Fault detection in a wastewater treatment plant

Imen Baklouti,Mohamed Ben Slima,Majdi Mansouri,Ahmed Ben Hamida,Hazem Nounou

doi:10.1109/atsip.2017.8075523

Fault detection in a wastewater treatment plant

Imen Baklouti, Mohamed Ben Slima + Show 3 more

https://doi.org/10.1109/atsip.2017.8075523

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Publication Date: May 1, 2017

Citations: 22

Affiliation: University of Carthage, Texas A&M University at Qatar, University of Sfax

#Exponentially Weighted Moving Average #Exponentially Weighted Moving Average Control Chart + Show 8 more

Abstract
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Abstract

In this paper, Unscented Kalman filter (UKF) based Exponentially Weighted Moving Average (EWMA) is proposed for fault detection in a Wastewater Treatment Plant (WWTP). In the developed UKF-based EWMA, the UKF technique is used to compute the residual between the true and the estimated variable and the EWMA control chart is applied to detect the faults. The fault detection technique will be tested using simulated COST wastewater treatment ASM1 model. The detection results of the UKF-based EWMA technique are evaluated using three fault detection criteria: the false alarm rate (FAR), Average Run Length (ARL 1 ) and the missed detection rate (MDR).

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