Symbolic Dynamic Analysis of Transient Time Series for Fault Detection in Gas Turbine Engines
2012 ◽
Vol 135
(1)
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This brief paper presents a symbolic dynamics-based method for detection of incipient faults in gas turbine engines. The underlying algorithms for fault detection and classification are built upon the recently reported work on symbolic dynamic filtering. In particular, Markov model-based analysis of quasi-stationary steady-state time series is extended to analysis of transient time series during takeoff. The algorithms have been validated by simulation on the NASA Commercial Modular Aero Propulsion System Simulation (C-MAPSS) transient test-case generator.
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Disturbance Attenuation in Fault Detection of Gas Turbine Engines: A Discrete Robust Observer Design
2009 ◽
Vol 39
(2)
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pp. 234-239
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2011 ◽
Vol 226
(4)
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pp. 422-436
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2016 ◽
Vol 24
(4)
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pp. 1184-1200
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