Journal
WATER RESEARCH
Volume 101, Issue -, Pages 75-83Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.watres.2016.05.068
Keywords
Fault detection; Mass balancing; Multi-objective optimization; Redundancy; Sensor placement; Wastewater treatment
Funding
- Peter Vanrolleghem's Discovery Grant - NSERC (Natural Sciences and Engineering Research Council of Canada)
- Ramon and Cajal grant [RYC-2013-14595]
- Marie Curie Career Integration Grant [PCIG9-GA-2011-293535]
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Obtaining high quality data collected on wastewater treatment plants is gaining increasing attention in the wastewater engineering literature. Typical studies focus on recognition of faulty data with a given set of installed sensors on a wastewater treatment plant. Little attention is however given to how one can install sensors in such a way that fault detection and identification can be improved. In this work, we develop a method to obtain Pareto optimal sensor layouts in terms of cost, observability, and redundancy. Most importantly, the resulting method allows reducing the large set of possibilities to a minimal set of sensor layouts efficiently for any wastewater treatment plant on the basis of structural criteria only, with limited sensor information, and without prior data collection. In addition, the developed optimization scheme is fast. Practically important is that the number of sensors needed for both observability of all flows and redundancy of all flow sensors is only one more compared to the number of sensors needed for observability of all flows in the studied wastewater treatment plant configurations. (C) 2016 Elsevier Ltd. All rights reserved.
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