A Novel Leakage-Detection Method Based on Sensitivity Matrix of Pipe Flow: Case Study of Water Distribution Systems
Publication: Journal of Water Resources Planning and Management
Volume 145, Issue 2
Abstract
Urban water supply networks are important infrastructure to ensure the daily water consumption of urban residents and factories. However, the scope of leakage detection is large and inaccurate using the traditional leakage-detection method based on a sensitivity matrix of the nodal flow. Therefore, this paper proposes a novel leakage-detection method based on a sensitivity matrix of the pipe flow. The sensitivity matrices regarding the pipe flow to nodal pressure and pipe flow are deduced. Then, the least-square method based on the sensitivity of the pipe flow is used to fit the actual leakage state of the pipeline network. Moreover, the leaking pipeline is determined by using the fitting residuals of each pipeline. Finally, the proposed method is applied to fit the leakage detection of water distribution systems. Compared with the traditional leakage-detection method, the results show that the proposed method is more accurate and effective in locating the leaky pipe and improving the utilization rate of water resources.
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Acknowledgments
This research was partly funded by the Natural Science Foundation of Beijing, China (4162045) and National Natural Science Foundation of China (61374166 and 61603025).
References
Aksela, K., M. Aksela, and R. Vahala. 2009. “Leakage detection in a real distribution network using a SOM.” Urban Water J. 6 (4): 279–289. https://doi.org/10.1080/15730620802673079.
Andersen, J. H., and R. S. Powell. 2000. “Implicit state-estimation technique for water network monitoring.” Urban Water 2 (2): 123–130. https://doi.org/10.1016/S1462-0758(00)00050-9.
Cong, F., and C. W. Oosterlee. 2016. “Multi-period mean-variance portfolio optimization based on Monte-Carlo simulation.” J. Econ. Dyn. Control 64: 23–38. https://doi.org/10.1016/j.jedc.2016.01.001.
Du, K., T. Y. Long, J. H. Wang, and J. S. Guo. 2015. “Inversion model of water distribution systems for nodal demand calibration.” J. Water Resour. Plann. Manage. 141 (9): 04015002. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000506.
Farley, B., S. R. Mounce, and J. B. Boxall. 2010. “Field testing of an optimal sensor placement methodology for event detection in an urban water distribution network.” Urban Water J. 7 (6): 345–356. https://doi.org/10.1080/1573062X.2010.526230.
Ferrante, M., and B. Brunone. 2003. “Pipe system diagnosis and leak detection by unsteady-state tests. 2: Wavelet analysis.” Adv. Water Resour. 26 (1): 107–116. https://doi.org/10.1016/S0309-1708(02)00102-1.
Kang, D., and K. Lansey. 2015. “Novel approach to detecting pipe bursts in water distribution networks.” J. Water Resour. Plann. Manage. 140 (1): 121–127. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000264.
Lee, P. J., J. P. Vítkovský, M. F. Lambert, A. R. Simpson, and J. A. Liggett. 2005. “Leak location using the pattern of the frequency response diagram in pipelines: A numerical study.” J. Sound Vibr. 284 (3–5): 1051–1073. https://doi.org/10.1016/j.jsv.2004.07.023.
Liggett, J. A., and L. C. Chen. 1996. “Inverse transient analysis in pipe networks.” J. Hydraul. Eng. 120 (8): 934–955. https://doi.org/10.1061/(ASCE)0733-9429(1994)120:8(934).
Liu, N. D., K. Du, J. P. Tu, and W. X. Dong. 2017. “Analytical solution of Jacobian matrices of WDS models.” Proc. Eng. 186: 388–396. https://doi.org/10.1016/j.proeng.2017.03.236.
Liu, T., Y. Liu, J. Li, and X. Dong. 2013. “Leakage situation and control solution of China water supply pipeline.” J. Fudan Univ. (Natural Science) 52 (06): 807–810.
Mamo, T. G., I. Juran, and I. Shahrour. 2014. “Virtual DMA municipal water supply pipeline leak detection and classification using advance pattern recognizer multi-class SVM.” J. Pattern Recognit. Res. 9 (1): 25–42. https://doi.org/10.13176/11.548.
Ministry of Construction of the People’s Republic of China. 2002. “Standard for leakage control and assessment of urban water supply distribution system.” CJJ 92-2002 J187-2002. Shanghai: China Architecture & Building Press.
Mounce, S. R., J. B. Boxall, and J. Machell. 2009. “Development and verification of an online artificial intelligence system for detection of bursts and other abnormal flows.” J. Water Resour. Plann. Manage. 13 (4): 672–686. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000030.
