Shi, P., Yu, Y., Watts, J. et al. (2 more authors) (2025) An application of a MEMS vector hydrophone for condition assessment of a water supply pipe. Applied Acoustics, 231. 110449. ISSN: 0003-682X
Abstract
This paper describes an application of a micro-electromechanical system (MEMS) vector hydrophone to detect 10–20 mm wall damage in a 300 mm diameter ductile iron pipe used for water distribution. A key novelty of this work is the use of the acoustic pressure and particle velocity measured in the vicinity of the pipe wall at frequencies of sound with wavelengths much greater than the pipe diameter, i.e. below 400 Hz. It is shown through numerical simulation and laboratory experiment that the acoustic particle velocity, unlike the acoustic pressure, is highly sensitive to the presence of relatively small wall damage. This work paves the way for the development of new sensor solutions that can be deployed on inspection robots in pressurized clean and wastewater pipes to localize the onset of wall damage. Machine learning algorithms could be used to train the robot to recognize signal patterns associated with an in-pipe defect to guide maintenance and repair equipment.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Pipe inspection; MEMS; Vector hydrophone; Particle velocity; Leakage |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > School of Mechanical, Aerospace and Civil Engineering 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 |
| Date Deposited: | 10 Oct 2025 16:11 |
| Last Modified: | 10 Oct 2025 16:11 |
| Status: | Published |
| Publisher: | Elsevier BV |
| Refereed: | Yes |
| Identification Number: | 10.1016/j.apacoust.2024.110449 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:232836 |

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