Improved thickness measurement on rough surfaces by using guided wave cut-off frequency
File(s)
Published version
Author(s)
Cawley, Peter
Heinlein, Sebastian
Mariani, Stefano
Vogt, Thomas
Milewczyk, Josh
Type
Journal Article
Abstract
Substantial variability is seen when thickness measurements using conventional ultrasonic time of flight measurements are carried out on rough surfaces; this makes it difficult to estimate corrosion rates when the corrosion mechanism leads to surface roughness. It has been shown that thickness measurements using guided wave cut-off frequencies (through thickness resonance frequencies) can be done at much lower frequencies than conventional time of flight thickness gauging for the same minimum thickness resolution. The lower frequency measurements are less susceptible to variations caused by surface roughness and so will give more consistent and reliable results in cases where corrosion leads to increased surface roughness. Measurements were carried out using guided wave cut-off frequencies on four plates with different surface roughness. On a plate with root mean square (rms) surface roughness of 0.3 mm, the thickness estimates followed the trend predicted from the plate geometry and probe footprint, whereas higher frequency measurements reported in the literature deviated from this trend at an rms roughness of 0.1 mm. The guided wave cut-offcut-off frequency measurements can be done using the same transduction system as that used for large area guided wave monitoring so it is possible to combine large and small area monitoring in a single unit. Frequent measurements enable the wall thickness obtained with guided wave cut-off measurements to be tracked with time, and the low susceptibility of the measurements to surface roughness means that accurate corrosion rates will be obtained.
Date Issued
2022-12
Date Acceptance
2022-07-30
Citation
NDT&E International, 2022, 132, pp.1-7
Publisher
Elsevier
Start Page
1
End Page
7
Journal / Book Title
NDT&E International
Volume
132
Copyright Statement
© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
https://www.sciencedirect.com/science/article/pii/S0963869522001128?via%3Dihub
Publication Status
Published
Date Publish Online
2022-08-05