Dr. Yingping Jeffrey Yang Profile

Dr. Yingping Jeffrey Yang

Environmental Scientist at USEPA

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Proceedings Article | 9 May 2006 Paper

Adaptive monitoring to enhance water sensor capabilities for chemical and biological contaminant detection in drinking water systems

Y. Jeffrey Yang, Roy Haught, John Hall, James Goodrich, Jafrul Hasan

Proceedings Volume 6203, 62030K (2006) https://doi.org/10.1117/12.665358

KEYWORDS: Sensors, Water, Chlorine, Biosensors, Biological detection systems, Signal detection, Data analysis, Chemical analysis, Computer simulations, Interference (communication)

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Optoelectronic and other conventional water quality sensors offer a potential for real-time online detection of chemical and biological contaminants in a drinking water supply and distribution system. The nature of the application requires sensors of detection capabilities at low contaminant concentrations, for continuous data acquisition and management, and with reduced background noise and low false detection rates for a wide spectrum of contaminants. To meet these application requirements, feasibilities of software-based methods were examined and a novel technique was developed using adaptive monitoring and contaminant detection methodologies. This new monitoring and early detection framework relies on the local adaptive and network adaptive sensors in order to reduce background noise interference and enhance contaminant peak identifications. After "noise" reduction, the sensor measurements can be assembled and analyzed for temporal, spatial and inter-parameter relationships. Further detection reliability improvement is accomplished through signal interpretation in term of chemical signatures and in consideration of contaminant fate and transport in pipe flows. Based on this integrated adaptive approach, a data statistical compression technique can be used to process and reduce the sensor onboard data for background variations, which frequently represent a bulk of inflowing data stream. The adaptive principles and methodology were examined using a pilot-scale distribution simulator at the U.S. EPA Test & Evaluation facility. Preliminary results indicate the research and development activities on adaptive monitoring may lead to the emergence of a practical drinking water online detection system.

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