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ADAPTIVE WATER SENSOR SIGNAL PROCESSING: EXPERIMENTAL RESULTS AND IMPLICATIONS FOR ONLINE CONTAMINANT WARNING SYSTEMS
Citation:
YANG, Y. J., R. HAUGHT, J. HALL, J. G. SZABO, R. M. CLARK, AND G. MEINERS. ADAPTIVE WATER SENSOR SIGNAL PROCESSING: EXPERIMENTAL RESULTS AND IMPLICATIONS FOR ONLINE CONTAMINANT WARNING SYSTEMS. In Proceedings, ASCE 2007 World Environment and Water Resources Congress, Tampa, FL, May 15 - 19, 2007. American Society of Civil Engineers (ASCE), Reston, VA, ISBN 10:0784409277, (2007).
Impact/Purpose:
present information
Description:
A contaminant detection technique and its optimization algorithms have two principal functions. One is the adaptive signal treatment that suppresses background noise and enhances contaminant signals, leading to a promising detection of water quality changes at a false rate as low as 3-5%. The second function is forensic classification that relates a matrix of water quality parameter changes to the reactivity of contaminants in chlorinated drinking water. To test the method capability, the adaptive procedures were used to analyze a composite time-series output from conventional water quality sensors (free and total chlorine, chloride, pH, DO, conductivity, ORP, and turbidity) in experiments of a pilot-scale single pass water pipe for the 16 herbicide, pesticides, inorganic and biological contaminants. Based on the results, the unique water quality parameter changes and clear chlorine reactivity differences were identified which can be used to establish an effective contaminant detection program.
URLs/Downloads:
ADAPTIVE WATER SENSOR SIGNAL PROCESSING: EXPERIMENTAL RESULTS AND IMPLICATIONS FOR ONLINE CONTAMINANT WARNING SYSTEMS
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