Max-Double Adaptive EWMA for Fault Detection of Wastewater Treatment Plants

Imen Baklouti; Majdi Mansouri; Ahmed Ben Hamida; Hazem Nounou; Mohamed Nounou

doi:10.1109/AICCSA.2018.8612891

Max-Double Adaptive EWMA for Fault Detection of Wastewater Treatment Plants

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

The objective of this paper is to extend the Maximum Adaptive Exponential Weighted Moving Average (Max-AEWMA) chart to the Max Double AEWMA (Max-DAEWMA) chart. The Max-DAEWMA statistic is based on the Max of the absolute values of the two DAEWMA statistics, one for controlling the variance and the other for the mean. The combined novel technique, is called particle filter (PF)-based Max-DAEWMA for detecting faults of wastewater treatment plants (WWTP). The statistical chart, Max-DAEWMA is applied to detect the fault in mean and/or drifts in WWTP systems where the state variables are estimated using PF technique. The results show the effectiveness of the Max-DAEWMA method over Max-DEWMA and EWMA charts.

Original language	English
Title of host publication	2018 IEEE/ACS 15th International Conference on Computer Systems and Applications, AICCSA 2018
Publisher	IEEE Computer Society
ISBN (Electronic)	9781538691205
DOIs	https://doi.org/10.1109/AICCSA.2018.8612891
Publication status	Published - 2 Jul 2018
Externally published	Yes
Event	15th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2018 - Aqaba, Jordan Duration: 28 Oct 2018 → 1 Nov 2018

Publication series

Name	Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA
Volume	2018-November
ISSN (Print)	2161-5322
ISSN (Electronic)	2161-5330

Conference

Conference	15th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2018
Country/Territory	Jordan
City	Aqaba
Period	28/10/18 → 1/11/18

Keywords

Fault Detection (FD)
Max Double-Adaptive Exponentially Weighted Moving Average (Max-DAEWMA)
Particle Filter (PF)
Wastewater Treatment Plant (WWTP)

Access to Document

10.1109/AICCSA.2018.8612891

Cite this

Baklouti, I., Mansouri, M., Ben Hamida, A., Nounou, H., & Nounou, M. (2018). Max-Double Adaptive EWMA for Fault Detection of Wastewater Treatment Plants. In 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications, AICCSA 2018 Article 8612891 (Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA; Vol. 2018-November). IEEE Computer Society. https://doi.org/10.1109/AICCSA.2018.8612891

@inproceedings{e2103207ff094156915e8162c7f5a873,

title = "Max-Double Adaptive EWMA for Fault Detection of Wastewater Treatment Plants",

abstract = "The objective of this paper is to extend the Maximum Adaptive Exponential Weighted Moving Average (Max-AEWMA) chart to the Max Double AEWMA (Max-DAEWMA) chart. The Max-DAEWMA statistic is based on the Max of the absolute values of the two DAEWMA statistics, one for controlling the variance and the other for the mean. The combined novel technique, is called particle filter (PF)-based Max-DAEWMA for detecting faults of wastewater treatment plants (WWTP). The statistical chart, Max-DAEWMA is applied to detect the fault in mean and/or drifts in WWTP systems where the state variables are estimated using PF technique. The results show the effectiveness of the Max-DAEWMA method over Max-DEWMA and EWMA charts.",

keywords = "Fault Detection (FD), Max Double-Adaptive Exponentially Weighted Moving Average (Max-DAEWMA), Particle Filter (PF), Wastewater Treatment Plant (WWTP)",

author = "Imen Baklouti and Majdi Mansouri and \{Ben Hamida\}, Ahmed and Hazem Nounou and Mohamed Nounou",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 15th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2018 ; Conference date: 28-10-2018 Through 01-11-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/AICCSA.2018.8612891",

language = "English",

series = "Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA",

publisher = "IEEE Computer Society",

booktitle = "2018 IEEE/ACS 15th International Conference on Computer Systems and Applications, AICCSA 2018",

address = "United States",

}

Baklouti, I, Mansouri, M, Ben Hamida, A, Nounou, H & Nounou, M 2018, Max-Double Adaptive EWMA for Fault Detection of Wastewater Treatment Plants. in 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications, AICCSA 2018., 8612891, Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, vol. 2018-November, IEEE Computer Society, 15th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2018, Aqaba, Jordan, 28/10/18. https://doi.org/10.1109/AICCSA.2018.8612891

Max-Double Adaptive EWMA for Fault Detection of Wastewater Treatment Plants. / Baklouti, Imen; Mansouri, Majdi; Ben Hamida, Ahmed et al.
2018 IEEE/ACS 15th International Conference on Computer Systems and Applications, AICCSA 2018. IEEE Computer Society, 2018. 8612891 (Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA; Vol. 2018-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Max-Double Adaptive EWMA for Fault Detection of Wastewater Treatment Plants

AU - Baklouti, Imen

AU - Mansouri, Majdi

AU - Ben Hamida, Ahmed

AU - Nounou, Hazem

AU - Nounou, Mohamed

PY - 2018/7/2

Y1 - 2018/7/2

N2 - The objective of this paper is to extend the Maximum Adaptive Exponential Weighted Moving Average (Max-AEWMA) chart to the Max Double AEWMA (Max-DAEWMA) chart. The Max-DAEWMA statistic is based on the Max of the absolute values of the two DAEWMA statistics, one for controlling the variance and the other for the mean. The combined novel technique, is called particle filter (PF)-based Max-DAEWMA for detecting faults of wastewater treatment plants (WWTP). The statistical chart, Max-DAEWMA is applied to detect the fault in mean and/or drifts in WWTP systems where the state variables are estimated using PF technique. The results show the effectiveness of the Max-DAEWMA method over Max-DEWMA and EWMA charts.

AB - The objective of this paper is to extend the Maximum Adaptive Exponential Weighted Moving Average (Max-AEWMA) chart to the Max Double AEWMA (Max-DAEWMA) chart. The Max-DAEWMA statistic is based on the Max of the absolute values of the two DAEWMA statistics, one for controlling the variance and the other for the mean. The combined novel technique, is called particle filter (PF)-based Max-DAEWMA for detecting faults of wastewater treatment plants (WWTP). The statistical chart, Max-DAEWMA is applied to detect the fault in mean and/or drifts in WWTP systems where the state variables are estimated using PF technique. The results show the effectiveness of the Max-DAEWMA method over Max-DEWMA and EWMA charts.

KW - Fault Detection (FD)

KW - Max Double-Adaptive Exponentially Weighted Moving Average (Max-DAEWMA)

KW - Particle Filter (PF)

KW - Wastewater Treatment Plant (WWTP)

UR - https://www.scopus.com/pages/publications/85061926032

U2 - 10.1109/AICCSA.2018.8612891

DO - 10.1109/AICCSA.2018.8612891

M3 - Conference contribution

AN - SCOPUS:85061926032

T3 - Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA

BT - 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications, AICCSA 2018

PB - IEEE Computer Society

T2 - 15th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2018

Y2 - 28 October 2018 through 1 November 2018

ER -

Baklouti I, Mansouri M, Ben Hamida A, Nounou H , Nounou M. Max-Double Adaptive EWMA for Fault Detection of Wastewater Treatment Plants. In 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications, AICCSA 2018. IEEE Computer Society. 2018. 8612891. (Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA). doi: 10.1109/AICCSA.2018.8612891

Max-Double Adaptive EWMA for Fault Detection of Wastewater Treatment Plants

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this