Pipe burst diagnostics using evidence theory

Journal of Hydroinformatics

Volumn 13, Issue 4, 2011, Pages 596-608

  Bicik, Josef ^a   Kapelan, Zoran ^a   Makropoulos, Christos ^b   Drasavić, Gan A ^a  

^a UNIVERSITY OF EXETER   (United Kingdom)

^b NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

Author keywords

Decision support; Diagnostics; Evidence theory; Pipe burst; Water Distribution System

Indexed keywords

EID: 80054977425     PISSN: 14647141     EISSN: None     Source Type: Journal    
DOI: 10.2166/hydro.2010.201     Document Type: Article

References (37)

1. Andersen, J. H. & Powell, R. S. 2000 Implicit state-estimation technique for water network monitoring. Urban Wat. 2(2), 123-130.
2. Bai, H., Sadiq, R., Najjaran, H. & Rajani, B. 2008 Condition assessment of buried pipes using hierarchical evidential reasoning model. J. Comput. Civil Engng. 22(2), 114-122. (Pubitemid 351264009)
3. Bayes, T. 1763 An essay towards solving a problem in the doctrine of chances. Phil. Trans. R. Soc. 53, 370-418.
4. Berardi, L., Kapelan, Z., Giustolisi, O. & Savic, D. A. 2008 Development of pipe deterioration models for water distribution systems using EPR. J. Hydroinf. 10(2), 113-126.
5. Beynon, M. J. 2005 A novel technique of object ranking and classification under ignorance: an application to the corporate failure risk problem. Eur. J. Oper. Res. 167(2), 493-517. (Pubitemid 40219993)
6. Bi, Y., Guan, J. & Bell, D. 2008 The combination of multiple classifiers using an evidential reasoning approach. Artif. Intell. 172(15), 1731-1751.
7. Brunone, B. 1999 Transient test based technique for leak detection in outfall pipes. J. Wat. Res. Plann. Mngmnt. 125(5), 302-306.
8. Bush, C. A. & Uber, J. G. 1998 Sampling design methods for water distribution model calibration. J. Wat. Res. Plann. Mngmnt. 124(6), 334-344. (Pubitemid 29038883)
9. Colombo, A. F. & Karney, B. W. 2002 Energy and costs of leaky pipes: toward a comprehensive picture. J. Wat. Res. Plann. Mngmnt. 128(6), 441-450. (Pubitemid 35307664)
10. Colombo, A. F., Lee, P. & Karney, B. W. 2009 A selective literature review of transient-based leak detection methods. J. Hydroenviron. Res. 2(4), 212-227.
11. Cooper, N. R., Blakey, G., Sherwin, C., Ta, T., Whiter, J. T. & Woodward, C. A. 2000 The use of GIS to develop a probability-based trunk mains burst risk model. Urban Wat. 2(2), 97-103.
12. Démotier, S., Denœux, T. & Schön, W. 2003 Risk assessment in drinking water production using belief functions. In: Symbolic and Quantitative Approaches to Reasoning with Uncertainty (T. D., Nielsen, N. L., Zhang (Eds.)) pp. 319-331. Springer, Berlin. (Pubitemid 36904915)
13. Dempster, A. P. 1967 Upper and lower probabilities induced by a multivalued mapping. Annal. Math. Statist. 38(2), 325-339.
14. Kapelan, Z., Savic, D. A. & Walters, G. A. 2003a A hybrid inverse transient model for leakage detection and roughness calibration in pipe networks. J. Hydraul. Res. 41(5), 481-492. (Pubitemid 37293365)
15. Kapelan, Z., Savic, D. A. & Walters, G. A. 2003b Multiobjective sampling design for water distribution model calibration. J. Wat. Res. Plann. Mngmnt. 129(6), 466-479. (Pubitemid 37450406)
16. Kleiner, Y. & Rajani, B. 2001 Comprehensive review of structural deterioration of water mains: statistical models. Urban Wat. 3(3), 131-150. (Pubitemid 33066191)
