An optimization of heuristic model of water supply network
Abstract
In the paper an intelligent monitoring system of local water supply system is described. The main task of this system concerns water leakages detecting. For inputs, this system uses information from few pressure or flow sensors, mounted on the pipeline network, the output is a piece of information about leakage detection and localization. A heuristic model of water supply network makes the main part of intelligent diagnostic system. The model was built with the use of artificial neural networks. This paper presents the structure and optimization of a heuristic model. The authors took advantage of methods of artificial intelligence and methods known from model-based process diagnostics to increase the accuracy with which system detects of water leakages.
Keywords
water supply systems, diagnostics, genetics algorithm, artificial neural network,References
[1] A. Borowa, K. Mazur, M. Grochowski, M.A. Brdyś, K. Jezior. MultiRegional PCA for leakage detection and localization I DWDS - approach. In: Fault Diagnosis and Fault Tolerant Control. EXIT, Warsaw, 2007.[2] W. Cholewa, J. Kaźmierczak. Data Processing and Reasoning in Technical Diagnostics. WNT, Warsaw, 1995.
[3] D.E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading, 1989.
[4] http://www.epa.gov/ORD/NRMRL/wswrd/epanet.html
[5] J . Holnicki-Szulc, P. Kołakowski, N. Nasher. Identification of leakages in water networks - Virtual distortion method approach. Proc. of the 5th World Congress of Structural and Multidisciplinary Optimization, May 19- 23, 2003, Lido di Jesolo, Italy; http://smart.ippt.gov.pl/pdf/paper 2003_JH_PK_NN .pdf.
