Towards a condition monitoring scheme for combustion instability detection and fuel blends performance classification in gas turbine engines using pattern recognition and advanced machine learning

Matthaiou, I., Khandelwal, B. and Antoniadou, I. (2016) Towards a condition monitoring scheme for combustion instability detection and fuel blends performance classification in gas turbine engines using pattern recognition and advanced machine learning. In: e-journal of Nondestructive Testing. 8th European Workshop on Structural Health Monitoring (EWSHM 2016), July 5-8, 2016, Bilbao, Spain. NDT .

Abstract

Metadata

Authors/Creators:
  • Matthaiou, I.
  • Khandelwal, B.
  • Antoniadou, I.
Copyright, Publisher and Additional Information: © NDT
Keywords: Machine learning and pattern recognition; Feature extraction; Engine vibration; Thermoacoustic instability; Cluster analysis; Support vector machine; Gas turbine engines
Dates:
  • Published: 27 July 2016
  • Published (online): 5 July 2016
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 16 Aug 2016 15:29
Last Modified: 03 Nov 2016 04:34
Published Version: http://www.ndt.net/events/EWSHM2016/app/content/Pa...
Status: Published
Publisher: NDT

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