A Generic Indirect Deep Learning Approach for Multisensor Degradation Modeling

Wang, Di; Liu, Kaibo; Zhang, Xi

doi:10.1109/tase.2021.3072363

A Generic Indirect Deep Learning Approach for Multisensor Degradation Modeling

Journal Article · 01 July 2022 · IEEE Transactions on Automation Science and Engineering

DOI:https://doi.org/10.1109/tase.2021.3072363· OSTI ID:1980458

Wang, Di ^[1]; ^[2]; ^[3]

Department of Industrial Engineering and Management, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA
Department of Industrial Engineering and Management, Peking University, Beijing, China

Not provided.

Research Organization:: Univ. of Wisconsin, Madison, WI (United States)

Sponsoring Organization:: USDOE Office of Nuclear Energy (NE)

DOE Contract Number:: NE0008805

OSTI ID:: 1980458

Journal Information:: IEEE Transactions on Automation Science and Engineering, Vol. 19, Issue 3; ISSN 1545-5955

Publisher:: IEEE

Country of Publication:: United States

Language:: English

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