Fault Detection using UKF-based Optimized EWMA Method in Wastewater Treatment Plant Conference Paper

abstract

• 2018 IEEE. In this work, Unscented Kalman Filter (UKF) based Optimized exponentially weighted moving average (OEWMA) is suggested for fault detection (FD) in a Wastewater Treatment Plant (WWTP). UKF method is suggested, to compute the residual of the true and the estimated data of WWTP, in addition, the Optimized EWMA is utilised to the faults in a simulated WWTP. The FD techniques will be tested using simulated data, which are generated using the simulated COST benchmark BSM1 of wastewater treatment model, provided by the IWA Task Group of Control Strategies. The results of the detection of the UKF-based Optimized EWMA are appraised with two criteria of FD : the missed detection rate (MDR) and the false alarm rate (FAR).

name of conference

• 2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

authors

• Nounou, Mohamed

published proceedings

• 2018 4TH INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR SIGNAL AND IMAGE PROCESSING (ATSIP)

author list (cited authors)

• Djmal, I. B., Mansouri, M., Nounou, M., Nounou, H., & Ben Hamida, A.

citation count

• 4

complete list of authors

• Djmal, Imen Baklouti||Mansouri, Majdi||Nounou, Mohamed||Nounou, Hazem||Ben Hamida, Ahmed

publication date

• March 2018

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

keywords

• Fault Detection
• Optimized Ewma
• Unscented Kalman Filter
• Wastewater Treatment Plant

Digital Object Identifier (DOI)

• 10.1109/atsip.2018.8364489

International Standard Book Number (ISBN) 13

• 9781538652398

start page

• 1

end page

• 6

URL

• http://dx.doi.org/10.1109/atsip.2018.8364489