Research on intelligent fault diagnosis of mechanical equipment based on sparse deep neural networks

Research on intelligent fault diagnosis of mechanical equipment based on sparse deep neural networks

In the big data background, the accuracy of fault diagnosis and recognition has been difficult to be improved. The deep neural network was used to recognize the diagnosis rate of the bearing with four kinds of conditions and compared with traditional BP neural network, genetic neural network and par...

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Bibliographic Details
Main Authors:	Fei-Wei Qin, Jing Bai, Wen-Qiang Yuan
Format:	Article
Language:	English
Published:	JVE International 2017-06-01
Series:	Journal of Vibroengineering
Subjects:	fault diagnosis accuracy rate sparse deep neural networks fault diameters excitation loads
Online Access:	https://www.jvejournals.com/article/17146

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