Study of the influence of the technological parameters on the weld quality using artificial neural networks

被引：1

作者：

Anghel, Daniel-Constantin ^{[1
]}

Ene, Alexandru ^{[2
]}

机构：

[1] Univ Pitesti, Dept Mfg & Ind Management, Str Tg Din Vale 1, Pitesti, Romania

[2] Univ Pitesti, Dept Elect Comp Commun & Elect Engn, Str Tg Din Vale 1, Pitesti, Romania

来源：

22ND INTERNATIONAL CONFERENCE ON INNOVATIVE MANUFACTURING ENGINEERING AND ENERGY - IMANE&E 2018 | 2018年 / 178卷

关键词：

D O I：

10.1051/matecconf/201817803011

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper presents a study on the weld quality obtained by different values of the input parameters. The weld quality is characterized by two categories of parameters: geometrical parameters and mechanical parameters. They are dependent on the following process parameters: electric arc voltage, electric current intensity, welding speed, the feed wire velocity. Because the dependence between inputs and outputs is a nonlinear one was used an artificial feed forward neural network (ANN). The ANN was trained with the backpropagation algorithm, using as training patterns data measured from the mechanical process. This ANN can be used to estimate some parameters from future experiments of the mechanical process.

引用

页数：6