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首页> 外文期刊>Journal of Materials Processing Technology >Modeling of surface roughness in precision machining of metal matrix composites using ANN
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Modeling of surface roughness in precision machining of metal matrix composites using ANN

机译:基于ANN的金属基复合材料精密加工中表面粗糙度的建模。

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摘要

Characteristics of machined surfaces are known to influence the product performance significantly since they are directly linked to the ability of the material to withstand stresses, temperature, friction and corrosion. This paper presents an experimental work on the analysis of machined surface quality on Al/SiCp composites leading to an artificial neural network-based (ANN) model to predict the surface roughness. The predicted roughness of machined surfaces based on the ANN model was found to be in very good agreement with the unexposed experimental data set.
机译:众所周知,机加工表面的特性会显着影响产品性能,因为它们与材料承受应力,温度,摩擦和腐蚀的能力直接相关。本文介绍了对Al / SiCp复合材料的机械加工表面质量进行分析的实验工作,从而建立了基于人工神经网络(ANN)的模型来预测表面粗糙度。发现基于ANN模型的加工表面的预测粗糙度与未暴露的实验数据集非常吻合。

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