A fault diagnosis method for nuclear power plant rotating machinery based on adaptive deep feature extraction and multiple support vector machines-Reference-Cited by-同舟云学术

A fault diagnosis method for nuclear power plant rotating machinery based on adaptive deep feature extraction and multiple support vector machines

Published:2023-10 Issue: Volume:164 Page:104862
ISSN:0149-1970
Container-title:Progress in Nuclear Energy
language:en
Short-container-title:Progress in Nuclear Energy

Author:

Yin Wenzhe,Xia Hong,Huang Xueying,Zhang Jiyu,Miyombo Miyombo Ernest

Publisher

Elsevier BV

Subject

Waste Management and Disposal,Energy Engineering and Power Technology,Safety, Risk, Reliability and Quality,Nuclear Energy and Engineering

Reference33 articles.

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4. A hybrid fine-tuned VMD and CNN scheme for untrained compound fault diagnosis of rotating machinery with unequal-severity faults;Dibaj;Expert Syst. Appl.,2021

5. Feature extraction and recognition for rolling element bearing fault utilizing short-time Fourier transform and non-negative matrix factorization;Gao;Chin. J. Mech. Eng.,2015

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1. Application of deep learning to fault diagnosis of rotating machineries;Measurement Science and Technology;2024-01-25