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Indirect model for roughness in rough honing processes based on artificial neural networks

Autor
Sivatte, M.; Parra, X.; Buj, I.; Vivancos, J.
Tipus d'activitat
Article en revista
Revista
Precision engineering - Journal of the American Society for Precision Engineering (ASPE)
Data de publicació
2016-01-01
Volum
43
Pàgina inicial
505
Pàgina final
513
DOI
https://doi.org/10.1016/j.precisioneng.2015.09.004 Obrir en finestra nova
Projecte finançador
Optimización del acabado superficial interior de cilindros mecanizados mediante honing y plateau-honing
Repositori
http://hdl.handle.net/2117/82884 Obrir en finestra nova
URL
http://www.sciencedirect.com/science/article/pii/S0141635915001658 Obrir en finestra nova
Resum
In the present paper an indirect model based on neural networks is presented for modelling the rough honing process. It allows obtaining values to be set for different process variables (linear speed, tangential speed, pressure of abrasive stones, grain size of abrasive and density of abrasive) as a function of required average roughness Ra. A multilayer perceptron (feedforward) with a backpropagation (BP) training system was used for defining neural networks. Several configurations were tested ...
Citació
Sivatte, M., Llanas, F., Buj, I., Vivancos, J. Indirect model for roughness in rough honing processes based on artificial neural networks. "Precisionn engineering - Journal of the American Society for Precision Engineering (ASPE)", 01 Gener 2016, vol. 43, p. 505-513.
Paraules clau
Artificial neural networks, Honing, Indirect model, Surface roughness
Grup de recerca
CETpD -Centre d'Estudis Tecnològics per a l'Atenció a la Dependència i la Vida Autònoma
TECNOFAB - Grup de Recerca en Tecnologies de Fabricació

Participants

Arxius