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Fundamental Fault Detection Limitations in Linear Non-Gaussian Systems
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.ORCID-id: 0000-0002-1971-4295
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
2005 (engelsk)Rapport (Annet vitenskapelig)
Abstract [en]

Sophisticated fault detection (FD) algorithms often include nonlinear mappings of observed data to fault decisions, and simulation studies are used to support the methods. Objective statistically supported performance analysis of FDalgorithms is only possible for some special cases, including linear Gaussian models. The goal here is to derive general statistical performance bounds for any FD algorithm, given a nonlinear non-Gaussian model of the system. Recent advances in numerical algorithms for nonlinear filtering indicate that such bounds in many practical cases are attainable. This paper focuses on linear non-Gaussian models. A couple of different fault detection setups based on parity space and Kalman filter approaches are considered, where the fault enters a computable residual linearly. For this class of systems, fault detection can be based on the best linear unbiased estimate (BLUE) of the fault vector. Alternatively, a nonlinear filter can potentially compute the maximum likelihood (ML) state estimate, whose performance is bounded by the Cramér-Rao lower bound (CRLB). The contribution in this paper is general expressions for the CRLB for this class of systems, interpreted in terms offault detectability. The analysis is exemplified for a case with measurements affected by outliers.

sted, utgiver, år, opplag, sider
Linköping: Linköping University Electronic Press, 2005. , s. 11
Serie
LiTH-ISY-R, ISSN 1400-3902 ; 2709
Emneord [en]
Fault detection, Maximum likelihood estimation, Colored Noice, Automatic control
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-56071ISRN: LiTH-ISY-R-2709OAI: oai:DiVA.org:liu-56071DiVA, id: diva2:316866
Tilgjengelig fra: 2010-04-30 Laget: 2010-04-30 Sist oppdatert: 2015-09-22bibliografisk kontrollert

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