Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra

Part of Advances in Neural Information Processing Systems 13 (NIPS 2000)

Bibtex Metadata Paper


Paul Hayton, Bernhard Schölkopf, Lionel Tarassenko, Paul Anuzis


A system has been developed to extract diagnostic information from jet engine carcass vibration data. Support Vector Machines applied to nov(cid:173) elty detection provide a measure of how unusual the shape of a vibra(cid:173) tion signature is, by learning a representation of normality. We describe a novel method for Support Vector Machines of including information from a second class for novelty detection and give results from the appli(cid:173) cation to Jet Engine vibration analysis.