Butterfield, J.D., Krynkin, A., Collins, R.P. et al. (1 more author) (2017) Experimental investigation into vibro-acoustic emission signal processing techniques to quantify leak flow rate in plastic water distribution pipes. Applied Acoustics, 119. pp. 146-155. ISSN 0003-682X
Abstract
Leakage from water distribution pipes is a problem worldwide, and are commonly detected using the Vibro-Acoustic Emission (VAE) produced by the leak. The ability to quantify leak flow rate using VAE would have economic and operational benefits. However the complex interaction between variables and the leak’s VAE signal make classification of leak flow rate difficult and therefore there has been a lack of research in this area. The aim of this study is to use VAE monitoring to investigate signal processing techniques that quantify leak flow rate. A number of alternative signal processing techniques are deployed and evaluated, including VAE counts, signal Root Mean Square (RMS), peak in magnitude of the power spectral density and octave banding. A strong correlation between the leak flow rate and signal RMS was found which allowed for the development of a flow prediction model. The flow prediction model was also applied to two other media types representing buried water pipes and it was found that the surrounding media had a strong influence on the VAE signal which reduced the accuracy of flow classification. A further model was developed for buried pipes, and was found to yield good leak flow quantification using VAE. This paper therefore presents a useful method for water companies to prioritise maintenance and repair of leaks on water distribution pipes.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Leakage; Water supply; Pipeline; Acoustic emission; Leak rate; Acoustic energy; Vibration |
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) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Jan 2017 09:55 |
Last Modified: | 29 Oct 2018 11:36 |
Published Version: | https://doi.org/10.1016/j.apacoust.2017.01.002 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.apacoust.2017.01.002 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:110342 |