2013
DOI: 10.1016/j.watres.2013.01.017
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A dynamic thresholds scheme for contaminant event detection in water distribution systems

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Cited by 100 publications
(44 citation statements)
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“…The second approach to event detection is based on signal processing and data driven techniques [10,[15][16][17][18][19][20]. For example, Hart et al [15] reported a linear prediction filter (LPF).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…The second approach to event detection is based on signal processing and data driven techniques [10,[15][16][17][18][19][20]. For example, Hart et al [15] reported a linear prediction filter (LPF).…”
Section: Introductionmentioning
confidence: 99%
“…Allgeier et al [17] and Raciti et al [18] utilized artificial neural networks (ANN) and support vector machines (SVM) to classify water quality data into normal and anomalous classes after supervised learning training. Perelman et al [19] and Arad et al [20] reported a general framework that integrates a data-driven estimation model with sequential probability updating to detect quality faults in water distribution systems using multivariate water quality time series. A common feature of the methods mentioned above is that they are merely relying on data process.…”
Section: Introductionmentioning
confidence: 99%
“…The threshold can be set manually (e.g., Pickard, et al 2011) or inferred in an automatic fashion based on the acquired data and trends observed (Arad et al 2013). This approach, however, is vulnerable to faulty measurements that present a large deviation from the pattern.…”
Section: Event Detection In Streams Of Stationary Wdesn Nodesmentioning
confidence: 99%
“…Perelman et al (2012) tested their approach on a real data set. Arad et al (2013) followed up on the work of Perelman et al (2012) by adding a dynamic threshold scheme. The decision variables were: positive and negative filters, positive and negative dynamic thresholds and data window size.…”
Section: Optimization Techniquesmentioning
confidence: 99%