文献类型： 会议论文
第一作者： Laura Haviez
作者： Laura Haviez 1 ; Rosario Toscano 2 ; Siegfried Fourvy 1 ; Ghislain Yantio 3 ;
作者机构： 1.LTDS, UMR 5513, Ecole Centrale de Lyon
2.LTDS, UMR 5513, ENISE
3.SAGEM, Boulogne-Billancourt Cedex
关键词： Fretting Wear Modeling;Artificial Intelligence;Artificial Neural Networks
会议名称： International Conference on Agents and Artificial Intelligence
主办单位：
页码： 610-614
摘要： 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.
分类号： TP18-53
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