首页> 外文期刊>Journal of the Balkan Tribological Association >COMPUTER AIDED DETERMINATION OF DRILLING PARAMETERS TO OBTAIN TARGETED SURFACE ROUGHNESS
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COMPUTER AIDED DETERMINATION OF DRILLING PARAMETERS TO OBTAIN TARGETED SURFACE ROUGHNESS

机译:计算机辅助确定目标表面粗糙度的钻削参数

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摘要

The aim of this study was to obtain targeted surface roughness values in drilling by determining drilling parameters using Artificial Neural Networks (ANN). In realizing this, two Artificial Neural Network (ANN) models were developed for the drilling process. The first model is employed for predicting the surface roughness of holes, depending on the drilling parameters (spindle speed and feed rate). The second model is involved with the experimental data and used to determine the drilling parameters to obtain targeted surface roughness. The drilling experiments were performed by changing the spindle speed and feed rate, while the other parameters were kept constant. While the surface roughness of drilled holes was predicted successfully by the first ANN Model, the optimaldrilling parameters to obtain targeted surface roughness were determined by the second model. By this approach, enhanced surface roughness (Ra) values reaching up to the 0.17 lam were obtained during the drilling of AISI 2080 steel.
机译:这项研究的目的是通过使用人工神经网络(ANN)确定钻孔参数来获得钻孔时的目标表面粗糙度值。为实现这一点,开发了两种用于钻孔过程的人工神经网络(ANN)模型。根据钻削参数(主轴转速和进给速度),采用第一个模型来预测孔的表面粗糙度。第二个模型涉及实验数据,用于确定钻孔参数以获得目标表面粗糙度。通过改变主轴转速和进给速度进行钻孔实验,而其他参数保持不变。虽然通过第一个ANN模型成功预测了钻孔的表面粗糙度,但通过第二个模型确定了用于获得目标表面粗糙度的最佳钻孔参数。通过这种方法,在AISI 2080钢的钻孔过程中获得了高达0.17 lam的增强表面粗糙度(Ra)值。

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