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  Support vector novelty detection applied to jet engine vibration spectra

Hayton, P., Schölkopf, B., Tarassenko, L., & Anuzis, P. (2001). Support vector novelty detection applied to jet engine vibration spectra. Advances in Neural Information Processing Systems, 946-946.

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 Creators:
Hayton, P, Author
Schölkopf, B1, Author           
Tarassenko, L, Author
Anuzis, P, Author
Leen, Editor
T.K., Editor
Dietterich, T.G., Editor
Tresp, V., Editor
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Abstract: A system has been developed to extract diagnostic information from jet engine carcass vibration data. Support Vector Machines applied to novelty detection provide a measure of how unusual the shape of a vibration 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 application to Jet Engine vibration analysis.

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 Dates: 2001-04
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISBN: 0-262-12241-3
URI: http://books.nips.cc/nips13.html
BibTex Citekey: 1840
 Degree: -

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Title: Fourteenth Annual Neural Information Processing Systems Conference (NIPS 2000)
Place of Event: Denver, CO, USA
Start-/End Date: -

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Title: Advances in Neural Information Processing Systems
Source Genre: Journal
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Affiliations:
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 946 - 946 Identifier: -