Implementation of an on-line artificial intelligence district meter area flow meter data analysis system for abnormality detection: A case study

Water Science and Technology: Water Supply

Volumn 10, Issue 3, 2010, Pages 437-444

  Mounce, S R ^a   Boxall, J B ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

Artificial neural networks; Data analysis; Leakage; On line monitoring; Water distribution systems

Indexed keywords

APPLICATION PROGRAMS; ARTIFICIAL INTELLIGENCE; COMPUTER SOFTWARE; DATA HANDLING; DATA REDUCTION; DATA WAREHOUSES; EMERGENCY TRAFFIC CONTROL; INFORMATION ANALYSIS; LEAKAGE (FLUID); MATLAB; NEURAL NETWORKS; RADIO COMMUNICATION; SALES; WATER DISTRIBUTION SYSTEMS; WATER SUPPLY SYSTEMS; WATERWORKS;

ABNORMALITY DETECTION; ARTIFICIAL INTELLIGENCE SYSTEMS; COMMUNICATIONS SOFTWARE; DATA ANALYSIS SYSTEM; GENERAL PACKET RADIO SERVICE; OFF-LINE APPLICATIONS; ONLINE MONITORING; REAL TIME DATA COLLECTIONS;

DEEP NEURAL NETWORKS;

ABNORMALITY; ARTIFICIAL INTELLIGENCE; DATA ASSIMILATION; DISTRIBUTION SYSTEM; FIELD SURVEY; MASS BALANCE; REAL TIME; SOFTWARE;

ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; COMPUTER PROGRAM; DATA ANALYSIS; DECISION SUPPORT SYSTEM; FLOWMETER; ONLINE MONITORING; WATER SUPPLY;

EID: 79951744060     PISSN: 16069749     EISSN: None     Source Type: Journal    
DOI: 10.2166/ws.2010.697     Document Type: Article

References (15)

1. Bicik, J., Kapelan, Z. & Savic, D. A. 2009 Operational Perspective of the Impact of Failures in Water Distribution Systems, Proceedings of the World Environmental & Water Resources Congress 2009 (WDSA 2009).
2. Covas, D., Jacob, A. & Ramos, H. 2008 Water losses assessment in an urban water network. Water Pract. Technol. 3(3), http://www.iwaponline.com/wpt/ 003/0061/0030061.pdf (accessed 14 September 2009).
3. Farley, M. & Hamilton, S. 2008 Non-intrusive leak detection in large diameter, low-pressure non-metallic pipes: are we close to finding the perfect solution? Proceedings of the IWA World Water Congress, September 7-12, Vienna, Austria.
4. Fayyad, U. M., Piatetsky-Shapiro, G. & Smyth, P. 1996 From data mining to knowledge discovery: an overview. In Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P. & Uthurusamy, R. (eds) Advances in Knowledge Discovery and Data Mining. AAAI Press/The MIT Press, pp. 495-515.
5. Hulme, M., Jenkins, G. J., Lu, X., Turnpenny, J. R., Mitchell, T. D., Jones, R. G., Lowe, J., Murphy, J. M., Hassell, D., Boorman, P., McDonald, R., & Hill, S. 2002 Climate Change Scenarios for the United Kingdom: The UKCIP02 Scientific Report, Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, Norwich, UK. p. 120.
6. Jankovic-Nisic, B., Maksimovic, C., Butler, D. & Graham, N. 2004 Use of flow meters for managing water supply networks. J. Water Resour. Plann. Manage. 130, 171-179.
7. McKenzie, R. & Seago, C. 2005 Assessment of real losses in potable water distribution systems: some recent developments. Wat. Sci. Technol.: Water Supply 5(1), 33-40. (Pubitemid 40570594)
8. Mounce, S. R., Day, A. J., Wood, A. S., Khan, A., Widdop, P. D. & Machell, J. 2002 A neural network approach to burst detection. Water Sci. Technol. 45(4-5), 237-246.
9. Mounce, S. R., Khan, A., Wood, A. S., Day, A. J., Widdop, P. D. & Machell, J. 2003 Sensor-fusion of hydraulic data for burst detection and location in a treated water distribution system. Int. J. Inf. Fusion 4(3), 217-229.
10. Mounce, S. R., Machell, J. & Boxall, J. 2006 Development Of Artificial Intelligence Systems For Analysis Of Water Supply System Data. Proceedings of the 8th Water Distribution System Analysis Symposium, August 27-30, Cincinnati, USA.
11. Mounce, S. R., Boxall, J. B. & Machell, J. 2007 An artificial neural network/fuzzy logic system for DMA flow meter data analysis providing burst identification and size estimation. In Ulanicki, B., et al. (ed.) Water Management Challenges in Global Change. Taylor and Francis, pp. 313-320, ISBN 978-0-415-45415-5.
12. Mounce, S. R., Boxall, J. B. & Machell, J. 2010 Development and Verification of an Online Artificial Intelligence System for Burst Detection in Water Distribution Systems. ASCE Water Resour. Plann. Manage. 309, 309-318.
13. Nabney, I. 2001 NETLAB: Algorithms for Pattern Recognition. Springer-Verlag, UK.
14. Olsson, G. 2006 Instrumentation, control and automation in the water industry - state-of-the-art and new challenges. Water Sci. Technol. 53(4-5), 1-16.
15. UNEP 2007 Fourth Global Environment Outlook: environment for development assessment report, United Nations Environment Programme, Nairobi (Kenya), ISBN 978-92-807-2836-1.