Stochastic Fault Diagnosability in Parity Spaces
2002 (English)In: Proceedings of the 15th IFAC World Congress, 2002, 736-736 p.Conference paper (Refereed)
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.
Fault detection, Diagnosis, Kalman filtering, Adaptive filters, Linear systems
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-90297DOI: 10.3182/20020721-6-ES-1901.00738ISBN: 978-3-902661-74-6OAI: oai:DiVA.org:liu-90297DiVA: diva2:613659
15th IFAC World Congress, Barcelona, Spain, July, 2002