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Original title:
Preliminaries of probabilistic hierarchical fault detection
Authors: Jirsa, Ladislav ; Pavelková, Lenka ; Dedecius, Kamil
Document type: Papers
Conference/Event: The 3rd International Workshop on Scalable Decision Making: Uncertainty, Imperfection, Deliberation held in conjunction with ECML/PKDD 2013, Prague (CZ), 2013-09-23 / 2013-09-23
Year: 2013
Language: eng
Abstract: The paper proposes a novel probabilistic fault detection and isolation (FDI) system that enables to evaluate dynamically the industrial system condition (health) at any level of its functional hierarchy. The investigated industrial system is considered as a set of interconnected individual components. Each component acts in its noisy environment as an imperfect participant, more or less dependent on neighbouring components and, in turn, influencing some others. The nature of the problem prevents us from expressing sufficiently hard propositions about the health of the system as a whole at once but we can observe and construct propositions at lower system hierarchies. These propositions (opinions) are combined at higher levels using the rules of probabilistic logic, retaining the ignorance and finally yielding a single opinion on the health of the whole monitored system.
Keywords: Fault detection; FDI; probabilistic logic; system health
Project no.: 7D12004 (CEP), GA13-13502S (CEP)
Funding provider: GA MŠk, GA ČR
Host item entry: Preprints of the 3rd International Workshop on Scalable Decision Making held in conjunction with ECML/PKDD 2013, ISBN 978-80-903834-8-7
Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2013/AS/jirsa-preliminaries of probabilistic hierarchical fault detection.pdf
Original record: http://hdl.handle.net/11104/0224316
Permalink: http://www.nusl.cz/ntk/nusl-156605
The record appears in these collections:
Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers
Authors: Jirsa, Ladislav ; Pavelková, Lenka ; Dedecius, Kamil
Document type: Papers
Conference/Event: The 3rd International Workshop on Scalable Decision Making: Uncertainty, Imperfection, Deliberation held in conjunction with ECML/PKDD 2013, Prague (CZ), 2013-09-23 / 2013-09-23
Year: 2013
Language: eng
Abstract: The paper proposes a novel probabilistic fault detection and isolation (FDI) system that enables to evaluate dynamically the industrial system condition (health) at any level of its functional hierarchy. The investigated industrial system is considered as a set of interconnected individual components. Each component acts in its noisy environment as an imperfect participant, more or less dependent on neighbouring components and, in turn, influencing some others. The nature of the problem prevents us from expressing sufficiently hard propositions about the health of the system as a whole at once but we can observe and construct propositions at lower system hierarchies. These propositions (opinions) are combined at higher levels using the rules of probabilistic logic, retaining the ignorance and finally yielding a single opinion on the health of the whole monitored system.
Keywords: Fault detection; FDI; probabilistic logic; system health
Project no.: 7D12004 (CEP), GA13-13502S (CEP)
Funding provider: GA MŠk, GA ČR
Host item entry: Preprints of the 3rd International Workshop on Scalable Decision Making held in conjunction with ECML/PKDD 2013, ISBN 978-80-903834-8-7
Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2013/AS/jirsa-preliminaries of probabilistic hierarchical fault detection.pdf
Original record: http://hdl.handle.net/11104/0224316
Permalink: http://www.nusl.cz/ntk/nusl-156605
The record appears in these collections:
Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers
Record created 2013-10-04, last modified 2021-11-24