Data-driven fault detection in aircraft engines with noisy sensor measurements

Journal of Engineering for Gas Turbines and Power

Volumn 133, Issue 8, 2011, Pages

  Sarkar, Soumik ^a   Jin, Xin ^a   Ray, Asok ^a  

^a The Pennsylvania State University   (United States)

Author keywords

aircraft gas turbine engines; data driven fault detection; multiclass classification; optimal feature extraction

Indexed keywords

AIRCRAFT GAS TURBINE ENGINES; DATA-DRIVEN; DETECTION PERFORMANCE; MODEL-BASED; MULTI-CLASS CLASSIFICATION; NOISY SENSORS; OPTIMAL FEATURE EXTRACTION; PATTERN CLASSIFICATION; PROPULSION SYSTEM; SENSOR DEGRADATION; SENSOR NOISE LEVEL; SENSOR SIGNALS; SYMBOLIC DYNAMIC FILTERING; SYSTEM FAULTS; TIME-SERIES DATA;

AIRCRAFT; AIRCRAFT ENGINES; FAULT DETECTION; FEATURE EXTRACTION; GAS TURBINES; NASA; OPTIMIZATION; PROPULSION; SENSORS; TIME SERIES; TURBOMACHINERY;

AIRCRAFT DETECTION;

EID: 79954507840     PISSN: 07424795     EISSN: 15288919     Source Type: Journal    
DOI: 10.1115/1.4002877     Document Type: Article

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