选择最佳工具，几何形状和切削条件:利用表面粗糙度预测模型端铣-------外文翻译中英文.doc
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选择最佳工具，几何形状和切削条件:利用表面粗糙度预测模型端铣-------外文翻译中英文,abstract : influence of tool geometry on the quality of surface produced is well known and hence any attempt to assess the performance of end milling should inc...
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Abstract :
Influence of tool geometry on the quality of surface produced is well known and hence any attempt to assess the performance of end milling should include the tool geometry. In the present work, experimental studies have been conducted to see the effect of tool geometry (radial rake angle and nose radius) and cutting conditions (cutting speed and feed rate) on the machining performance during end milling of medium carbon steel. The first and second order mathematical models, in terms of machining parameters, were developed for surface roughness prediction using response surface methodology (RSM) on the basis of experimental results. The model selected for optimization has been validated with the Chi square test. The significance of these parameters on surface roughness has been established with analysis of variance. An attempt has also been made to optimize the surface roughness prediction model using genetic algorithms (GA). The GA program gives minimum values of surface roughness and their respective optimal conditions.
1、Introduction
End milling is one of the most commonly used metal removal operations in industry because of its ability to remove material faster giving reasonably good surface quality. It is used in a variety of manufacturing industries including aerospace and automotive sectors, where quality is an important factor in the production of slots, pockets, precision and dies. Greater attention is given to dimensional accuracy and surface roughness of products by the industry these days. Moreover, surface finish influences mechanical properties such as fatigue behaviour, wear, corrosion, lubrication and electrical conductivity. Thus, measuring and characterizing surface finish can be considered for predicting machining performance.
摘要： 刀具几何形状对工件表面质量产生的影响是人所共知的，因此，任何成型面端铣设计应包括刀具的几何形状。在当前的工作中，实验性研究的进行已看到刀具几何（径向前角和刀尖半径）和切削条件（切削速度和进给速度） ，对加工性能，和端铣中碳钢影响效果。第一次和第二次为建立数学模型，从加工参数方面，制订了表面粗糙度预测响应面方法（丹参） ，在此基础上的实验结果。该模型取得的优化效果已得到证实，并通过了卡方检验。这些参数对表面粗糙度的建立，方差分析极具意义。通过尝试也取得了优化表面粗糙度预测模型，采用遗传算法（ GA ） 。在加文的程式中实现了最低值，表面粗糙度及各自的值都达到了最佳条件。
1 导言
端铣是最常用的金属去除作业方式，因为它能够更快速去除物质并达到合理良好的表面质量。它可用于各种各样的制造工业，包括航空航天和汽车这些以质量为首要因素的行业，以及在生产阶段，槽孔，精密模具和模具这些更加注重尺寸精度和表面粗糙度产品的行业内。此外，表面光洁度还影响到机械性能，如疲劳性能，磨损，腐蚀，润滑和导电性。因此，测量表面光洁度，可预测加工性能。
车削过程对表面光洁度造成的影响历来倍受研究关注，对于加工过程采用多刀，用机器制造处理，都是研究员需要注意的。由于这些过程涉及大量的参数，使得难以将关联表面光洁度与其他参数进行实验。在这个过程中建模有助于更好的理解。在过去，虽然通过许多人的大量工作，已开发并建立了表面光洁度预测模型，但影响刀具几何方面受到很少注意。然而，除了切向和径向力量，径向前角对电力的消费有着重大的影响。它也影响着芯片冰壶和修改芯片方向人流。此外，研究人员[ 1 ]也指出，在不影响表面光洁度情况下，刀尖半径发挥着重要作用。因此，发展一个很好的模式应当包含径向前角和刀尖半径连同其他相关因素。
对于制造业，建立高效率的加工参数几乎是将近一个世纪的问题，并且仍然是许多研究的主题。获得最佳切削参数，是在制造业是非常关心的，而经济的加工操作中及竞争激烈的市场中发挥了关键作用。在材料去除过程中，不当的选择切削条件造成的表面粗糙度
Influence of tool geometry on the quality of surface produced is well known and hence any attempt to assess the performance of end milling should include the tool geometry. In the present work, experimental studies have been conducted to see the effect of tool geometry (radial rake angle and nose radius) and cutting conditions (cutting speed and feed rate) on the machining performance during end milling of medium carbon steel. The first and second order mathematical models, in terms of machining parameters, were developed for surface roughness prediction using response surface methodology (RSM) on the basis of experimental results. The model selected for optimization has been validated with the Chi square test. The significance of these parameters on surface roughness has been established with analysis of variance. An attempt has also been made to optimize the surface roughness prediction model using genetic algorithms (GA). The GA program gives minimum values of surface roughness and their respective optimal conditions.
1、Introduction
End milling is one of the most commonly used metal removal operations in industry because of its ability to remove material faster giving reasonably good surface quality. It is used in a variety of manufacturing industries including aerospace and automotive sectors, where quality is an important factor in the production of slots, pockets, precision and dies. Greater attention is given to dimensional accuracy and surface roughness of products by the industry these days. Moreover, surface finish influences mechanical properties such as fatigue behaviour, wear, corrosion, lubrication and electrical conductivity. Thus, measuring and characterizing surface finish can be considered for predicting machining performance.
摘要： 刀具几何形状对工件表面质量产生的影响是人所共知的，因此，任何成型面端铣设计应包括刀具的几何形状。在当前的工作中，实验性研究的进行已看到刀具几何（径向前角和刀尖半径）和切削条件（切削速度和进给速度） ，对加工性能，和端铣中碳钢影响效果。第一次和第二次为建立数学模型，从加工参数方面，制订了表面粗糙度预测响应面方法（丹参） ，在此基础上的实验结果。该模型取得的优化效果已得到证实，并通过了卡方检验。这些参数对表面粗糙度的建立，方差分析极具意义。通过尝试也取得了优化表面粗糙度预测模型，采用遗传算法（ GA ） 。在加文的程式中实现了最低值，表面粗糙度及各自的值都达到了最佳条件。
1 导言
端铣是最常用的金属去除作业方式，因为它能够更快速去除物质并达到合理良好的表面质量。它可用于各种各样的制造工业，包括航空航天和汽车这些以质量为首要因素的行业，以及在生产阶段，槽孔，精密模具和模具这些更加注重尺寸精度和表面粗糙度产品的行业内。此外，表面光洁度还影响到机械性能，如疲劳性能，磨损，腐蚀，润滑和导电性。因此，测量表面光洁度，可预测加工性能。
车削过程对表面光洁度造成的影响历来倍受研究关注，对于加工过程采用多刀，用机器制造处理，都是研究员需要注意的。由于这些过程涉及大量的参数，使得难以将关联表面光洁度与其他参数进行实验。在这个过程中建模有助于更好的理解。在过去，虽然通过许多人的大量工作，已开发并建立了表面光洁度预测模型，但影响刀具几何方面受到很少注意。然而，除了切向和径向力量，径向前角对电力的消费有着重大的影响。它也影响着芯片冰壶和修改芯片方向人流。此外，研究人员[ 1 ]也指出，在不影响表面光洁度情况下，刀尖半径发挥着重要作用。因此，发展一个很好的模式应当包含径向前角和刀尖半径连同其他相关因素。
对于制造业，建立高效率的加工参数几乎是将近一个世纪的问题，并且仍然是许多研究的主题。获得最佳切削参数，是在制造业是非常关心的，而经济的加工操作中及竞争激烈的市场中发挥了关键作用。在材料去除过程中，不当的选择切削条件造成的表面粗糙度
