Yu, Y., Shi, P., Krynkin, A. et al. (1 more author) (2024) An application of a beamforming technique, linear acoustic array and robot for pipe condition localization. Measurement, 238. 115361. ISSN 0263-2241
Abstract
Pipe inspection robots with sensors significantly enhance the maintenance of water systems by enabling early defect detection and reducing the risks of leaks and environmental damage. This paper introduces a sparse representation acoustic beamformer designed to locate artefacts within pipes using a short linear microphone array on a robot. The primary contributions include: (i) a new acoustic beamforming approach based on sparse representation that accurately predicts pipe conditions with a localization error within 3 % of the sensing distance; (ii) an enhanced beamforming algorithm combining plane wave and first non-axisymmetric mode, extending the frequency range from < 1300 Hz to < 2200 Hz in a 150 mm diameter pipe (an increase by 1.69 times), effectively managing unwanted acoustic reverberations and distinguishing blockages from lateral connections; and (iii) a novel robust algorithm predicting pipe length with an error margin within 2 %. This research advances acoustic sensing technologies for autonomous mobile robots inspecting buried pipes.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Acoustic beamforming; Robotic localization; Microphone array; Pipe inspection; Sparse representation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/S016813/1 Engineering and Physical Sciences Research Council 1943491 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Aug 2024 13:44 |
Last Modified: | 07 Aug 2024 13:44 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.measurement.2024.115361 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:215683 |