title: Real-time detection of organic contamination events in water distribution systems by principal components analysis of ultraviolet spectral data.
abstract: The detection of organic contaminants in water distribution systems is essential to protect public health from potential harmful compounds resulting from accidental spills or intentional releases. Existing methods for detecting organic contaminants are based on quantitative analyses such as chemical testing and gas/liquid chromatography, which are time- and reagent-consuming and involve costly maintenance. This study proposes a novel procedure based on discrete wavelet transform and principal component analysis for detecting organic contamination events from ultraviolet spectral data. Firstly, the spectrum of each observation is transformed using discrete wavelet with a coiflet mother wavelet to capture the abrupt change along the wavelength. Principal component analysis is then employed to approximate the spectra based on capture and fusion features. The significant value of Hotelling's T2statistics is calculated and used to detect outliers. An alarm of contamination event is triggered by sequential Bayesian analysis when the outliers appear continuously in several observations. The effectiveness of the proposed procedure is tested on-line using a pilot-scale setup and experimental data.
authors.affiliation: State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Zhang
authors.affiliation: State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China. houdb@zju.edu.cn.
authors.forename: Dibo
authors.initials: D
authors.lastname: Hou
authors.affiliation: State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
authors.forename: Ke
authors.initials: K
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
authors.forename: Pingjie
authors.initials: P
authors.lastname: Huang
authors.affiliation: State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
authors.forename: Guangxin
authors.initials: G
authors.lastname: Zhang
authors.affiliation: Department of Geography/UCSB, Santa Barbara, CA, 93106, USA.
authors.forename: Hugo
authors.initials: H
authors.lastname: Loáiciga
mesh_terms: D001499:Bayes Theorem; D004784:Environmental Monitoring; D014867:Water; D060753:Water Quality; D014881:Water Supply
chemical_list: D014867:Water
keywords: anomaly detection; organic contamination; ultraviolet spectra; water distribution system