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  • 中国标准连:ISSN1005-2895
  • 续出版物号: CN 33-1180/TH
  • 主管单位:轻工业杭州机电设计研究院有限公司
  • 主办单位:轻工业杭州机电设计研究院有限公司、中国轻工机械协会、中国轻工业机械总公司
  • 社  长:刘安江
  • 主  编:黄丽珍
  • 地  址:杭州市余杭区高教路970号西溪联合科技广场4-711
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叶文珺, 钱炜.基于AdvantEdge加工的M2高速钢微铣削力仿真与预测[J].轻工机械,2022,40(5):81-85
基于AdvantEdge加工的M2高速钢微铣削力仿真与预测
Simulation and Prediction of Micro Milling Force of M2 High Speed Steel Based on AdvantEdge Machining
  
DOI:10.3969/j.issn.1005 2895.2022.05.012
中文关键词:  微铣削加工  M2高速钢  切削力  AdvantEdge  多元线性回归预测  正交试验
英文关键词:micro milling machining  M2 high speed steel  cutting force  AdvantEdge  multiple linear regression prediction  orthogonal experiment
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作者单位
叶文珺, 钱炜 上海电气慧程智能系统有限公司 上海201615 
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中文摘要:
      微织构的加工领域中常用到激光加工,但激光加工设备成本高且无法进行大规模生产,因此文中用已发展成熟的加工中心来对高速钢进行铣削加工。采用0.3 mm的硬质合金微小径铣刀,利用数控加工中心对M2高速钢进行微沟槽铣削加工;在微铣削加工中,铣削力过大会导致铣刀磨损过快影响加工质量,因此笔者利用仿真软件AdvantEdge对微铣削加工进行仿真;由于微细铣削不同于传统铣削,分析了刀具前角以及刀刃圆弧半径对铣削力的影响,并利用正交实验的方法,研究切削参数及刀具几何参数对铣削力的影响规律;采用MATLAB多元线性回归对铣削力进行预测;最后通过一组实验对预测模型进行验证。结果表明构建的模型对铣削力的预测较为准确,误差在10%以内。该研究方法有助于在实际加工中更高效、更便捷地选用合适的切削用量。
英文摘要:
      Laser machining, which is commonly used in micro texture milling, cannot be produced on a large scale due to the high cost of the equipment. Therefore, mature machining center is used to mill high speed steel. The micro groove milling of M2 high speed steel was carried out by CNC machining center with a 0.3 mm carbide micro diameter milling cutter. Due to the fact that in micro milling, the excessive milling force will cause the milling cutter to wear too quickly and affect the processing quality, the simulation software AdvantEdge was adopted to simulate micro milling machining. Since micro milling is different from traditional milling, the influence of the tool angle and the radius of the cutting edge arc on the milling force was analyzed. Using the method of orthogonal experiments, the influence of process parameters and tool geometry parameters on milling force was studied. MATLAB multivariate linear regression was used to predict the milling force, and finally a set of experiments were carried out to verify the prediction model. The results show that the built model can predict the milling force accurately with an error less than 10%. The research method is beneficial for selecting the suitable cutting amount more efficiently and conveniently in practical machining.
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