Fault detection using UKF-based optimized EWMA method in wastewater treatment plant

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

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).

Original languageEnglish
Title of host publication2018 4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538652398
DOIs
Publication statusPublished - 23 May 2018
Externally publishedYes
Event4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018 - Sousse, Tunisia
Duration: 21 Mar 201824 Mar 2018

Publication series

Name2018 4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018

Conference

Conference4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018
Country/TerritoryTunisia
CitySousse
Period21/03/1824/03/18

Keywords

  • Fault detection
  • Optimized EWMA
  • Unscented Kalman Filter
  • Wastewater Treatment Plant

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