Improved signal interpretation for cast iron thickness assessment based on pulsed eddy current sensing

Nguyen, L; Ulapane, N; Miro, JV; Dissanayake, G; Munoz, F

Improved signal interpretation for cast iron thickness assessment based on pulsed eddy current sensing

Nguyen, L

Ulapane, N

Miro, JV

Dissanayake, G

Munoz, F

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2017 12th IEEE Conference on Industrial Electronics and Applications, ICIEA 2017, 2018, 2018-February pp. 2005 - 2010
Issue Date:: 2018-02-05

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Field	Value	Language
dc.contributor.author	Nguyen, L https://orcid.org/0000-0001-5360-886X	en_US
dc.contributor.author	Ulapane, N https://orcid.org/0000-0003-3432-3943	en_US
dc.contributor.author	Miro, JV https://orcid.org/0000-0002-0083-7797	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.contributor.author	Munoz, F https://orcid.org/0000-0002-0143-5407	en_US
dc.date.available	2017-02-25	en_US
dc.date.issued	2018-02-05	en_US
dc.identifier.citation	Proceedings of the 2017 12th IEEE Conference on Industrial Electronics and Applications, ICIEA 2017, 2018, 2018-February pp. 2005 - 2010	en_US
dc.identifier.isbn	9781538621035	en_US
dc.identifier.uri	http://hdl.handle.net/10453/107370
dc.description.abstract	© 2017 IEEE. This paper presents a novel signal processing approach for computing thickness of ferromagnetic cast iron material, widely employed in older infrastructure such as water mains or bridges. Measurements are gathered from a Pulsed Eddy Current (PEC) based sensor placed on top of the material, with unknown lift-off, as commonly used during non-destructive testing (NDT). The approach takes advantage of an analytical logarithmic model proposed in the literature for the decaying voltage induced at the PEC sensor pick-up coil. An increasingly more accurate and robust algorithm is proven here by means of an Adaptive Least Square Fitting Line (ALSFL) recursive strategy, suitable to recognize the most linear part of the sensor's logarithmic output voltage for subsequent gradient computation, from which thickness is then derived. Moreover, efficiency is also gained as processing can be carried out on only one decaying voltage signal, unlike averaging over multiple measurements as is usually done in the literature. Importantly, the new signal processing methodology demonstrates highest accuracies at the lower thicknesses, a circumstance most relevant to NDT evaluation. Experiments that verify the proposed method in real-world thickness assessment of cast iron material are presented and compared with current practices, showing promising results.	en_US
dc.relation.ispartof	Proceedings of the 2017 12th IEEE Conference on Industrial Electronics and Applications, ICIEA 2017	en_US
dc.relation.isbasedon	10.1109/ICIEA.2017.8283167	en_US
dc.title	Improved signal interpretation for cast iron thickness assessment based on pulsed eddy current sensing	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2018-February	en_US
utslib.for	091307 Numerical Modelling and Mechanical Characterisation	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	2018-February	en_US

Abstract:

© 2017 IEEE. This paper presents a novel signal processing approach for computing thickness of ferromagnetic cast iron material, widely employed in older infrastructure such as water mains or bridges. Measurements are gathered from a Pulsed Eddy Current (PEC) based sensor placed on top of the material, with unknown lift-off, as commonly used during non-destructive testing (NDT). The approach takes advantage of an analytical logarithmic model proposed in the literature for the decaying voltage induced at the PEC sensor pick-up coil. An increasingly more accurate and robust algorithm is proven here by means of an Adaptive Least Square Fitting Line (ALSFL) recursive strategy, suitable to recognize the most linear part of the sensor's logarithmic output voltage for subsequent gradient computation, from which thickness is then derived. Moreover, efficiency is also gained as processing can be carried out on only one decaying voltage signal, unlike averaging over multiple measurements as is usually done in the literature. Importantly, the new signal processing methodology demonstrates highest accuracies at the lower thicknesses, a circumstance most relevant to NDT evaluation. Experiments that verify the proposed method in real-world thickness assessment of cast iron material are presented and compared with current practices, showing promising results.

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http://hdl.handle.net/10453/107370