17. Li, H. 2007 Hierarchical Risk Assessment of Water Supply Systems. PhD thesis, Loughborough University, Loughborough, Leicestershire.
18. Marashi, S. E., Davis, J. P. & Hall, J. W. 2008 Combination methods and conflict handling in evidential theories. Int. J. Uncertainty Fuzziness Knowledge-Based Syst. 16(3), 337-369.
19. Misiunas, D., Vítkovský, J., Olsson, G., Lambert, M. & Simpson, A. 2006 Failure monitoring in water distribution networks. Wat. Sci. Technol. 53(4-5), 503-511 (Pubitemid 43744635)
20. Mounce, S. R., Boxall, J. B. & Machell, J. 2010 Development and verification of an online artificial intelligence system for detection of bursts and other abnormal flows. J. Wat. Res. Plann. Mngmnt. 136(3), 309-318.
21. Mounce, S. R. & Machell, J. 2006 Burst detection using hydraulic data from water distribution systems with artificial neural networks. Urban Wat. J. 3(1), 21-31.
22. Poulakis, Z., Valougeorgis, D. & Papadimitriou, C. 2003 Leakage detection in water pipe networks using a Bayesian probabilistic framework. Probab. Engng. Mech. 18(4), 315-327.
23. Puust, R., Kapelan, Z., Savic, D. A. & Koppel, T. 2010 A review of methods for leakage management in pipe networks. Urban Wat. J. 7(1), 25-45.
24. Romano, M., Kapelan, Z. & Savic, D. A. 2009 Bayesian-based online burst detection in water distribution systems. In: Proc. 10th International Conference on Computing and Control for the Water Industry, CCWI 2009 "Integrating Water Systems", Sheffield, UK (eds J. Boxall and C. Maksimović) pp. 331-337. CRC Press, Florida.
25. Rossman, L. A. 2000 EPANET 2 Users Manual. US Environmental Protection Agency, Cincinnati, OH
26. Sadiq, R., Kleiner, Y. & Rajani, B. 2006 Estimating risk of contaminant intrusion in water distribution networks using Dempster-Shafer theory of evidence. Civil Engng. Environ. Syst. 23(3), 129-141. (Pubitemid 44111580)
27. Sadiq, R. & Rodriguez, M. J. 2005 Interpreting drinking water quality in the distribution system using Dempster-Shafer theory of evidence. Chemosphere 59(2), 177-188. (Pubitemid 40255659)
28. Safranek, R. J., Gottschlich, S. & Kak, A. C. 1990 Evidence accumulation using binary frames of discernment for verification vision. IEEE Trans. Robotics Automation 6(4), 405-417.
29. Sentz, K. & Ferson, S. 2002 Combination of Evidence in Dempster-Shafer Theory. SAND 2002-0835, Sandia National Laboratories, Albuquerque, NM.
30. Shafer, G. A. 1976 A Mathematical Theory of Evidence. Princeton University Press, Princeton, NJ.
31. Shannon, C. E. 1948 A mathematical theory of communications, I and II. Bell Syst. Tech. J. 27, 379-423.
32. Smarandache, F. & Dezert, J. 2006 Advances and Applications of DSmT for Information Fusion II (Collected Works). American Research Press Rehoboth, NM.
33. Smets, P. & Kennes, R. 1994 The transferable belief model. Artif. Intell. 66(2), 191-234.
34. Wang, Y., Zayed, T. & Moselhi, O. 2009 Prediction models for annual break rates of water mains. J. Perf. Constr. Facil. 23(1), 47-54.
35. Wu, Z. Y., Sage, P. & Turtle, D. 2010 Pressure-dependent leak detection model and its application to a district water system. J. Wat. Res. Plann. Mngmnt. 136(1), 116-128.
36. Yager, R. R. 1987 On the Dempster-Shafer framework and new combination rules. Inf. Sci. 41(2), 93-137
37. Yager, R. R. 2004 On the determination of strength of belief for decision support under uncertainty - Part II: Fusing strengths of belief. Fuzzy Sets Syst. 142(1), 129-142.