ID:
publications-4600
Type:
article
Year:
2014
Authors:
Romano, Michele and Romano, Michele and Kapelan, Zoran and Kapelan, Zoran and Savić, Dragan and Savic, Dragan
Title:
Automated Detection of Pipe Bursts and Other Events in Water Distribution Systems
Venue/Journal:
Journal of Water Resources Planning and Management
DOI:
10.1061/(asce)wr.1943-5452.0000339
Research type:
Water System:
Technical Focus:
Abstract:
AbstractThis paper presents a new methodology for the automated near-real-time detection of pipe bursts and other events that induce similar abnormal pressure/flow variations (e.g.,unauthorized consumptions) at the district metered area (DMA) level. The new methodology makes synergistic use of several self-learning artificial intelligence (AI) techniques and statistical data analysis tools, including wavelets for denoising of the recorded pressure/flow signals, artificial neural networks (ANNs) for the short-term forecasting of pressure/flow signal values, statistical process control (SPC) techniques for short- and long-term analysis of the pipe burst/other event-induced pressure/flow variations, and Bayesian inference systems (BISs) for inferring the probability of a pipe burst/other event occurrence and raising corresponding detection alarms. The methodology presented here is tested and verified on a case study involving several DMAs in the United Kingdom (U.K.) with both real-life pipe burst/other eve...
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