Robotic pipeline wall thickness evaluation for dense nondestructive testing inspection

Valls Miro, J; Ulapane, N; Shi, L; Hunt, D; Behrens, M

Robotic pipeline wall thickness evaluation for dense nondestructive testing inspection

Valls Miro, J

Ulapane, N

Shi, L

Hunt, D Behrens, M

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Publication Type:: Journal Article
Citation:: Journal of Field Robotics, 2018, 35 (8), pp. 1293 - 1310
Issue Date:: 2018-12-01

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Field	Value	Language
dc.contributor.author	Valls Miro, J https://orcid.org/0000-0002-0083-7797	en_US
dc.contributor.author	Ulapane, N https://orcid.org/0000-0003-3432-3943	en_US
dc.contributor.author	Shi, L https://orcid.org/0000-0002-5215-025X	en_US
dc.contributor.author	Hunt, D	en_US
dc.contributor.author	Behrens, M https://orcid.org/0000-0002-3072-059X	en_US
dc.date.available	2020-05-25T19:08:22Z
dc.date.issued	2018-12-01	en_US
dc.identifier.citation	Journal of Field Robotics, 2018, 35 (8), pp. 1293 - 1310	en_US
dc.identifier.issn	1556-4959	en_US
dc.identifier.uri	http://hdl.handle.net/10453/130937
dc.description.abstract	© 2018 Wiley Periodicals, Inc. This paper addresses automated mapping of the remaining wall thickness of metallic pipelines in the field by means of an inspection robot equipped with nondestructive testing (NDT) sensing. Set in the context of condition assessment of critical infrastructure, the integrity of arbitrary sections in the conduit is derived with a bespoke robot kinematic configuration that allows dense pipe wall thickness discrimination in circumferential and longitudinal direction via NDT sensing with guaranteed sensing lift-off (offset of the sensor from pipe wall) to the pipe wall, an essential barrier to overcome in cement-lined water pipelines. A tailored covariance function for pipeline cylindrical structures within the context of a Gaussian Processes has also been developed to regress missing sensor data incurred by a sampling strategy folllowed in the field to speed up the inspection times, given the slow response of the pulsed eddy current electromagnetic sensor proposed. The data gathered represent not only a visual understanding of the condition of the pipe for asset managers, but also constitute a quantative input to a remaining-life calculation that defines the likelihood of the pipeline for future renewal or repair. Results are presented from deployment of the robotic device on a series of pipeline inspections which demonstrate the feasibility of the device and sensing configuration to provide meaningful 2.5D geometric maps.	en_US
dc.relation.ispartof	Journal of Field Robotics	en_US
dc.relation.isbasedon	10.1002/rob.21828	en_US
dc.subject.classification	Industrial Engineering & Automation	en_US
dc.title	Robotic pipeline wall thickness evaluation for dense nondestructive testing inspection	en_US
dc.type	Journal Article
utslib.citation.volume	8	en_US
utslib.citation.volume	35	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0913 Mechanical Engineering	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	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.issue	8	en_US
pubs.publication-status	Published	en_US
pubs.volume	35	en_US

Abstract:

© 2018 Wiley Periodicals, Inc. This paper addresses automated mapping of the remaining wall thickness of metallic pipelines in the field by means of an inspection robot equipped with nondestructive testing (NDT) sensing. Set in the context of condition assessment of critical infrastructure, the integrity of arbitrary sections in the conduit is derived with a bespoke robot kinematic configuration that allows dense pipe wall thickness discrimination in circumferential and longitudinal direction via NDT sensing with guaranteed sensing lift-off (offset of the sensor from pipe wall) to the pipe wall, an essential barrier to overcome in cement-lined water pipelines. A tailored covariance function for pipeline cylindrical structures within the context of a Gaussian Processes has also been developed to regress missing sensor data incurred by a sampling strategy folllowed in the field to speed up the inspection times, given the slow response of the pulsed eddy current electromagnetic sensor proposed. The data gathered represent not only a visual understanding of the condition of the pipe for asset managers, but also constitute a quantative input to a remaining-life calculation that defines the likelihood of the pipeline for future renewal or repair. Results are presented from deployment of the robotic device on a series of pipeline inspections which demonstrate the feasibility of the device and sensing configuration to provide meaningful 2.5D geometric maps.

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http://hdl.handle.net/10453/130937