Finite-sensor fault-diagnosis simulation study of gas turbine engine using information entropy and deep belief networks

Frontiers of Information Technology and Electronic Engineering

Volumn 17, Issue 12, 2016, Pages 1287-1304

  Feng, De long ^a   Xiao, Ming qing ^a   Liu, Ying xi ^b   Song, Hai fang ^a   Yang, Zhao ^a   Hu, Ze wen ^a  

^a AIR FORCE ENGINEERING UNIVERSITY   (China)

^b Air Force Xi'an Flight Academy   (China)

Author keywords

Deep belief networks (DBNs); Engine; Fault diagnosis; Information entropy

Indexed keywords

AIRCRAFT PROPULSION; COMPLEX NETWORKS; ENGINES; FAILURE ANALYSIS; GAS TURBINES; LEARNING SYSTEMS;

DEEP BELIEF NETWORKS; INFORMATION ENTROPY; LOGISTIC REGRESSIONS; MACHINE LEARNING APPROACHES; OPERATING ENVIRONMENT; PROGNOSTICS AND HEALTH MANAGEMENTS; SENSOR FAULT DIAGNOSIS; SIMULATION STUDIES;

FAULT DETECTION;

EID: 85006380247     PISSN: 20959184     EISSN: 20959230     Source Type: Journal    
DOI: 10.1631/FITEE.1601365     Document Type: Article

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