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Research on Fault Diagnosis System of Mine Ventilator Based on Elman Neural Network
Ren Zihui 1 * #,Li Jiangang 2,Liu Yanxia 2
1.College of Information and Electrical Engineering, CUMT
2.College of Information and Electrical Engineering, CUMT, Xuzhou 221116, China
*Correspondence author
#Submitted by
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Funding: none
Opened online: 5 July 2011
Accepted by: none
Citation: Ren Zihui,Li Jiangang,Liu Yanxia.Research on Fault Diagnosis System of Mine Ventilator Based on Elman Neural Network[OL]. [ 5 July 2011] http://en.paper.edu.cn/en_releasepaper/content/4433667
 
 
This paper introduced the theory, learning algorithm and technical route of Elman neural. Though acquainting fault signals on-site and normalizing characteristic data, this method realized intelligent diagnosis of ventilator by constructing optimum structure and parameters based on Elman neural network. Compared with the traditional BP neural network, Elman network had a better comprehensive performance in diagnosis of ventilator. The result for the fault diagnosis of a ventilator showed that the Elman network improves the study speed, represses the network to sink local minimum, shortens the study time, and Elman neural is a effective method for the fault diagnosis of ventilator.
Keywords:mine ventilator; Elman neural network; fault diagnosis
 
 
 

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