Prediction of the pattern of electroless deposit after pulse laser heating via artificial neural network
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MOE Key Laboratory of Mechanical Manufacture and Automation, Zhejiang University of Technology, Hangzhou 310014, China;
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Research Center of Laser Processing Technology and Engineering, Zhejiang University of Technology, Hangzhou 310014, China
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Corresponding author:
YAO Jian-hua, laser@zjut.edu.cn
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Received Date:
2008-12-15
Accepted Date:
2008-12-24
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Abstract
A model of the relationship between pulse-laser parameters and the pattern of electroless deposit composite coatings(taking into account hardened width,depth and melting state) with a back propagation neural network was constructed in order to explore the theoretical principles underlying pulse-laser reinforcement of plating coatings.The momentum-adaptive learning rate algorithm was selected to increase network stability,training speed and accuracy.The appearance of composite coating was effectively predicted with ±8.33% relative error.This method is a new way of exploring the theoretical principles of pulse-laser coating-reinforcement.
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