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Visualization of multi-channel sensor data from aero jet engines for condition monitoring and novelty detection

Abstract:

The work presented in this paper seeks to determine if it is possible to determine if an aero gas jet engine is behaving normally by learning the expected variation of its Feature Detector (FD) scores and comparing subsequent flight data against a model of the expected scores. We want to be able to characterize the engine by monitoring combinations of FD scores so that it is possible to quickly and intuitively ascertain if an engine is behaving normally according to the previously learned mod...

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Publication status:
Not Published
Peer review status:
Not peer reviewed
Version:
Author's Original

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Institution:
University of Oxford
Research group:
Biological Signal Processing Research Group
Department:
Mathematical,Physical & Life Sciences Division - Engineering Science
URN:
uuid:90783179-00b1-4fab-989c-9ddf82f2b1ab
Local pid:
ora:1873

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