Header logo is

Support vector novelty detection applied to jet engine vibration spectra

2001

Conference Paper

ei


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.

Author(s): Hayton, P. and Schölkopf, B. and Tarassenko, L. and Anuzis, P.
Book Title: Advances in Neural Information Processing Systems 13
Journal: Advances in Neural Information Processing Systems
Pages: 946-952
Year: 2001
Month: April
Day: 0
Editors: TK Leen and TG Dietterich and V Tresp
Publisher: MIT Press

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

Event Name: 14th Annual Neural Information Processing Systems Conference (NIPS 2000)
Event Place: Denver, CO, USA

Address: Cambridge, MA, USA
Digital: 0
ISBN: 0-262-12241-3
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF
Web

BibTex

@inproceedings{1840,
  title = {Support vector novelty detection applied to jet engine vibration spectra},
  author = {Hayton, P. and Sch{\"o}lkopf, B. and Tarassenko, L. and Anuzis, P.},
  journal = {Advances in Neural Information Processing Systems},
  booktitle = {Advances in Neural Information Processing Systems 13},
  pages = {946-952},
  editors = {TK Leen and TG Dietterich and V Tresp},
  publisher = {MIT Press},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Cambridge, MA, USA},
  month = apr,
  year = {2001},
  month_numeric = {4}
}