The estimation with Artificial Neural Networks of some quality parameters for the surfaces processed by superfinishing

This paper presents a study on the quality parameters obtained by superfinishing. The quality is characterized by the roughness. They are dependent on the following process parameters: circular feed, the contact pressure between the piece and the tool, frequency of oscillation of the tool, the cover...

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Bibliographic Details
Main Authors: Anghel Daniel-Constantin, Ene Alexandru
Format: Article
Language:English
Published: EDP Sciences 2017-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201711205001
Description
Summary:This paper presents a study on the quality parameters obtained by superfinishing. The quality is characterized by the roughness. They are dependent on the following process parameters: circular feed, the contact pressure between the piece and the tool, frequency of oscillation of the tool, the coverage degree between the tool and the piece and the basic time. Because the dependence between inputs and outputs is a nonlinear one, in this paper we used an artificial feed forward neural network (ANN). The ANN is trained with the backpropagation algorithm, using as training patterns data measured from the mechanical process. The ANN is used to estimate some parameters from future experiments of the mechanical process.
ISSN:2261-236X