Multi-fault diagnosis of rotating machinery based on deep convolution neural network and support vector machine-Reference-Cited by-同舟云学术

Multi-fault diagnosis of rotating machinery based on deep convolution neural network and support vector machine

Published:2020-05 Issue: Volume:156 Page:107571
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Xue Yan,Dou Dongyang,Yang Jianguo

Funder

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference25 articles.

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4. Dominant feature selection for the fault diagnosis of rotary machines using modified genetic algorithm and empirical mode decomposition;Lu;J. Sound Vib.,2015

5. A wavelet packet decomposition and principal component analysis approach for feature extraction in bearing failure vibration signal;Du;Control Eng. China,2016

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