Simulation of Failure Detection Based on Neural Network for No-Ball Mill

Abstract:

Article Preview

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 et al., "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:

$35.00

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