Imperial College London
Alternate

DrFredericCegla

Faculty of Engineering, Department of Mechanical Engineering

Reader in Mechanical Engineering
 
 
 
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Contact

 

+44 (0)20 7594 8096f.cegla

 
 
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Location

 

567City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Cegla:2016:11/115010,
author = {Cegla, FB and Gajdacsi, A},
doi = {11/115010},
journal = {Smart Materials and Structures},
title = {The effect of corrosion induced surface morphology changes on ultrasonically monitored corrosion rates},
url = {http://dx.doi.org/10.1088/0964-1726/25/11/115010},
volume = {25},
year = {2016}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Cegla,FB
AU  - Gajdacsi,A
DO  - 11/115010
PY  - 2016///
SN  - 1361-665X
TI  - The effect of corrosion induced surface morphology changes on ultrasonically monitored corrosion rates
T2  - Smart Materials and Structures
UR  - http://dx.doi.org/10.1088/0964-1726/25/11/115010
UR  - http://hdl.handle.net/10044/1/33704
VL  - 25
ER  -
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