Successive Linear Approximation Methods for Leak Detection in Water Distribution Systems
Publication: Journal of Water Resources Planning and Management
Volume 143, Issue 8
Abstract
In many modern water networks, an emerging trend is to measure pressure at various points in the network for operational reasons. Because leaks typically induce a signature on pressure, these routine measurements can be used to develop nonintrusive leak detection approaches. This research employs successive linear approximation methods, based on linear programming and mixed integer linear programming, in a simulation-optimization framework to explore an alternative leak detection methodology for urban water distribution networks based on pressure measurements. The methods attempt to minimize the absolute differences between observed and simulated pressure values at the sensors to determine a linear combination of leaks that most closely approximates the observed pressure pattern. Steady-state and time-varying models of differing complexity (from small published networks to a 27,000-node network for a U.S. utility) were used to test the method. Results are presented to illustrate the method’s effectiveness under different conditions. The methods are shown to work well when pervasive pressure data and hydraulic models representing true operational conditions are available. The methods developed in this work are not intended to replace traditional leak detection methods; rather, they are meant to work in concert with available methods to more accurately and efficiently isolate leak locations and reduce water loss.
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Acknowledgments
This research was supported in part by the Department of Civil, Construction, and Environmental Engineering at North Carolina State University and by the National Science Foundation under Grant No. 1100458. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of North Carolina State University or the National Science Foundation.
References
Areti, S., Berglund, A., Patskoski, J., Ranjithan, R., Brill, D., and Mahinthakumar, G. (2016). “Leakage detection in water distribution systems using iterative mathematical programming methods.” 2016 World Environmental and Water Resources Congress, ASCE, Reston, VA.
AWWA (American Water Works Association). (2012). Water loss control: Water loss control terms defined, Denver.
Berglund, A. (2013). “An iterative simulation and mathematical programming optimization approach to leak detection in water distribution systems.” Master’s thesis, North Carolina State Univ., Raleigh, NC.
De Paola, F., Fontana, N., Galdiero, E., Giugni, M., Uberti, S., and Vitaletti, M. (2014). “Optimal design of district metered areas in water distribution networks.” 12th Int. Conf. on Computing and Control for the Water Industry, CCWI2013, Vol. 70, Elsevier, Amsterdam, Netherlands, 449–457.
Giustolisi, O., Savic, D., and Kapelan, Z. (2008). “Pressure-driven demand and leakage simulation for water distribution networks.” J. Hydraul. Eng., 626–635.
Giustolisi, O., and Walski, T. (2012). “Demand components in water distribution network analysis.” J. Water Resour. Plann. Manage., 356–367.
Gong, J., Simpson, A. R., and Lambert, M. F. (2013). “Detection of distributed deterioration in single pipes using transient reflections.” J. Pipeline Syst. Eng. Pract., 32–40.
Gurobi Optimizer version 6.0 [Computer software]. Gurobi Optimization, Inc., Houston.
Hamilton, S., and Charalambous, B. (2013). Leak detection: Technology and implementation, IWA Publishing, London, 98.
MATLAB [Computer software]. MathWorks, Natick, MA.
Meseguer, J., et al. (2014). “A decision support system for on-line leakage localization.” Environ. Modell. Software, 60, 331–345.
Pérez, R., Puig, V., Pascual, J., and Peralta, A. (2011). “Methodology for leakage isolation using pressure sensitivity analysis in water distribution networks.” Control Eng. Practice, 19(10), 1157–1167.
Ponce, M. V. C., Castanon, L. E. G., and Cayuela, V. P. (2014). “Model-based leak detection and location in water distribution networks considering an extended-horizon analysis of pressure sensitivities.” J. Hydroinf., 16(3), 649–670.
Poulakis, Z., Valougeorgis, D., and Papadimitriou, C. (2003). “Leakage detection in water pipe networks using a Bayesian probabilistic framework.” Probab. Eng. Mech., 18(2003), 315–327.
Puust, R., Kapelan, Z., Savic, D. A., and Koppel, T. (2010). “A review of methods for leakage management in pipe networks.” Urban Water J., 7(1), 25–45.
Puust, R. E., Kapelan, Z., Savic, D. A., and Koppel, T. (2006). “Probabilistic leak detection in pipe networks using the SCEN-UA algorithm.” 8th Annual Water Distribution Systems Analysis Symp., ASCE, Reston, VA.
Rossman, L. (2000). EPANET 2 user’s manual, National Risk Management Research Laboratory Office of Research and Development, U.S. Environmental Protection Agency, Cincinnati.
Sala, D., and Kołakowski, P. (2014). “Detection of leaks in a small-scale water distribution network based on pressure data—Experimental verification.” Procedia Eng., 70, 1460–1469.
Savic, D. (1997). “Genetic algorithms for least-cost design of water distribution networks.” J. Water Resour. Plann. Manage., 67–77.
Soares, A. K., Covas, D. I. C., and Reis, L. F. R. (2011). “Leak detection by inverse transient analysis in an experimental PVC pipe system.” J. Hydroinf., 13(2), 153–166.
Sophocleous, S., Savic, D., Kapelan, Z., Shen, Y., and Sage, P. (2015). “Advances in water mains network modelling for improved operations.” Procedia Eng., 119, 593–602.
Sreepathi, S., and Mahinthakumar, G. (2012). “Optimus: A parallel optimization framework with topology aware PSO and applications.” 2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC), IEEE, New York, 1524–1525.
Todini, E. (2003). “A more realistic approach to the extended period simulation of water distribution networks.” Advances in water supply management, A. A. Balkema, Lisse, Netherlands, 173–184.
Van Zyl, J. E., and Cassa, A. M. (2014). “Modeling elastically deforming leaks in water distribution pipes.” J. Hydraul. Eng., 182–189.
Wu, Z. Y., et al. (2008). “Leak detection case study by means of optimizing emitter locations and flow.” Proc., 10th Annual Water Distribution Systems Analysis Conf., ASCE, Reston, VA.
Wu, Z. Y. (2009). “Unified parameter optimization approach for leakage detection and extended-period simulation model calibration.” Urban Water J., 6(1), 53–67.
Wu, Z. Y., Sage, P., and Turtle, D. (2010). “Pressure-dependent leak detection model and its application to a district water system.” J. Water Resour. Plann. Manage., 116–128.
Wu, Z. Y., Wang, R. H., Walski, T. M., Yang, S. Y., Bowdler, D., and Baggett, C. C. (2009). “Extended global-gradient algorithm for pressure-dependent water distribution analysis.” J. Water Resour. Plan. Manage., 13–22.
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©2017 American Society of Civil Engineers.
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Received: Jun 1, 2016
Accepted: Jan 30, 2017
Published online: Jun 5, 2017
Published in print: Aug 1, 2017
Discussion open until: Nov 5, 2017
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