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Applying an Artificial Neural Network to the Control System for Electrochemical Gear-Tooth Profile Modifications  

Jianjun, Yi (Department of Mechanical Engineering, East China University of Science and Technology)
Yifeng, Guan (Department of Mechanical Engineering, East China University of Science and Technology)
Baiyang, Ji (HangZhou Sunyard System Engineering Co. Ltd.)
Bin, Yu (Department of Mechanical Engineering, East China University of Science and Technology)
Jinxiang, Dong (College of Computer Science, Zhejiang University)
Publication Information
International Journal of Precision Engineering and Manufacturing / v.8, no.4, 2007 , pp. 27-32 More about this Journal
Abstract
Gears, crucial components in modern precision machinery for power transmission mechanisms, are required to have low contacting noise with high torque transmission, which makes the use of gear-tooth profile modifications and gear-tooth surface crowning extremely efficient and valuable. Due to the shortcomings of current techniques, such as manual rectification, mechanical modification, and numerically controlled rectification, we propose a novel electrochemical gear-tooth profile modification method based on an artificial neural network control technique. The fundamentals of electrochemical tooth-profile modifications based on real-time control and a mathematical model of the process are discussed in detail. Due to the complex and uncertain relationships among the machining parameters of electrochemical tooth-profile modification processes, we used an artificial neural network to determine the required processing electric current as the tooth-profile modification requirements were supplied. The system was implemented and a practical example was used to demonstrate that this technology is feasible and has potential applications in the production of precision machinery.
Keywords
Back-propagation technique; Real-time control; Electrochemical gear-tooth modifications; Control system;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
Times Cited By Web Of Science : 3  (Related Records In Web of Science)
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