## Robust Reliability of Diagnostic Multi-Hypothesis Algorithms: Application to Rotating Machinery

• Damage diagnosis based on a bank of Kalman filters, each one conditioned on a specific hypothesized system condition, is a well recognized and powerful diagnostic tool. This multi-hypothesis approach can be applied to a wide range of damage conditions. In this paper, we will focus on the diagnosis of cracks in rotating machinery. The question we address is: how to optimize the multi-hypothesis algorithm with respect to the uncertainty of the spatial form and location of cracks and their resulting dynamic effects. First, we formulate a measure of the reliability of the diagnostic algorithm, and then we discuss modifications of the diagnostic algorithm for the maximization of the reliability. The reliability of a diagnostic algorithm is measured by the amount of uncertainty consistent with no-failure of the diagnosis. Uncertainty is quantitatively represented with convex models.

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Author: Yakov Ben-Haim, Susanne Seibold urn:nbn:de:hbz:386-kluedo-7107 Berichte des Fraunhofer-Instituts für Techno- und Wirtschaftsmathematik (ITWM Report) (3) Preprint English 1998 1998 Fraunhofer-Institut für Techno- und Wirtschaftsmathematik 2000/04/03 Kalman filtering ; Robust reliability ; convex models ; crack diagnosis; multi-hypothesis diagnosis ; rotating machinery Fraunhofer (ITWM) 5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik Standard gemäß KLUEDO-Leitlinien vor dem 27.05.2011

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