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The Study of Variational Feed Rate in 4-Axis Machining of Blades

  • Qing-Chun TangEmail author
  • Shao-Hui Yin
  • Jun-Xiao Geng
  • Hu Luo
  • Yue-Ping Chen
Regular Paper
  • 103 Downloads

Abstract

As a core part of aerospace, space, and steam turbine plants, blades are generally machined via 5-axis linkage processing to satisfy the high precision requirements of the rigorous surface. To save costs in blade machining, many small- and medium-sized enterprises often combine standard 3-axis computer numeric control machines with the automatic indexing turntable. The traditional 4-axis machining method adopts a constant feed rate, which causes overcutting near the leading and trailing edges of the blade because of the rapid changes in tool orientation. To solve this problem, we propose a speed optimization method that utilizes variational speed to ensure that the decomposition velocity and acceleration of each axis do not exceed the allowable values. First, we guarantee the correct tool lead angle. Second, a corrected speed model is established to obtain the component speed of each axis and to determine the constraint conditions of maximum and accelerated speed. Third, a 4-axis post processor for blade processing is developed using Java advanced language combined with the optimization algorithm. The cutting experiment reveals that our proposed speed optimization method effectively controls the precision of the surface profile and overcomes the overcut phenomenon that often occurs in traditional 4-axis machining.

Keywords

Blade 4-Axis machining Overcutting Variational speed rate Optimization 

Nomenclature

is, im, ie

Cutter axis vector

ps, pm, pe

The contact point

ns, nm, ne

The normal vector of the contact point Cutter axis vector

ks, km, ke

The tangential vector of the contact point Cutter axis vector

β

Lead angle

X, Y, Z

Linear axes

A

Rotary axis

F

Program feed rate

V

Path feed

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Copyright information

© Korean Society for Precision Engineering and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.National Engineering Research Center for High Efficiency GrindingHunan UniversityChangShaChina
  2. 2.Engineering Training CenterGuangxi University of Science and TechnologyLiuzhouChina

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