MATEC Web Conf.
Volume 178, 201822nd International Conference on Innovative Manufacturing Engineering and Energy - IManE&E 2018
|Number of page(s)||6|
|Section||Non-Conventional Technologies in Manufacture and Industry, Welding Technologies|
|Published online||24 July 2018|
Study of the influence of the technological parameters on the weld quality using artificial neural networks
University of Pitesti, Department of Manufacturing and Industrial Management, Str. Tg. din Vale, nr. 1, Pitesti, Romania Romania
2 University of Pitesti, Department of Electronics, Computers, Communications and Electrical Engineering, Str. Tg. Din Vale, nr. 1, Pitesti, Romania
* Corresponding author: email@example.com
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.
© The Authors, published by EDP Sciences, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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