Classification of Acoustic Emissions Using Modified Matching Pursuit

Samuel P. Ebenezer, Antonia Papandreou-Suppappola, Seth B. Suppappola

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


We propose methodologies to automatically classify time-varying warning signals from an acoustic monitoring system that indicate the potential catastrophic structural failures of reinforced concrete structures. Since missing even a single warning signal may prove costly, it is imperative to develop a classifier with high probability of correctly classifying the warning signals. Due to the time-varying nature of these signals, various time-frequency classifiers are considered. We propose a new time-frequency decomposition-based classifier using the modified matching pursuit algorithm for an actual acoustic monitoring system. We investigate the superior performance of the classifier and compare it with existing classifiers for various sets of acoustic emissions, including warning signals from real-world faulty structures. Furthermore, we study the performance of the new classifier under different test conditions.

Original languageEnglish (US)
Pages (from-to)347-357
Number of pages11
JournalEurasip Journal on Applied Signal Processing
Issue number3
StatePublished - Mar 1 2004


  • Acoustic emissions
  • Classification
  • Detection
  • Matching pursuit decomposition
  • Time-frequency representations

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Electrical and Electronic Engineering


Dive into the research topics of 'Classification of Acoustic Emissions Using Modified Matching Pursuit'. Together they form a unique fingerprint.

Cite this