Monitoring of carbon steel corrosion by use of electrochemical noise and recurrence quantification analysis

The corrosion of carbon steel in aqueous media resulting in uniform corrosion, pitting corrosion and passivation was investigated on a laboratory scale. Recurrence quantification analysis was applied to short segments of electrochemical current noise measurements. These segments were converted to re...

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Main Authors: Hou, Y., Aldrich, Chris, Lepkova, Katerina, Machuca, Luis, Kinsella, B.
Format: Journal Article
Published: Elsevier 2016
Online Access:http://hdl.handle.net/20.500.11937/12725
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author Hou, Y.
Aldrich, Chris
Lepkova, Katerina
Machuca, Luis
Kinsella, B.
author_facet Hou, Y.
Aldrich, Chris
Lepkova, Katerina
Machuca, Luis
Kinsella, B.
author_sort Hou, Y.
building Curtin Institutional Repository
collection Online Access
description The corrosion of carbon steel in aqueous media resulting in uniform corrosion, pitting corrosion and passivation was investigated on a laboratory scale. Recurrence quantification analysis was applied to short segments of electrochemical current noise measurements. These segments were converted to recurrence variables, which could be used as reliable predictors in a multilayer perceptron neural network model to identify the type of corrosion. In addition, an automated corrosion monitoring scheme is proposed, based on the principal component scores of the recurrence variables. This approach used the uniform corrosion measurements as reference data and could differentiate between uniform and non-uniform corrosion.
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format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T07:00:34Z
publishDate 2016
publisher Elsevier
recordtype eprints
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spelling curtin-20.500.11937-127252018-07-12T04:58:30Z Monitoring of carbon steel corrosion by use of electrochemical noise and recurrence quantification analysis Hou, Y. Aldrich, Chris Lepkova, Katerina Machuca, Luis Kinsella, B. The corrosion of carbon steel in aqueous media resulting in uniform corrosion, pitting corrosion and passivation was investigated on a laboratory scale. Recurrence quantification analysis was applied to short segments of electrochemical current noise measurements. These segments were converted to recurrence variables, which could be used as reliable predictors in a multilayer perceptron neural network model to identify the type of corrosion. In addition, an automated corrosion monitoring scheme is proposed, based on the principal component scores of the recurrence variables. This approach used the uniform corrosion measurements as reference data and could differentiate between uniform and non-uniform corrosion. 2016 Journal Article http://hdl.handle.net/20.500.11937/12725 10.1016/j.corsci.2016.07.009 Elsevier fulltext
spellingShingle Hou, Y.
Aldrich, Chris
Lepkova, Katerina
Machuca, Luis
Kinsella, B.
Monitoring of carbon steel corrosion by use of electrochemical noise and recurrence quantification analysis
title Monitoring of carbon steel corrosion by use of electrochemical noise and recurrence quantification analysis
title_full Monitoring of carbon steel corrosion by use of electrochemical noise and recurrence quantification analysis
title_fullStr Monitoring of carbon steel corrosion by use of electrochemical noise and recurrence quantification analysis
title_full_unstemmed Monitoring of carbon steel corrosion by use of electrochemical noise and recurrence quantification analysis
title_short Monitoring of carbon steel corrosion by use of electrochemical noise and recurrence quantification analysis
title_sort monitoring of carbon steel corrosion by use of electrochemical noise and recurrence quantification analysis
url http://hdl.handle.net/20.500.11937/12725