Artificial neural network models for the prediction of surface roughness in electrical discharge machining

被引：103

作者：

Markopoulos, Angelos P. ^{[1
]}

Manolakos, Dimitrios E. ^{[1
]}

Vaxevanidis, Nikolaos M. ^{[2
]}

机构：

[1] Natl Tech Univ Athens, Dept Mech Engn, Mfg Technol Div, Athens, Greece

[2] Inst Pedagog & Technol Educ, Dept Mech Engn, N Heraklion Attikis, Greece

来源：

JOURNAL OF INTELLIGENT MANUFACTURING | 2008年 / 19卷 / 03期

关键词：

artificial neural networks; modeling; surface roughness; electrical discharge machining (EDM);

D O I：

10.1007/s10845-008-0081-9

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the present paper Artificial Neural Networks (ANNs) models are proposed for the prediction of surface roughness in Electrical Discharge Machining (EDM). For this purpose two well-known programs, namely Matlab (R) with associated toolboxes, as well as Netlab (R), were employed. Training of the models was performed with data from an extensive series of EDM experiments on steel grades; the proposed models use the pulse current, the pulse duration, and the processed material as input parameters. The reported results indicate that the proposed ANNs models can satisfactorily predict the surface roughness in EDM. Moreover, they can be considered as valuable tools for the process planning for EDMachining.

引用

页码：283 / 292

页数：10

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