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  • 标题:Study of the influence of the technological parameters on the weld quality using artificial neural networks
  • 本地全文:下载
  • 作者:Daniel-Constantin Anghel ; Alexandru Ene
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2018
  • 卷号:178
  • DOI:10.1051/matecconf/201817803011
  • 语种:English
  • 出版社:EDP Sciences
  • 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.
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