Gas Turbine Engine Condition Monitoring Using Gaussian Mixture and Hidden Markov Models

Gas Turbine Engine Condition Monitoring Using Gaussian Mixture and Hidden Markov Models

This paper investigates the problem of condition monitoring of complex dynamic systems, specifically the detection, localisation and quantification of transient faults. A data driven approach is developed for fault detection where the multidimensional data sequence is viewed as a stochastic process...

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Bibliographic Details
Main Authors:	William R. Jacobs, Huw L. Edwards, Ping Li, Visakan Kadirkamanathan, Andrew R. Mills
Format:	Article
Language:	English
Published:	The Prognostics and Health Management Society 2018-06-01
Series:	International Journal of Prognostics and Health Management
Subjects:	condition monitoring fault detection hidden markov model gaussian mixture model gas turbine engine
Online Access:	https://papers.phmsociety.org/index.php/ijphm/article/view/2734

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