Transfer Learning with Deep Recurrent Neural Networks for Remaining Useful Life Estimation

Transfer Learning with Deep Recurrent Neural Networks for Remaining Useful Life Estimation

Prognostics, such as remaining useful life (RUL) prediction, is a crucial task in condition-based maintenance. A major challenge in data-driven prognostics is the difficulty of obtaining a sufficient number of samples of failure progression. However, for traditional machine learning methods and deep...

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Bibliographic Details
Main Authors:	Ansi Zhang, Honglei Wang, Shaobo Li, Yuxin Cui, Zhonghao Liu, Guanci Yang, Jianjun Hu
Format:	Article
Language:	English
Published:	MDPI AG 2018-11-01
Series:	Applied Sciences
Subjects:	remaining useful life fault diagnosis LSTM deep learning transfer learning turbofan engine
Online Access:	https://www.mdpi.com/2076-3417/8/12/2416

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