ID:
publications-4156
Type:
article
Year:
2012
Authors:
Murray, S. and Murray, Steven and Ghazali, Mirnader and Ghazali, Mirnader and McBean, Edward A. and McBean, Edward A.
Title:
Real-Time Water Quality Monitoring: Assessment of Multisensor Data Using Bayesian Belief Networks
Venue/Journal:
Journal of Water Resources Planning and Management
DOI:
10.1061/(asce)wr.1943-5452.0000163
Research type:
Water System:
Technical Focus:
Abstract:
Real-time sensing in water distribution systems provides a potentially powerful analytical tool for providing water security. Through monitoring surrogate parameters (e.g., pH, turbidity, and residual chlorine) over time, the natural variations of a distribution system’s parameters are established, allowing rapid detection of changes in water quality. However, the level of performance that water quality event detection algorithms have exhibited to date is insufficient for real-world utilization. Bayesian belief networks (BBNs) offer a formalized method of reasoning under uncertainty and are well suited to the analysis of multiple sources of information. The application of a BBN to water quality event detection is described. Surrogate parameters (pH, conductivity, and turbidity) were monitored during an experimental E. coli contamination. Difference filtration using a 60-s moving window of observations identified rapid rates of change present in the surrogate parameter signals, demonstrated as responsive t...
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