A new power-based method to determine the first arrival information of an acoustic emission wave

Avik Kumar Das*, Christopher K.Y. Leung

*Corresponding author for this work

Research output: Contribution to journalJournal Articlepeer-review

Abstract

Acoustic emission is a powerful experimental structural health monitoring technique for determining the location of cracks formed in a member. Pinpointing wave arrival time is essential for accurate source location. Conventional arrival detection technique’s accuracy deteriorates rapidly in low signal to noise ratio (5–40 dB) region, thus unsuitable for source location due to this inaccuracy. A new technique to pinpoint the arrival time based on the power of the wave is proposed. We have designed an adaptive filter based on the power characteristics of acoustic emission wave. After filtration of the acoustic emission wave, sliding window is employed to accurately identify the region of wave arrival based on the change in transmitted power. The results from various experimental and numerical arrival time detection experiments consistently show that the proposed methodology is stable and accurate for a wide range of signal to noise ratio values (5–100 dB). Particularly, in signal to noise ratio region (5–40 dB), the method is significantly more accurate as compared to the other methods described in the literature. The method was then employed to study the localized damage progression in a steel fiber–reinforced beam under four-point bending. The results suggest that calculated source location using the new method is consistent with that from visual inspection of the member at failure and more accurate than the localization results from existing method.

Original languageEnglish
Pages (from-to)1620-1632
Number of pages13
JournalStructural Health Monitoring
Volume18
Issue number5-6
DOIs
Publication statusPublished - 1 Nov 2019

Bibliographical note

Publisher Copyright:
© The Author(s) 2018.

Keywords

  • Time of arrival
  • acoustic emission
  • power method
  • structural health monitoring

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