The study of high efficiency and intelligent optimization system in EDM sinking processl

被引：47

作者：

Cao, FG ^{[1
]}

Yang, DY ^{[1
]}

机构：

[1] Beijing Inst Electro Machining, Beijing 100083, Peoples R China

来源：

JOURNAL OF MATERIALS PROCESSING TECHNOLOGY | 2004年 / 149卷 / 1-3期

关键词：

artificial neural networks; genetic algorithms; electron discharge machining;

D O I：

10.1016/j.jmatprotec.2003.10.059

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper presents a method that can be used to automatically determine and optimize the processing parameters in the EDM sinking process with the application of artificial neural networks (ANN). ANN can be optimized with a genetic algorithm (GA) and node deleting algorithm so that the number of hidden nodes of ANN will be determined automatically and scientifically. ANN can be trained with GA and BP algorithms, so that the local least solution can be avoided and the training speed enhanced. The experiment has proved that the utilization of mirror processing conditions generated from the above method will consequently lead to both good small-area mirror processing results and desired processing precision and efficiency. (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：83 / 87

页数：5

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