Integration of alarm design in fault detection and diagnosis through alarm-range normalization. (May 2020)
- Record Type:
- Journal Article
- Title:
- Integration of alarm design in fault detection and diagnosis through alarm-range normalization. (May 2020)
- Main Title:
- Integration of alarm design in fault detection and diagnosis through alarm-range normalization
- Authors:
- Lucke, Matthieu
Chioua, Moncef
Grimholt, Chriss
Hollender, Martin
Thornhill, Nina F. - Abstract:
- Abstract: Alarm systems designed according to engineering and safety considerations provide the primary source of information for operators when it comes to abnormal situations. Still, alarm systems have rarely been exploited for fault detection and diagnosis. Recent work has demonstrated the benefits of alarm logs for fault detection and diagnosis. However, alarm settings conceived during the alarm design stage can also be integrated into fault detection and diagnosis methods. This paper suggests the use of those alarm settings in the preprocessing of the process measurements, proposing a normalization based on the alarm thresholds of each process variable. Normalization is needed to render process measurements dimensionless for multivariate analysis. While common normalization approaches such as standardization depend on the historical process measurements available, the proposed alarm-range normalization is based on acceptable variations of the process measurements. An industrial case study of an offshore oil gas separation plant is used to demonstrate that the alarm-range normalization improves the robustness of popular methods for fault detection, fault isolation, and fault identification. Highlights: Current normalization practices depend on historical process measurements available. The proposed normalization using alarm thresholds is independent of historical data. Alarm thresholds from alarm design specify acceptable variations of the measurements. Robustness of theAbstract: Alarm systems designed according to engineering and safety considerations provide the primary source of information for operators when it comes to abnormal situations. Still, alarm systems have rarely been exploited for fault detection and diagnosis. Recent work has demonstrated the benefits of alarm logs for fault detection and diagnosis. However, alarm settings conceived during the alarm design stage can also be integrated into fault detection and diagnosis methods. This paper suggests the use of those alarm settings in the preprocessing of the process measurements, proposing a normalization based on the alarm thresholds of each process variable. Normalization is needed to render process measurements dimensionless for multivariate analysis. While common normalization approaches such as standardization depend on the historical process measurements available, the proposed alarm-range normalization is based on acceptable variations of the process measurements. An industrial case study of an offshore oil gas separation plant is used to demonstrate that the alarm-range normalization improves the robustness of popular methods for fault detection, fault isolation, and fault identification. Highlights: Current normalization practices depend on historical process measurements available. The proposed normalization using alarm thresholds is independent of historical data. Alarm thresholds from alarm design specify acceptable variations of the measurements. Robustness of the fault detection and diagnosis is improved on a separation plant. … (more)
- Is Part Of:
- Control engineering practice. Volume 98(2020)
- Journal:
- Control engineering practice
- Issue:
- Volume 98(2020)
- Issue Display:
- Volume 98, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 98
- Issue:
- 2020
- Issue Sort Value:
- 2020-0098-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-05
- Subjects:
- Alarm systems -- Fault detection and diagnosis
Automatic control -- Periodicals
629.89 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09670661 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.conengprac.2020.104388 ↗
- Languages:
- English
- ISSNs:
- 0967-0661
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3462.020000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13615.xml