Timing Aspects in Causality Analysis with Multilevel Flow Modelling

Denis Kirchhübel; Dimitri Lefebvre; Morten Lind; Safae Lmansouri; Claus Myllerup

doi:10.1016/j.ifacol.2022.07.201

Timing Aspects in Causality Analysis with Multilevel Flow Modelling

Denis Kirchhübel^*, Dimitri Lefebvre^*, Morten Lind^*, Safae Lmansouri^*, Claus Myllerup^*

^*Corresponding author for this work

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

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Abstract

Temporal aspects of multilevel flow modelling (MFM) are important for reasoning about causes and consequences. In particular real time reasoning about sensor data are dependent on proper temporal ordering of events in order to cope with plant dynamics. The purpose of the present paper is to contribute to the further development of the temporal aspects of MFM by explaining how time stamps associated to the measured signals can be used to enhance the causality analysis and infer the possible causes of a sequence of alarms.

Original language	English
Title of host publication	Proceedings of 11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2022
Number of pages	6
Volume	55
Publisher	Elsevier
Publication date	2022
Edition	6
Pages	649-654
DOIs	https://doi.org/10.1016/j.ifacol.2022.07.201
Publication status	Published - 2022
Event	11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes - Aliathon Resort , Pafos, Cyprus Duration: 8 Jun 2022 → 10 Jun 2022 Conference number: 11 https://safeprocess2021.eu/

Conference

Conference	11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes
Number	11
Location	Aliathon Resort
Country/Territory	Cyprus
City	Pafos
Period	08/06/2022 → 10/06/2022
Internet address	https://safeprocess2021.eu/

Keywords

Causality analysis
Fault diagnosis
Multilevel flow modeling
Timing analysis

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title = "Timing Aspects in Causality Analysis with Multilevel Flow Modelling",

abstract = "Temporal aspects of multilevel flow modelling (MFM) are important for reasoning about causes and consequences. In particular real time reasoning about sensor data are dependent on proper temporal ordering of events in order to cope with plant dynamics. The purpose of the present paper is to contribute to the further development of the temporal aspects of MFM by explaining how time stamps associated to the measured signals can be used to enhance the causality analysis and infer the possible causes of a sequence of alarms.",

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author = "Denis Kirchh{\"u}bel and Dimitri Lefebvre and Morten Lind and Safae Lmansouri and Claus Myllerup",

note = "Publisher Copyright: {\textcopyright} 2022 Elsevier B.V.. All rights reserved.; 11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2022 ; Conference date: 08-06-2022 Through 10-06-2022",

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booktitle = "Proceedings of 11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2022",

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Kirchhübel, D, Lefebvre, D, Lind, M, Lmansouri, S & Myllerup, C 2022, Timing Aspects in Causality Analysis with Multilevel Flow Modelling. in Proceedings of 11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2022. 6 edn, vol. 55, Elsevier, pp. 649-654, 11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, Pafos, Cyprus, 08/06/2022. https://doi.org/10.1016/j.ifacol.2022.07.201

Timing Aspects in Causality Analysis with Multilevel Flow Modelling. / Kirchhübel, Denis; Lefebvre, Dimitri; Lind, Morten et al.

Proceedings of 11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2022. Vol. 55 6. ed. Elsevier, 2022. p. 649-654.

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

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AU - Kirchhübel, Denis

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AU - Myllerup, Claus

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KW - Causality analysis

KW - Fault diagnosis

KW - Multilevel flow modeling

KW - Timing analysis

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DO - 10.1016/j.ifacol.2022.07.201

M3 - Article in proceedings

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Y2 - 8 June 2022 through 10 June 2022

ER -

Timing Aspects in Causality Analysis with Multilevel Flow Modelling

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Keywords

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