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Journal of Zhejiang University SCIENCE A
ISSN 1673-565X(Print), 1862-1775(Online), Monthly
2008 Vol.9 No.1 P.104-108
Parameter optimization model in electrical discharge machining process
Abstract: Electrical discharge machining (EDM) process, at present is still an experience process, wherein selected parameters are often far from the optimum, and at the same time selecting optimization parameters is costly and time consuming. In this paper, artificial neural network (ANN) and genetic algorithm (GA) are used together to establish the parameter optimization model. An ANN model which adapts Levenberg-Marquardt algorithm has been set up to represent the relationship between material removal rate (MRR) and input parameters, and GA is used to optimize parameters, so that optimization results are obtained. The model is shown to be effective, and MRR is improved using optimized machining parameters.
Key words: Electrical discharge machining (EDM), Genetic algorithm (GA), Artificial neural network (ANN), Levenberg-Marquardt algorithm
References:
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DOI:
10.1631/jzus.A071242
CLC number:
TG5; TP2
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On-line Access:
2007-11-10
Received:
2007-03-12
Revision Accepted:
2007-07-05
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