Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra
Abstract
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.
Cite
Text
Hayton et al. "Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra." Neural Information Processing Systems, 2000.Markdown
[Hayton et al. "Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra." Neural Information Processing Systems, 2000.](https://mlanthology.org/neurips/2000/hayton2000neurips-support/)BibTeX
@inproceedings{hayton2000neurips-support,
title = {{Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra}},
author = {Hayton, Paul M. and Schölkopf, Bernhard and Tarassenko, Lionel and Anuzis, Paul},
booktitle = {Neural Information Processing Systems},
year = {2000},
pages = {946-952},
url = {https://mlanthology.org/neurips/2000/hayton2000neurips-support/}
}