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The effect of corrosion induced surface morphology changes on ultrasonically monitored corrosion rates

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AXC_Revised_24May16.pdfAccepted version1.12 MBAdobe PDFView/Open
sms_25_11_115010.pdfPublished version1.37 MBAdobe PDFView/Open
Title: The effect of corrosion induced surface morphology changes on ultrasonically monitored corrosion rates
Authors: Cegla, FB
Gajdacsi, A
Item 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.
Issue Date: 1-Nov-2016
Date of Acceptance: 15-Jun-2016
URI: http://hdl.handle.net/10044/1/33704
DOI: 10.1088/0964-1726/25/11/115010
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.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/K033565/1
Keywords: 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
Online Publication Date: 2016-10-07
Appears in Collections:Mechanical Engineering
Faculty of Engineering