
PDF: 12 pages
Proc. SPIE 6926, Modeling, Signal Processing, and Control for Smart Structures 2008, 69260M (3 April 2008); doi: 10.1117/12.776628
Show Author Affiliations
Debejyo Chakraborty, Arizona State Univ. (United States)
Sunilkumar Soni, Arizona State Univ. (United States)
Jun Wei, Arizona State Univ. (United States)
Narayan Kovvali, Arizona State Univ. (United States)
Antonia Papandreou-Suppappola, Arizona State Univ. (United States)
Douglas Cochran, Arizona State Univ. (United States)
Aditi Chattopadhyay, Arizona State Univ. (United States)

Published in SPIE Proceedings Vol. 6926:
Modeling, Signal Processing, and Control for Smart Structures 2008
Douglas K. Lindner, Editor(s)

© SPIE. Terms of Use
Back to Top