Yu, Y., Safari, A., Niu, X. et al. (2 more authors) (2021) Acoustic and ultrasonic techniques for defect detection and condition monitoring in water and sewerage pipes: a review. Applied Acoustics, 183. 108282. ISSN 0003-682X
Abstract
Condition monitoring for water and sewerage pipes is essential for the safety of the environment, energy conservation and human health. This paper focuses on the application of acoustic and ultrasonic techniques for the detection and assessment of leaks, blockages and defect in buried pipes. The review includes acoustic methods (below 20 kHz) based on vibration sensing using accelerometers, hydrophones and fibre optic sensors, and ultrasonic methods (above 20 kHz) based on the propagation of bulk and guided waves. Related data-driven, machine-learning techniques are also discussed. Typical arrangements of sensors are shown, explained and analysed in terms of their applicability to buried pipe networks. Commercial systems and state of the art research for the inspection of pipes made of a range of materials such as cast iron, high-density polyethylene and concrete are critically assessed. This review also explores the future application of autonomous robotics to deploy these sensors in water distribution and sewerage pipes.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 Elsevier Ltd. This is an author produced version of a paper subsequently published in Applied Acoustics. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Acoustics; Ultrasonics; Ultrasonic guided waves; Water pipes; Sewerage pipes; Buried pipeline |
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 Sciences Research Council 1943491 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 02 Aug 2021 16:11 |
Last Modified: | 21 Jul 2022 00:13 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.apacoust.2021.108282 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:176694 |