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

Fatigue life prediction of clutch sleeve based on abrasion mathematical model in service period

“…Abdulshaheed et al 17 analysed a variety of leakage testing methods under pressure and discussed the leakage problems in stable and unstable states and summarized different detection methods for special oil and water conveyance purposes. Another example, Butterfield et al 19 used vibro-acoustic emission (VAE) to monitor and quantify the leakage flow signal processing technology; the buried pipeline model has been further developed. In many cases, failure of external corrosion and other dynamic structures can lead to leakage failure, such as petroleum pipelines.…”

“…In many cases, failure of external corrosion and other dynamic structures can lead to leakage failure, such as petroleum pipelines. Another example, Butterfield et al 19 used vibro-acoustic emission (VAE) to monitor and quantify the leakage flow signal processing technology; the buried pipeline model has been further developed. In other fields, influences of different factors on the performance can be well obtained in numerical simulation by considering the influence of clearance.…”

Prediction of leak flow rate in plastic water distribution pipes using vibro-acoustic measurements

“…Studying just one hole size, the RMS of leak signals has also been shown to effectively describe leak flow rate in plastic water pipe by Butterfield et al 2 and in gas pipes by Chen et al 7 EMD-based decomposition was used by Sun et al 5 in combination with the signal RMS to classify the aperture of leaks in gas pipes, finding that the RMS of individual IMFs, produced from EMD provided good separation between circular holes in gas pipes of different diameters. RMS features can be used to characterise continuous vibration signals, with the RMS value representing the energy of the signal at that point in time 5 and could therefore be a good feature in predicting leak flow rates.…”

“…A number of factors have been shown to influence a leak signal and therefore vary the efficacy of leak noise correlators. Some of these factors have been investigated in the literature, including leak flow rate, backfill, pipe material, [2][3][4] among others. The leak's vibro-acoustic emission (VAE) is determined by all of the aforementioned parameters and therefore it may be possible to use the leak signal to predict both the leak flow rate 2 and leak area.…”

“…Signal RMS is likely a useful parameter as it has been shown to increase with leak flow rate. 2,8,7 Interestingly, the model preferred to utilise features that are broken down by individual frequency bands rather than the RMS of the whole signal which was not favoured by the model. The fast Fourier transform (FFT) of each IMF has demonstrated that those IMFs .…”