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基于AdvantEdge加工的M2高速钢微铣削力仿真与预测 被引量:2

Simulation and Prediction of Micro-Milling Force of M2 High-Speed Steel Based on AdvantEdge Machining
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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。 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.
作者 叶文珺 钱炜 YE Wenjun;QIAN Wei(School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093.China)
出处 《轻工机械》 CAS 2022年第5期81-85,共5页 Light Industry Machinery
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 micro-milling machining M2 high-speed steel cutting force AdvantEdge multiple linear regression prediction orthogonal experiment
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