Clough, A. R. and Edwards, R. S. (Rachel S.) (2015) Characterisation of hidden defects using the near-field ultrasonic enhancement of Lamb waves. Ultrasonics, 59 . pp. 64-71. doi:10.1016/j.ultras.2015.01.012

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Abstract

Defects that propagate from the inside of a structure can be difficult to detect by traditional non-destructive inspection methods. A non-contact inspection method is presented here that uses the near-field interactions of ultrasonic Lamb waves to detect defects propagating into a 1.5 mm thick aluminium sheet from the opposite side to that which is inspected. Near-field interactions of the S0 Lamb waves with the defects are shown to give rise to a characteristic increase in the wave magnitude, which is used to position and characterise these hidden defects. It is shown that such defects are difficult to detect from a study of their influence on ultrasonic transmission alone. Single defects of different depths, and systems of multiple defects with varying separations and relative depths, are successfully detected in both experimental trials and FEM simulations. Reliable single defect detection is achieved for defects with a minimum depth of 30% of the plate thickness, and resolution of multiple defects is achieved for defect separations of 5 mm.

Item Type:	Journal Article
Subjects:	Q Science > Q Science (General) Q Science > QC Physics
Divisions:	Faculty of Science, Engineering and Medicine > Engineering > Engineering Faculty of Science, Engineering and Medicine > Science > Physics
Library of Congress Subject Headings (LCSH):	Lamb waves, Stress corrosion
Journal or Publication Title:	Ultrasonics
Publisher:	Elsevier
Official Date:	May 2015
Dates:	Date Event May 2015 Published 2 February 2015 Available 21 January 2015 Accepted 5 August 2014 Submitted
Volume:	59
Number of Pages:	8
Page Range:	pp. 64-71
DOI:	10.1016/j.ultras.2015.01.012
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Date of first compliant deposit:	30 December 2015
Date of first compliant Open Access:	29 February 2016
Funder:	European Research Council (ERC)
Grant number:	202735 (ERC)

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