Pipe network leak detection: comparison between statistical and machine learning techniques

References

• Asgari, H. R., and M. F. Maghrebi. 2016. “Application of Nodal Pressure Measurements in Leak Detection.” Flow Measurement and Instrumentation 50 (June): 128–134. doi:10.1016/j.flowmeasinst.2016.06.009.
   Web of Science ®Google Scholar
• Caputo, A. C., and P. M. Pelagagge. 2003. “Using Neural Networks to Monitor Piping Systems.” Process Safety Progress 22 (2, June): 119–127. doi:10.1002/(ISSN)1547-5913.
   Web of Science ®Google Scholar
• Casillas, M. V., V. Puig, L. E. Garza-Castanon, and A. Rosich. 2013. “Optimal Sensor Placement for Leak Location in Water Distribuion Networks Using Genetic Algorithms.” In Conference on Control and Fault-Tolerant Systems, Nice France, 61–66. June.
   Google Scholar
• de Schaentzen, W. B. F., G. A. Walters, and D. A. Savic. 2000. “Optimal Sampling Desing for Model Calibraion Using Shortest Path, Genetic and Entropy Algorithms.” Urban Water. 2 (June): 114–152.
   Google Scholar
• De Silva, D., J. Mashford, and S. Burn. 2011. Computer aided leak location and sizing in pipe networks. Technical Report 17. Urban Water Security Research Alliance. April.
   Google Scholar
• Fuchs-Hanusch, D., and D. Steffelbauer. 2017. “Real-World Comparison of Sensor Placement Algorithms for Leakage Localization.” In XVIII International Conference on Water Distribuion Systems Analysis, Cartagena Colombia, 499–505.
   Google Scholar
• Mckenzie, R., Z. N. Siqalaba, and W. A. Wegelin. 2012. The State of Non-Revenue Water in South Africa. Technical Report. Water Research Commission. August.
   Google Scholar
• Mounce, S. R., and J. Machell. 2007. “Burst Detection Using Hydraulic Data from Water Distribution Systems with Artificial Neural Networks.” Urban Water Journal 3 (1, February): 21–31. doi:10.1080/15730620600578538.
   Web of Science ®Google Scholar
• Nasirian, A., M. F. Maghrebi, and S. Yazdani. 2013. “Leakage Detection in Water Distribution Network Based on a New Heuristic Genetic Algorithm Model.” Journal of Water Resource and Protection 5 (March): 294–303. doi:10.4236/jwarp.2013.53030.
   Google Scholar
• Nowicki, A., M. Grochowiski, and K. Dusinkiewichz. 2026. “Data-Driven Models for Fault Detection Using Kernal Pca: A Water Distribution System Case Study.” Applied Mathematics and Computer Science 22: 939–949.
   Google Scholar
• Pedregosa, F., G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, et al. 2011. “Scikit-Learn: Machine Learning in Python.” Journal of Machine Learning Research 12: 2825–2830.
   Web of Science ®Google Scholar
• Perez, R., J. Quevedo, V. Puig, F. Nejjari, M. A. Cuguero, G. Sanz, and J. M. Mirats. 2011. “Leakage Isolation in Water Distribuion Networks: A Comparative Study of Thwo Methodologies on a Real Case Study.” In 19th Mediteranean Conference on Control Automation, Corfu Greece, 138–143.
   Google Scholar
• Perez, R., G. Sanz, V. Puig, J. Quevendo, M. A. Cugeuro Escofet, F. Nejjari, J. Meseguer, G. Cembrano, J. M. Mirats Tur, and R. Serrate. 2014. “A Model-Based Methodology Using Pressure Sensors Applied to A Real Network in Barcelona.” In IEEE Control Systems Magazine, 24–36. August.
   Google Scholar
• Poulakis, Z., D. Valougeorgis, and C. Papadimitriou. 2003. “Leakage Detection in Water Pipe Networks Using a Bayesian Probabilistic Framework.” Probabilistic Engineering Mechanics 18 (4, July): 315–327. doi:10.1016/S0266-8920(03)00045-6.
   Web of Science ®Google Scholar
• Romano, M., Z. Kapelan, and D. A. Savić. 2013. “Geostatistical Techniques for Approximate Location of Pipe Burst Events in Water Distribution Systems.” Journal of Hydroinformatics 15 (3): 634–651. doi:10.2166/hydro.2013.094.
   Web of Science ®Google Scholar
• Salam, A. E. U., M. Tola, M. Selintung, and F. Maricar. 2014. “On-Line Monitoring System of Water Leakgage Detection in Pipe Networs with Artificial Intelligence.” ARPN Journal of Engineering and Applied Science 9 (10, October): 1817–1822.
   Google Scholar
• Soldevila, A., R. M. Fernandez-Canti, J. Blesa, S. Tornil-Sin, and V. Puig. 2016. “Leak Localization in Water Distribution Networks Using Model-Based Bayesian Reasoning.” In European Control Conference, Aalborg Denmark, 1758–1763. June.
   Google Scholar
• Soldevila, A., R. M. Fernandez-Canti, J. Blesa, S. Tornil-Sin, and V. Puig. 2017. “Leak Localization in Water Distribution Networks Using Bayesian Classifiers.” Journal of Process Control 55 (April): 1–9. doi:10.1016/j.jprocont.2017.03.015.
   Web of Science ®Google Scholar
• Steffelbauer, D., M. Neumayer, M. Günther, and D. Fuchs-Hanusch. 2014. “Sensor Placement and Leakage Localization considering Demand Uncertainties.” Procedia Engineering 89: 1160–1167. doi:10.1016/j.proeng.2014.11.242.
   Google Scholar