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

Reference33 articles.

1. On the usefulness of pre-processing methods in Rotating machines faults classification using artificial neural network;Alzghoul;Journal of Applied and Computational Mechanics,2021

2. Fault detection and diagnosis in rotating machinery by vibration monitoring using FFT and Wavelet techniques;Atoui,2013

3. Wavelet transform based on inner product in fault diagnosis of rotating machinery: a review;Chen;Mech. Syst. Signal Process.,2016

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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