Paper Title:
Simulation of Failure Detection Based on Neural Network for No-Ball Mill
  Abstract

According to the structural characteristics of non-ball mill, using the neural network theory to select and measure point, set the failure mode, analyze and determine the cause of malfunction. The newly developed fault detection system was used to simulative detect fault. Through data processing, the results can be directly derived which could be fed back into the design of non-ball mill, thereby improving the design.

  Info
Periodical
Advanced Materials Research (Volumes 201-203)
Edited by
Daoguo Yang, Tianlong Gu, Huaiying Zhou, Jianmin Zeng and Zhengyi Jiang
Pages
627-631
DOI
10.4028/www.scientific.net/AMR.201-203.627
Citation
K. S. Li, X. H. Wang, W. M. Wang, "Simulation of Failure Detection Based on Neural Network for No-Ball Mill", Advanced Materials Research, Vols. 201-203, pp. 627-631, 2011
Online since
February 2011
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Price
$32.00
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