Abstract

The ability to detect and classify damages in complex materials and structures is an important problem from both safety and economical perspectives. This paper develops a novel approach based on Hidden Markov Models (HMMs) for the classification of structural damage. Our approach here is based on using HMMs for modeling the time-frequency features extracted from time-varying structural data. Unlike conventional deterministic methods, the HMM is a stochastic approach which better accounts for the uncertainties encountered in the structural problem and leads to a more robust health monitoring system. The utility of the proposed approach is demonstrated via example results for the classification of fastener damage in an aluminum plate.

Original languageEnglish (US)
Title of host publicationModeling, Signal Processing, and Control for Smart Structures 2007
DOIs
StatePublished - Oct 15 2007
EventModeling, Signal Processing, and Control for Smart Structures 2007 - San Diego, CA, United States
Duration: Mar 19 2007Mar 21 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6523
ISSN (Print)0277-786X

Other

OtherModeling, Signal Processing, and Control for Smart Structures 2007
CountryUnited States
CitySan Diego, CA
Period3/19/073/21/07

Keywords

  • Damage classification
  • Damage detection
  • Hidden Markov model
  • Matching pursuit decomposition
  • Structural health monitoring

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Wenfan, Z., Kovvali, N., Papandreou-Suppappola, A., Cochran, D., & Chattopadhyay, A. (2007). Hidden Markov model based classification of structural damage. In Modeling, Signal Processing, and Control for Smart Structures 2007 [652311] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 6523). https://doi.org/10.1117/12.716132