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首页> 外文会议>Asia Pacific Conference on Optics Manufacture; 20070111-13; Hongkong(CN) >Prediction of Surface Roughness in High Speed Milling Process Using the Artificial Neural Networks
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Prediction of Surface Roughness in High Speed Milling Process Using the Artificial Neural Networks

机译：基于人工神经网络的高速铣削表面粗糙度预测

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摘要

The objective of this research was to apply the artificial neural network algorithm to predict the surface roughness in high speed milling operation. Tool length, feed rate, spindle speed, cutting path interval and run-out were used as five input neurons; and artificial neural networks model based on back-propagation algorithm was developed to predict the output neuron-surface roughness. A series of experiments was performed, and the results were estimated. The experimental results showed that the applied artificial neural network surface roughness prediction gave good accuracy in predicting the surface roughness under a variety of combinations of cutting conditions.
机译：这项研究的目的是应用人工神经网络算法来预测高速铣削操作中的表面粗糙度。刀具长度，进给速度，主轴速度，切削路径间隔和跳动被用作五个输入神经元。建立了基于反向传播算法的人工神经网络模型，以预测输出神经元表面的粗糙度。进行了一系列实验，并估计了结果。实验结果表明，所应用的人工神经网络表面粗糙度预测方法在各种切削条件组合下对表面粗糙度的预测具有良好的准确性。

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