The effect of corrosion induced surface morphology changes on ultrasonically monitored corrosion rates
File(s)
Published version
Accepted version
Author(s)
Cegla, FB
Gajdacsi, A
Type
Journal Article
Abstract
Corrosion rates obtained by very frequent (daily) measurements with permanently installed ultrasonic sensors have been shown to be highly inaccurate when changes in surface morphology lead to ultrasonic signal distortion. In this paper the accuracy of ultrasonically estimated corrosion rates (mean wall thickness loss) by means of standard signal processing methods (peak to peak—P2P, first arrival—FA, cross correlation—XC) was investigated and a novel thickness extraction algorithm (adaptive cross-correlation—AXC) is presented. All of the algorithms were tested on simulated ultrasonic data that was obtained by modelling the surface geometry evolution coupled with a fast ultrasonic signal simulator based on the distributed point source method. The performance of each algorithm could then be determined by comparing the actual known mean thickness losses of the simulated surfaces to the values that each algorithm returned. The results showed that AXC is the best of the investigated processing algorithms. For spatially random thickness loss 90% of AXC estimated thickness trends were within −10 to +25% of the actual mean loss rate (e.g. 0.75–1.1 mm year−1 would be measured for a 1 mm year−1 actual mean loss rate). The other algorithms (P2P, FA, XC) exhibited error distributions that were 5–10 times larger. All algorithms performed worse in scenarios where wall loss was not distributed randomly in space (spatially correlated thickness loss occured) and where the overall rms of the surface was either growing or declining. However, on these surfaces AXC also outperformed the other algorithms and showed almost an order of magnitude improvement compared to them.
Date Issued
2016-11-01
Date Acceptance
2016-06-15
Citation
Smart Materials and Structures, 2016, 25 (11)
ISSN
1361-665X
Publisher
IOP Publishing
Journal / Book Title
Smart Materials and Structures
Volume
25
Issue
11
Copyright Statement
Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
License URL
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/K033565/1
Subjects
Science & Technology
Technology
Instruments & Instrumentation
Materials Science, Multidisciplinary
Materials Science
corrosion monitoring
ultrasonic monitoring
surface morphology
corrosion rate
structural health monitoring
ROUGHNESS
PREDICTION
SCATTERING
Materials
03 Chemical Sciences
09 Engineering
Publication Status
Published
Article Number
115010
Date Publish Online
2016-10-07