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Authors: Laura Haviez 1 ; Rosario Toscano 2 ; Siegfried Fourvy 2 and Ghislain Yantio 3

Affiliations: 1 LTDS and SAGEM, France ; 2 LTDS, France ; 3 SAGEM, France

Keyword(s): Fretting Wear Modeling, Artificial Intelligence, Artificial Neural Networks.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: Materials wear is a very complex, only partially-formalized phenomenon involving numerous parameters and damage mechanisms. The need to characterize wear in many industrial applications prompted the present research. The study concerns an original strategy investigating the effect of contact conditions on the wear behavior of carburized stainless steels under fretting and reciprocating sliding motion. A physical model was constructed, and pre-treated experimental data were incorporated in a neural network to model wear volume. Three models are proposed and compared, according to input.

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Paper citation in several formats:
Haviez, L.; Toscano, R.; Fourvy, S. and Yantio, G. (2014). Neural Network for Fretting Wear Modeling. In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-015-4; ISSN 2184-433X, pages 617-621. DOI: 10.5220/0004908506170621

@conference{icaart14,
author={Laura Haviez. and Rosario Toscano. and Siegfried Fourvy. and Ghislain Yantio.},
title={Neural Network for Fretting Wear Modeling},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2014},
pages={617-621},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004908506170621},
isbn={978-989-758-015-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Neural Network for Fretting Wear Modeling
SN - 978-989-758-015-4
IS - 2184-433X
AU - Haviez, L.
AU - Toscano, R.
AU - Fourvy, S.
AU - Yantio, G.
PY - 2014
SP - 617
EP - 621
DO - 10.5220/0004908506170621