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.
Verfasser*innenangaben: | Yakov Ben-Haim, Susanne Seibold |
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URN: | urn:nbn:de:hbz:386-kluedo-7107 |
Schriftenreihe (Bandnummer): | Berichte des Fraunhofer-Instituts für Techno- und Wirtschaftsmathematik (ITWM Report) (3) |
Dokumentart: | Preprint |
Sprache der Veröffentlichung: | Englisch |
Jahr der Fertigstellung: | 1998 |
Jahr der Erstveröffentlichung: | 1998 |
Veröffentlichende Institution: | Fraunhofer-Institut für Techno- und Wirtschaftsmathematik |
Datum der Publikation (Server): | 03.04.2000 |
Freies Schlagwort / Tag: | Kalman filtering; Robust reliability; convex models; crack diagnosis; multi-hypothesis diagnosis; rotating machinery |
Fachbereiche / Organisatorische Einheiten: | Fraunhofer (ITWM) |
DDC-Sachgruppen: | 5 Naturwissenschaften und Mathematik / 510 Mathematik |
Lizenz (Deutsch): | Standard gemäß KLUEDO-Leitlinien vor dem 27.05.2011 |