Gas turbine engine gas path anomaly detection using deep learning with Gaussian distribution

Gas turbine engine anomaly detection is a critical means to ensure the safety and economic efficiency of a flight. As gas path faults make up a sizeable proportion of all the engine faults, an engine gas path anomaly detection method was proposed in the present article. Inspired by recent progress i...

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Veröffentlicht in:	Prognostics and System Health Management Conference S. 1 - 6
Hauptverfasser:	Hui Luo, Shisheng Zhong
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.07.2017
Schlagworte:	Aircraft propulsion Anomaly detection deep learning engine health management Engines Feature extraction gas turbine engine Gaussian distribution Machine learning Noise reduction QAR stacked denoising autoencoders
ISSN:	2166-5656
Online-Zugang:	Volltext
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