Interpretation of Acoustic Field Data for Leak Detection in Ductile Iron and Copper Water-Distribution Pipes
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 8, Issue 3
Abstract
The acoustic emission (AE) method is becoming popular for detecting leaks in municipal water mains where leaks are identified and the locations are determined through the interpretation of measured acoustic signals without excavation or disruption of services. For the interpretation of signals, several parameters, such as the frequency band of signals, coherence between signals, and cross correlation between signals, are used. However, studies published in the literature lack data on the applicability of the AE method under various field conditions. This paper presents a number of case studies on the field application of the AE method performed by measuring acoustic noises at two points bracketing a leak along the pipe length. Relevant parameters for successful leak detection in ductile iron and copper water distribution pipes are identified. In the case studies presented, leaks were successfully determined for an estimated leak rate of and with a sensor distance of up to 176 m. Acoustic signal frequency corresponding to the leak noise was found to vary from approximately 220 Hz to around 1,400 Hz. The magnitudes of coherence between the signals from two sensors were higher than 0.5.
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Acknowledgments
The AE test results were provided by the city of Mount Pearl in the Province of Newfoundland and Labrador, Canada. The support from the city is gratefully acknowledged. The financial support for this research was provided by Research and Development Corporation of Newfoundland and Labrador. The authors appreciate the comments from the anonymous reviewers.
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Information
Published In
Journal of Pipeline Systems Engineering and Practice
Volume 8 • Issue 3 • August 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Oct 9, 2015
Accepted: Sep 27, 2016
Published online: Jan 23, 2017
Discussion open until: Jun 23, 2017
Published in print: Aug 1, 2017
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