Journal article
Static and dynamic novelty detection methods for jet engine health monitoring.
- Abstract:
-
Novelty detection requires models of normality to be learnt from training data known to be normal. The first model considered in this paper is a static model trained to detect novel events associated with changes in the vibration spectra recorded from a jet engine. We describe how the distribution of energy across the harmonics of a rotating shaft can be learnt by a support vector machine model of normality. The second model is a dynamic model partially learnt from data using an expectation-m...
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- Publisher copy:
- 10.1098/rsta.2006.1931
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Authors
Bibliographic Details
- Journal:
- Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
- Volume:
- 365
- Issue:
- 1851
- Pages:
- 493-514
- Publication date:
- 2007-02-01
- DOI:
- EISSN:
-
1471-2962
- ISSN:
-
1364-503X
- Source identifiers:
-
61531
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
pubs:61531
- UUID:
-
uuid:3e17d68d-7c26-4a35-ad9c-11d7e0760df1
- Local pid:
- pubs:61531
- Deposit date:
- 2013-11-17
Terms of use
- Copyright date:
- 2007
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