Experimental investigation into vibro-acoustic emission signal processing techniques to quantify leak flow rate in plastic water distribution pipes. (April 2017)

• Record Type: Journal Article
• Authors: Butterfield, J.D.; Krynkin, A.; Collins, R.P.; Beck, S.B.M.
• Is Part Of: Applied acoustics. Volume 119(2017)
• Page Start: 146
• Page End: 155
• Publication Date: 2017-04
• Subjects: Leakage -- Water supply -- Pipeline -- Acoustic emission -- Leak rate -- Acoustic energy -- Vibration; Acoustical engineering -- Periodicals; Periodicals; 620.2
• DOI: 10.1016/j.apacoust.2017.01.002
• Languages: English
• ISSNs: 0003-682X

Abstract

Highlights: Signal processing of vibro-acoustic emission signals is shown to be capable of quantifying leak flow rate. Of the signal processing techniques investigated, root mean square is shown to be the most effective in quantifying leak flow rate and numerical model is presented. The surrounding media the pipe is buried in is shown to have a strong influence on leak vibro-acoustic emission signal. 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.