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

11 Scopus citations


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
Number of pages4
StatePublished - 2001
Event2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing - Salt Lake, UT, United States
Duration: May 7 2001May 11 2001


Other2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing
Country/TerritoryUnited States
CitySalt Lake, UT

ASJC Scopus subject areas

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


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