Guided wave based-occupancy grid robotic mapping
Tabatabaeipour, Seyed Morteza and Trushkevych, Oksana and Dobie, Gordon and Edwards, Rachel and MacLeod, Charles Norman and Pierce, Gareth; Rizzo, Piervincenzo and Milazzo, Alberto, eds. (2021) Guided wave based-occupancy grid robotic mapping. In: European Workshop on Structural Health Monitoring. Lecture Notes in Civil Engineering (LNCE) . Springer International Publishing AG, ITA, pp. 267-275. ISBN 978-3-030-64908-1 (https://doi.org/10.1007/978-3-030-64908-1_25)
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Abstract
Asset inspection of large structures such as storage tanks in the oil, gas and petrochemical industry is challenging, either requiring labour-intensive manual measurements or using robotic deployment to make the measurements. Current robotic systems employ point-by-point scanning, which is time-consuming. Using guided waves for such inspections is attractive as they provide a mechanism for monitoring the inaccessible areas and simultaneously providing structural location data to speed up the inspection process. In this research, shear horizontal (SH) guided waves generated by electromagnetic acoustic transducers (EMATs) are used to screen a large area using a crawler. EMATs with 22 mm wavelength are used to generate the first two SH modes: a non-dispersive SH0 and highly dispersive SH1 on a 10 mm thick steel sample. Previously, we have demonstrated the feasibility of guided wave-based occupancy grid mapping (GW-OGM) for mapping a structure's edges. In this work, the GW-OGM technique is generalised to identify and estimate the location of a flat bottom hole in a pitch-catch mode. The simulation and empirical data demonstrate that the location of damage can be identified as the robot navigates on the component, with full coverage. Moreover, the simulated data are in good agreement with the experimental results on the generation of SH wave modes.
ORCID iDs
Tabatabaeipour, Seyed Morteza, Trushkevych, Oksana, Dobie, Gordon ORCID: https://orcid.org/0000-0003-3972-5917, Edwards, Rachel, MacLeod, Charles Norman ORCID: https://orcid.org/0000-0003-4364-9769 and Pierce, Gareth ORCID: https://orcid.org/0000-0003-0312-8766; Rizzo, Piervincenzo and Milazzo, Alberto-
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Item type: Book Section ID code: 75772 Dates: DateEvent9 January 2021Published8 September 2020AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
Strategic Research Themes > Advanced Manufacturing and Materials
Technology and Innovation Centre > Sensors and Asset ManagementDepositing user: Pure Administrator Date deposited: 11 Mar 2021 16:04 Last modified: 11 Nov 2024 15:22 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/75772