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Dynamic Intelligent Prediction Control in Slender Cylindrical Grinding
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Interpretative Structural Modeling for Ceramic Grindability System
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Study on Self-Configuration Method of Neural Network Model for Grinding Troubles On-Line Monitoring
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Dynamic Intelligent Prediction Control in Slender Cylindrical Grinding

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Abstract:

A dynamic intelligent prediction control system is built in slender cylindrical grinding. Elman network is used in the dynamic size prediction control model, and the first and the second derivative of the actual amount removed from the workpiece are added into the network input, which can greatly improve the size dynamic prediction accuracy. Moreover, a surface roughness equation with vibration data is proposed. Based the equation, the surface roughness dynamic fuzzy neural network prediction subsystem is built. Experiment verifies that the developed prediction control system is feasible and has high prediction and control accuracy.

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Periodical:

Key Engineering Materials (Volumes 359-360)

Pages:

189-193

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.359-360.189

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Online since:

November 2007

Authors:

Ning Ding, Xiao Mei Li, Yuan Ding, Guo Fa Li, Long Shan Wang

Keywords:

Control, Dynamic, Elman Network, Prediction, Roughness, Size, Vibration

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© 2008 Trans Tech Publications Ltd. All Rights Reserved

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