@inproceedings{2fe2db05639a43d4b2dbbfe10e83e6df,
title = "Fault detection in a wastewater treatment plant",
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 (ARL1) and the missed detection rate (MDR).",
author = "Imen Baklouti and Majdi Mansouri and Hazem Nounou and {Ben Slima}, Mohamed and {Ben Hamida}, Ahmed",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017 ; Conference date: 22-05-2017 Through 24-05-2017",
year = "2017",
month = oct,
day = "19",
doi = "10.1109/ATSIP.2017.8075523",
language = "English",
series = "Proceedings - 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Hamida, {Ahmed Ben} and Basel Solaiman and Slima, {Ahmed Ben} and {El Hassouni}, Mohammed and Mohammed Karim",
booktitle = "Proceedings - 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017",
address = "United States",
}