Data-driven remaining useful life prediction based on domain adaptation

Data-driven remaining useful life prediction based on domain adaptation

As an important part of prognostics and health management, remaining useful life (RUL) prediction can provide users and managers with system life information and improve the reliability of maintenance systems. Data-driven methods are powerful tools for RUL prediction because of their great modeling...

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Bibliographic Details
Main Authors: Bin cheng Wen, Ming qing Xiao, Xue qi Wang, Xin Zhao, Jian feng Li, Xin Chen
Format: Article
Language:English
Published: PeerJ Inc. 2021-09-01
Series:PeerJ Computer Science
Subjects:
Remaining Useful Life
Transfer Learning
Bidirectional Gated Recurrent Unit
Domain Adversarial Neural Network
Prognostics and Health Management
Online Access:https://peerj.com/articles/cs-690.pdf

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https://peerj.com/articles/cs-690.pdf

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