Anomaly Detection in Targeted Pipe Sections in Water Pipe Systems Using Hydroacoustic Signal Deconvolution
Publication: Journal of Hydraulic Engineering
Volume 150, Issue 1
Abstract
Detection of anomalies, such as leaks, blockages and deteriorated sections, in underground water pipe networks and long transmission mains is a challenging problem. This paper proposes a novel method for anomaly detection in targeted pipe sections embedded within any complex pipe system. In the proposed approach, persistent hydroacoustic waves generated simply by opening a side-discharge valve are sent into the pipe system through existing access points, such as hydrants and air valves. Pressure measurements are required only at existing access points that bracket the pipe section of interest. A signal deconvolution process was developed to transfer the complex waveforms of the measured hydroacoustic waves into a deconvolution trace, which consists of impulse response functions (IRFs) of the pipe. Mathematical models that link the spikes in the deconvolution trace to the anomalies existing in the pipe system were derived to identify and localize these anomalies. Numerical validation was undertaken on three different pipe configurations: two single-pipe systems, and a pipe network. Experimental validation was conducted on a laboratory copper pipe network connected to the municipal water distribution system in which a simulated leak was localized accurately. The results demonstrate that the proposed technique (1) is easy to implement (it uses only valves and single pressure transducers connected to existing access points), (2) is able to detect and locate anomalies accurately for targeted pipe sections in complex pipe systems, and (3) is tolerant of background pressure fluctuations and noise that naturally occur in real water distribution systems.
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Data Availability Statement
The simulation and experimental data as used during the study are available from the corresponding author by request.
Acknowledgments
The research presented in this paper has been supported by the Australian Research Council through the Discovery Projects Grants DP 190102484 and DP 210103565. The authors thank technicians Brenton Howie and Simon Golding for their support in the experimental work.
References
Brunone, B. 1999. “Transient test-based technique for leak detection in outfall pipes.” J. Water Resour. Plann. Manage. 125 (5): 302–306. https://doi.org/10.1061/(ASCE)0733-9496(1999)125:5(302).
Brunone, B., and M. Ferrante. 2004. “Pressure waves as a tool for leak detection in closed conduits.” Urban Water J. 1 (2): 145–155. https://doi.org/10.1080/1573062042000271073.
Capponi, C., B. Brunone, F. Maietta, and S. Meniconi. 2023. “Hydraulic diagnostic kit for the automatic expeditious survey of in-line valve sealing in long, large diameter transmission mains.” Water Resour. Manage. 37 (5): 1931–1945. https://doi.org/10.1007/s11269-023-03463-7.
Ghazali, M. F., S. B. M. Beck, J. D. Shucksmith, J. B. Boxall, and W. J. Staszewski. 2012. “Comparative study of instantaneous frequency based methods for leak detection in pipeline networks.” Mech. Syst. Signal Process. 29 (5): 187–200. https://doi.org/10.1016/j.ymssp.2011.10.011.
Gong, J., M. F. Lambert, A. C. Zecchin, and A. R. Simpson. 2016. “Experimental verification of pipeline frequency response extraction and leak detection using the inverse repeat signal.” J. Hydraul. Res. 54 (2): 210–219. https://doi.org/10.1080/00221686.2015.1116115.
Liou, C. P. 1998. “Pipeline leak detection by impulse response extraction.” J. Fluids Eng. 120 (4): 833–838. https://doi.org/10.1115/1.2820746.
Nguyen, S. T. N., J. Gong, M. F. Lambert, A. C. Zecchin, and A. R. Simpson. 2018. “Least squares deconvolution for leak detection with a pseudo random binary sequence excitation.” Mech. Syst. Signal Process. 99 (1): 846–858. https://doi.org/10.1016/j.ymssp.2017.07.003.
Shucksmith, J. D., J. B. Boxall, W. J. Staszewski, A. Seth, and S. B. M. Beck. 2012. “Onsite leak location in a pipe network by cepstrum analysis of pressure transients.” J. AWWA 104 (8): E457–E465. https://doi.org/10.5942/jawwa.2012.104.0108.
