Strategies for guided-wave structural health monitoring

AJ Croxford*, PD Wilcox, BW Drinkwater, G Konstantinidis

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

348 Citations (Scopus)

Abstract

Structural health monitoring (SHM) using guided waves is one of the only ways in which damage anywhere in a structure can be detected using a sparse array of permanently attached sensors. To distinguish damage from structural features, some form of comparison with damage-free reference data is essential, and here subtraction is considered. The detectability of damage is determined by the amplitude of residual signals from structural features remaining after the subtraction of reference data. These are non-zero due to changing environmental conditions such as temperature. In this paper, the amplitude of the residual signals is quantified for different guided-wave SHM strategies. Comparisons are made between two methods of reference signal subtraction and between two candidate sensor configurations. These studies allow estimates to be made of the number of sensors required per unit area to reliably detect a prescribed type of damage. It is shown that the number required is prohibitively high, even in the presence of modest temperature fluctuations, hence some form of temperature compensation is absolutely essential for guided-wave SHM systems to be viable. A potential solution is examined and shown to provide an improvement in signal suppression of approximately 30dB, which corresponds to two orders of magnitude reduction in the number of sensors required.
Translated title of the contributionStrategies for guided-wave structural health monitoring
Original languageEnglish
Pages (from-to)2961-2981
Number of pages21
JournalProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
Volume463
Issue number2087
DOIs
Publication statusPublished - 8 Nov 2007

Bibliographical note

Publisher: Royal Society

Keywords

  • Damage detection
  • Lamb waves
  • Signal-to-noise ratio
  • Structural health monitoring
  • Temperature effects

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