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Stochastic Fault Diagnosability in Parity Spaces
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2002 (English)In: Proceedings of the 15th IFAC World Congress, 2002, 736-736 p.Conference paper (Refereed)
Abstract [en]

We here analyze the parity space approach to fault detection and isolation in a stochastic setting. Using a state space model with both deterministic and stochastic unmeasurable inputs we show a formal relationship between the Kalman filter and the parity space. Based on a statistical fault detection and diagnosis algorithm, the probability for incorrect diagnosis is computed explicitly, given that only a single fault with known time profile has occurred. An example illustrates how the matrix of diagnosis probabilities can be used as a design tool for performance optimization with respect to, for instance, design variables and sensor placement and quality.

Place, publisher, year, edition, pages
2002. 736-736 p.
Keyword [en]
Fault detection, Diagnosis, Kalman filtering, Adaptive filters, Linear systems
National Category
Engineering and Technology Control Engineering
URN: urn:nbn:se:liu:diva-90297DOI: 10.3182/20020721-6-ES-1901.00738ISBN: 978-3-902661-74-6OAI: diva2:613659
15th IFAC World Congress, Barcelona, Spain, July, 2002
Available from: 2013-03-30 Created: 2013-03-24 Last updated: 2013-03-30

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Gustafsson, Fredrik
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Automatic ControlThe Institute of Technology
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ReferencesLink to record
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