Taghvaei, M., S. B. M. Beck, and W. J. Staszewski. 2006. “Leak detection in pipelines using cepstrum analysis.” Meas. Sci. Technol. 17 (2): 367–372. https://doi.org/10.1088/0957-0233/17/2/018.
Tijsseling, A., M. Lambert, A. Simpson, M. Stephens, J. Vítkovský, and A. Bergant. 2006. “Wave front dispersion due to fluid-structure interaction in long liquid-filled pipelines.” In Proc., 23rd IAHR Symp. Eindhoven, Netherlands: Eindhoven Univ. of Technology.
Vítkovský, J. P., P. J. Lee, M. L. Stephens, M. F. Lambert, A. R. Simpson, and J. A. Liggett. 2003. “Leak and blockage detection in pipelines via an impulse response method.” In Proc., Int. Conf. Pumps, Electromechanical Devices and Systems Applied to Urban Water Management, 423–430. Lisse: A. A. Balkema.
Wang, X., M. S. Ghidaoui, and P. J. Lee. 2020. “Linear model and regularization for transient wave–based pipeline-condition assessment.” J. Water Resour. Plann. Manage. 146 (5): 04020028. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001205.
Wong, L., R. Deo, S. Rathnayaka, B. Shannon, C. Zhang, J. Kodikara, W. Chiu, and H. Widyastuti. 2018. “Water pipe condition assessment using submersible quasi-distributed optical fibre based pressure transducers.” Electron. J. Struct. Eng. 18 (1): 54–60. https://doi.org/10.56748/ejse.182291.
WSAA and IPA (Water Services Association of Australia and Infrastructure Partnerships Australia). 2015. Doing the important, as well as the urgent: Reforming the urban water sector. Sydney, Australia: WSAA and IPA.
Wylie, E. B. 1984. “Fundamental equations of waterhammer.” J. Hydraul. Eng. 110 (4): 539–542. https://doi.org/10.1061/(ASCE)0733-9429(1984)110:4(539).
Wylie, E. B., and V. L. Streeter. 1993. Fluid transients in systems. Englewood Cliffs, NJ: Prentice Hall.
Zanganeh, R., E. Jabbari, A. Tijsseling, and A. Keramat. 2020. “Fluid-structure interaction in transient-based extended defect detection of pipe walls.” J. Hydraul. Eng. 146 (4): 04020015. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001693.
Zeng, W., J. Gong, P. R. Cook, J. W. Arkwright, A. R. Simpson, B. S. Cazzolato, A. C. Zecchin, and M. F. Lambert. 2020a. “Leak detection for pipelines using in-pipe optical fiber pressure sensors and a paired-IRF technique.” J. Hydraul. Eng. 146 (10): 06020013. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001812.
Zeng, W., J. Gong, A. R. Simpson, B. S. Cazzolato, A. C. Zecchin, and M. F. Lambert. 2020b. “Paired-IRF method for detecting leaks in pipe networks.” J. Water Resour. Plann. Manage. 146 (5): 04020021. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001193.
Zeng, W., J. Gong, A. C. Zecchin, M. F. Lambert, A. R. Simpson, and B. S. Cazzolato. 2018. “Condition assessment of water pipelines using a modified layer-peeling method.” J. Hydraul. Eng. 144 (12): 04018076. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001547.
Zeng, W., A. C. Zecchin, B. S. Cazzolato, A. R. Simpson, J. Gong, and M. F. Lambert. 2021. “Extremely sensitive anomaly detection in pipe networks using a higher-order paired-impulse response function with a correlator.” J. Water Resour. Plann. Manage. 147 (10): 04021068. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001446.
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© 2023 American Society of Civil Engineers.
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Received: Feb 16, 2023
Accepted: Sep 14, 2023
Published online: Nov 9, 2023
Published in print: Jan 1, 2024
Discussion open until: Apr 9, 2024
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