ID:
publications-4538
Type:
article
Year:
2010
Authors:
Mounce, S. R. and Mounce, Stephen R. and Boxall, Joby and Boxall, Joby and Machell, John and Machell, John
Title:
Development and Verification of an Online Artificial Intelligence System for Detection of Bursts and Other Abnormal Flows
Venue/Journal:
Journal of Water Resources Planning and Management
DOI:
10.1061/(asce)wr.1943-5452.0000030
Research type:
Water System:
Technical Focus:
Abstract:
Water lost through leakage from water distribution networks is often appreciable. As pressure increases on water resources, there is a growing emphasis for water service providers to minimize this loss. The objective of the work presented in this paper was to assess the online application and resulting benefits of an artificial intelligence system for detection of leaks/bursts at district meter area (DMA) level. An artificial neural network model, a mixture density network, was trained using a continually updated historic database that constructed a probability density model of the future flow profile. A fuzzy inference system was used for classification; it compared latest observed flow values with predicted flows over time windows such that in the event of abnormal flow conditions alerts are generated. From the probability density functions of predicted flows, the fuzzy inference system provides confidence intervals associated with each detection, these confidence values provide useful information for f...
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