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Study on Self-Configuration Method of Neural Network Model for Grinding Troubles On-Line Monitoring

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Abstract:

A grinding trouble on-line monitoring mode is presented based on the nonlinear building mode principle of neural network. The input units were the peak of the FFT, the peak of RMS, and the standard deviation of AE signals. The outputs were the troubles of the grinding burning, grinding chatter, and grinding wheel dull. The structure of neural network is established by self-configuration method. The network mode is trained and tested by using the experiment data, and the results indicate that the neural network mode obtained by self-configuration method has high recognize rate for grinding troubles, and can be used to monitor grinding troubles on-line.

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Periodical:

Key Engineering Materials (Volumes 359-360)

Pages:

199-203

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.359-360.199

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Online since:

November 2007

Authors:

Gui Jie Liu, Qiang Wang, Xiao Long Shi, Ren Ke Kang

Keywords:

Grinding Trouble, Neural Network (NN), Online Monitoring, Self-Configuration Building Mode Method

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© 2008 Trans Tech Publications Ltd. All Rights Reserved

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