Optimizing Sensor Placement and Quantity for Pipe Burst Detection in a Water Distribution Network
Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 11
Abstract
The configuration of a burst detection network is fundamental to safely monitoring a water distribution network (WDN). A pipe burst event can be detected only when the effects of the burst are distinguishable from background noise in the monitoring system. A new method of optimizing pressure sensor placement is proposed to monitor pipes in cases in which burst events are likely to have severe effects. An objective function for monitoring water leakage was defined. A genetic algorithm was used to find the optimal sensor placement in the pipe monitoring network and the most economical quantity of sensors. The method was illustrated with three case studies. In each case, the optimal solution evenly distributed the sensors across the WDN, and the number of sensors was determined based on the marginal gain of an additional sensor. In the optimal configuration, monitored pipes were identified clearly.
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Data Availability Statement
All WDN models during the study are available from the corresponding author by request.
Acknowledgments
This study was supported by the National Nature Science Foundation of China (NSFC) (Project No. 51578486), Guangzhou Science and Technology Program (No. 201604020019).
References
Baghdadi, A. H. A., and H. A. Mansy. 1988. “A mathematical model for leak location in pipelines.” Appl. Math. Modell. 12 (1): 25–30. https://doi.org/10.1016/0307-904X(88)90020-0.
Blesa, J., F. Nejjari, and R. Sarrate. 2016. “Robust sensor placement for leak location: Analysis and design.” J. Hydroinf. 18 (1): 2015021. https://doi.org/10.2166/hydro.2015.021.
Casillas, M. V., P. Vicenc, L. E. Garza-Castanon, and R. Albert. 2015. “Optimal sensor placement for leak location in water distribution networks using genetic algorithms.” Sensors 13 (11): 14984–15005. https://doi.org/10.3390/s131114984.
Cheng, W., H. Fang, G. Xu, and M. Chen. 2018. “Using SCADA to detect and locate bursts in a long-distance water pipeline.” Water 10 (12): 1727. https://doi.org/10.3390/w10121727.
Cheng, W., G. Xu, H. Fang, and D. Zhao. 2019. “Study on pipe burst detection frame based on water distribution model and monitoring system.” Water 11 (7): 1363. https://doi.org/10.3390/w11071363.
Cugueró-Escofet, M. À., V. Puig, and J. Quevedo. 2017. “Optimal pressure sensor placement and assessment for leak location using a relaxed isolation index: Application to the Barcelona water network.” Control Eng. Pract. 63 (21): 1–12. https://doi.org/10.1016/j.conengprac.2017.03.003.
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.
Goulet, J. A., S. Coutu, and I. F. C. Smith. 2013. “Model falsification diagnosis and sensor placement for leak detection in pressurized pipe networks.” Adv. Eng. Inf. 27 (2): 261–269. https://doi.org/10.1016/j.aei.2013.01.001.
Kang, D. S., and K. Lansey. 2010. “Optimal meter placement for water distribution system state estimation.” J. Water Resour. Plann. Manage. 136 (3): 337–347. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000037.
Kang, D. S., M. F. K. Pasha, and K. Lansey. 2009. “Approximate methods for uncertainty analysis of water distribution systems.” Urban Water J. 6 (3): 233–249. https://doi.org/10.1080/15730620802566844.
Kessler, A., A. Ostfeld, and G. Sinai. 1998. “Detecting accidental contaminations in municipal water networks.” J. Water Resour. Plann. Manage. 124 (4): 192–198. https://doi.org/10.1061/(ASCE)0733-9496(1998)124:4(192).
Li, D., H. Xue, and W. Zhang. 2018. “Optimal layout method of water pressure monitoring points for water supply network based on fault diagnosis.” J. Civ. Archit. Environ. Eng. 40 (2): 53–61. https://doi.org/10.11835/j.issn.1674-4764.2018.02.009.
Lu, R. Q., H. W. Zhang, Z. G. Niu, and W. J. Peng. 2010. “Study on an arrangement method for pressure monitoring points in urban water supply network by nonlinear mapping theory.” J. Hydraul. Eng. 41 (1): 25–29. https://doi.org/10.13243/j.cnki.slxb.2010.01.015.
Luo, H., J. Wang, X. Li, and J. Zhu. 2017. “Layout optimization of large-scale urban water supply network pressure measuring point distribution using genetic algorithm.” In Proc., 2017 36th Chinese Control Conf. (CCC), 1687–1691. Piscataway, NJ: IEEE. https://doi.org/10.23919/ChiCC.2017.8027594.
Ostfeld, A., E. Salomons, L. Ormsbee, J. G. Uber, C. M. Bros, P. Kalungi, and R. McKillop. 2012. “Battle of the water calibration networks.” J. Water Resour. Plann. Manage. 138 (5): 523–532. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000191.
Pérez, R., V. Puig, J. Pascual, J. Quevedo, E. Landeros, and A. Peralta. 2010. “Leakage isolation using pressure sensitivity analysis in water distribution networks: Application to the Barcelona case study.” IFAC Proc. 43 (8): 578–584. https://doi.org/10.3182/20100712-3-fr-2020.00094.
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.
Pudar, R. S., and J. A. Liggett. 1992. “Leaks in pipe networks.” J. Hydraul. Eng. 118 (7): 1031–1046. https://doi.org/10.1061/(ASCE)0733-9429(1992)118:7(1031).
Sarrate, R., J. Blesa, F. Nejjari, and J. Quevedo. 2014. “Sensor placement for leak detection and location in water distribution networks.” Water Supply 14 (5): 795–803. https://doi.org/10.2166/ws.2014.037.
Simone, A., O. Giustolisi, and D. B. Laucelli. 2016. “A proposal of optimal sampling design using a modularity strategy.” Water Resour. Res. 52 (8): 6171–6185. https://doi.org/10.1002/2016WR018944.
Sousa, J., L. Ribeiro, J. Muranho, and A. S. Marques. 2015. “Locating leaks in water distribution networks with simulated annealing and graph theory.” Procedia Eng. 119 (1): 63–71. https://doi.org/10.1016/j.proeng.2015.08.854.
Sun, J., and R. Wang. 2016. “Sensors layout optimization based on cluster analysis in water supply network.” In Proc., 2016 3rd Int. Conf. on Engineering Technology and Application (ICETA), 1011–1015. Lancaster, PA: DEStech Publications. https://doi.org/10.12783/dtetr/iceta2016/7125.
Xi, J., J. Gao, and W. Wu. 2008. “Optimal placement of pressure monitors in water supply network with elitist genetic algorithm.” Int. J. Model. Identif. Control 4 (2): 168–175. https://doi.org/10.1504/IJMIC.2008.021094.
Information & Authors
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Published In
Journal of Water Resources Planning and Management
Volume 146 • Issue 11 • November 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Jun 8, 2019
Accepted: Jun 19, 2020
Published online: Sep 11, 2020
Published in print: Nov 1, 2020
Discussion open until: Feb 11, 2021
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