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

• Main Authors: Anghel Daniel-Constantin, Ene Alexandru
• Format: Article
• Language: English
• Published: EDP Sciences 2018-01-01
• Series: MATEC Web of Conferences
• Online Access: https://doi.org/10.1051/matecconf/201817803011

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.