Mounce, S. R., A. Khan, A. S. Wood, A. J. Day, P. D. Widdop, and J. Machell. 2003. “Sensor-fusion of hydraulic data for burst detection and location in a treated water distribution system.” Inf. Fusion 4 (3): 217–229. https://doi.org/10.1016/S1566-2535(03)00034-4.
Mounce, S. R., R. B. Mounce, and J. B. Boxall. 2011. “Novelty detection for time series data analysis in water distribution systems using support vector machines.” J. Hydroinf. 13 (4): 672–686. https://doi.org/10.2166/hydro.2010.144.
Mpesha, W., M. Hanif Chaudhry, and S. L. Gassman. 2002. “Leak detection in pipes by frequency response method using a step excitation.” J. Hydraul. Res. 40 (1): 55–62. https://doi.org/10.1080/00221680209499873.
Palau, C. V., F. J. Arregui, and M. Carlos. 2011. “Burst detection in water networks using principal component analysis.” J. Water Resour. Plann. Manage. 138 (1): 47–54. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000147.
Pérez, R., V. Puig, J. Pascual, A. Peralta, E. Landeros, and L. Jordanas. 2009. “Pressure sensor distribution for leak detection in Barcelona water distribution network.” Water Sci. Technol. Water Supply 9 (6): 715–721. https://doi.org/10.2166/ws.2009.372.
Pérez, R., V. Puig, J. Pascual, J. Quevedo, E. Landeros, and A. Peralta. 2011. “Methodology for leakage isolation using pressure sensitivity analysis in water distribution networks.” Control Eng. Pract. 19 (10): 1157–1167. https://doi.org/10.1016/j.conengprac.2011.06.004.
Poulakis, Z., D. Valougeorgis, and C. Papadimitriou. 2003. “Leakage detection in water pipe networks using a Bayesian probabilistic framework.” Probab. Eng. Mech. 18 (4): 315–327. https://doi.org/10.1016/S0266-8920(03)00045-6.
Puust, R., Z. Kapelan, D. Savic, and T. Koppel. 2008. “Probabilistic leak detection in pipe networks using the SCEM-UA algorithm.” In Proc., Water Distribution Systems Analysis Symp., 1–12. Reston: ASCE.
Romano, M., Z. Kapelan, and D. A. Savić. 2010. “Real-time leak detection in water distribution systems.” In Proc., Water Distribution Systems Analysis, 1074–1082. Reston: ASCE.
Schwaller, J., and J. E. Van Zyl. 2014. “Modeling the pressure-leakage response of water distribution systems based on individual leak behavior.” J. Hydraul. Eng. 141 (5): 04014089. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000984.
Steffelbauer, D., M. Neumayer, M. Günther, and D. Fuchs-Hanusch. 2014. “Sensor placement and leakage localization considering demand uncertainties.” Proc. Eng. 89: 1160–1167. https://doi.org/10.1016/j.proeng.2014.11.242.
Vítkovský, J. P., A. R. Simpson, and M. F. Lambert. 2000. “Leak detection and calibration using transients and genetic algorithms.” J. Water Resour. Plann. Manage. 126 (4): 262–265. https://doi.org/10.1061/(ASCE)0733-9496(2000)126:4(262).
Vries, D., B. van den Akker, E. Vonk, W. de Jong, and J. van Summeren. 2016. “Application of machine learning techniques to predict anomalies in water supply networks.” Water Sci. Technol. Water Supply 16 (6): 1528–1535. https://doi.org/10.2166/ws.2016.062.
Ye, G., and R. A. Fenner. 2010. “Kalman filtering of hydraulic measurements for burst detection in water distribution systems.” J. Pipeline Syst. Eng. Pract. 2 (1): 14–22. https://doi.org/10.1061/(ASCE PS.1949-1204.0000070.
Yeh, W. W. G. 1986. “Review of parameter identification procedures in groundwater hydrology: The inverse problem.” Water Resour. Res. 22 (2): 95–108. https://doi.org/10.1029/WR022i002p00095.
Zhang, J. 1997. “Designing a cost-effective and reliable pipeline leak-detection system.” Pipes Pipelines Int. 42 (1): 20–26. https://doi.org/10.1016/j.jlp.2008.09.012.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 145 • Issue 2 • February 2019
Copyright
©2018 American Society of Civil Engineers.
History
Received: Nov 29, 2017
Accepted: Jul 23, 2018
Published online: Nov 30, 2018
Published in print: Feb 1, 2019
Discussion open until: Apr 30, 2019
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