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虚拟数控铣削表面粗糙度预测技术研究
引用本文:隋秀凛,杨小萍,张家泰,葛江华.虚拟数控铣削表面粗糙度预测技术研究[J].系统仿真学报,2008,20(19):5113-5116,5130.
作者姓名:隋秀凛  杨小萍  张家泰  葛江华
作者单位:哈尔滨工程大学机电工程学院,哈尔滨理工大学机械动力工程学院
基金项目:黑龙江省自然科学基金,黑龙江省教育厅自然科学基金
摘    要:分析了影响数控铣削加工表面粗糙度的主要因素,利用多元回归分析建立了基于球头铣刀的表面粗糙度关于其影响因素的数学模型.经显著性检验,该模型预测精度高,泛化能力强.该模型为虚拟数控铣削表面粗糙度预测的建模提供了理论依据.开发了基于DELPHI的可视化交互式的仿真系统,实现了虚拟数控铣床的表面粗糙度的在线预测.有助于理解表面粗糙度随铣削参数改变的规律,也为铣削参数优化提供理论依据.

关 键 词:虚拟数控铣削  表面粗糙度  预测技术  多元回归

Study of Predicted Technology on Surface Roughness in Virtual Numerical Control Milling
SUI Xiu-lin,YANG Xiao-ping,ZHANG Jia-tai,GE Jiang-hua.Study of Predicted Technology on Surface Roughness in Virtual Numerical Control Milling[J].Journal of System Simulation,2008,20(19):5113-5116,5130.
Authors:SUI Xiu-lin  YANG Xiao-ping  ZHANG Jia-tai  GE Jiang-hua
Abstract:The critical influence factors of surface roughness were analyzed in Numerical Control (NC) milling and mathematic model about surface roughness on influence factors was established by multiple regression, which has an ability of high prediction and strong generalization by significance test. This model provides technical support for surface roughness prediction model in virtual NC milling. A simulation system was developed based on DELPHI, which has an ability of interactive and visualization, and can predict surface roughness of virtual NC milling machine tool online. It helps to correctly understand the rule that surface roughness changes with milling parameters, and provides theoretical basis for optimizing milling parameters.
Keywords:virtual NC milling  surface roughness  predicted technology  multiple regression
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