Detecting faults in structures using time-frequency techniques

S. Pon Varma, Antonia Papandreou-Suppappola, S. B. Suppappola

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

In this paper, we investigate various methods of classifying time-varying signals. In particular, we are interested in detecting acoustic emissions that may occur in concrete structures during imminent failure. This important classification problem will result in detecting and separating the distress signal from other natural or man made acoustic signals. Due to the time-varying nature of the signals, we employ several time-frequency based classification methods proposed in the literature. We also propose a new automatic classification method that is based on the matching pursuit algorithm, and we demonstrate its superior performance using real data.

Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Pages3593-3596
Number of pages4
Volume6
StatePublished - 2001
Event2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing - Salt Lake, UT, United States
Duration: May 7 2001May 11 2001

Other

Other2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing
CountryUnited States
CitySalt Lake, UT
Period5/7/015/11/01

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Acoustics and Ultrasonics

Cite this

Pon Varma, S., Papandreou-Suppappola, A., & Suppappola, S. B. (2001). Detecting faults in structures using time-frequency techniques. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (Vol. 6, pp. 3593-3596)