Lamb Modes Detection Using Cumulative Shannon Entropy with Improved Estimation of Arrival Time

Francisco Sagasta, Kong Fah Tee*, Rosa Piotrkowski

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Non-destructive testing techniques for damage localization constitute a key aspect of structural health monitoring (SHM) systems. The acoustic emission (AE) method can be used for SHM and its location capability is considered as one of the most powerful qualities. This paper presents a novel method for distinguishing between AE transient and noise signals and this proposes a very promising procedure to detect the Lamb modes of AE signals, which provides an improvement in the localization of AE sources. The AE signals were generated on an aluminium flat bar and a plate using the normalised Hsu-Nielsen source. For a successful localisation of the AE sources, both the noise signal discrimination and detection of the beginning of the signal are crucial. The source locations were determined using the conventional Time of Arrival technique and a novel approach based on Shannon entropy of each AE signal. A sharp and substantial change in the cumulative Shannon entropy (CSE) at the instant of arrival of the A0 and S0 Lamb modes was observed. In addition, a comparison of the results using the first Threshold crossing and CSE of the AE signals illustrated that the new proposed method detects more accurately the location of AE sources and reduces the ambiguity introduced by arrival times of noisy signals in both studied specimens.

Original languageEnglish
Article number27
JournalJournal of Nondestructive Evaluation
Volume38
Issue number1
DOIs
StatePublished - 1 Mar 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019, The Author(s).

Keywords

  • Acoustic emission
  • Entropy
  • Lamb waves
  • Noise signals
  • Source location
  • Time of arrival

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering

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