Earticle

초록

영어

In order to meet the high cutting rate and high surface quality requirement, put forward the fuzzy control, on-line adjusting the cutting feed rate method to realize a constant force in CNC high speed milling. The input variables of a fuzzy controller are the difference between the reference forces and the actual cutting forces and the change rate of the deviation, after fuzzification, fuzzy inference and defuzzification, the output variable is the change of per tooth feed. The control strategy of on-line adjusting fuzzy rules and on-line self-adaptiving the output scaling factor is used in a fuzzy controller. The CNC high speed milling process model is established by 3-3-5-1 type BP neural network, and the input variables are cutting parameters, and the output variable is the actual cutting forces. Combining the fuzzy controller and the BP neural network, high speed milling constant force control model is constructed. By simulation and practical verification, metal removal rate is increased significantly, and the surface quality is improved substantially.

목차

Abstract
 1. Introduction
 2. Design of the Fuzzy Control Algorithm
  2.1 Fuzzification
  2.2 Fuzzy inference
  2.3 Defuzzification
 3. High-speed Milling Process Modeling Based on Neural Network
 4. Fuzzy Control Constant Force Simulation Based on Matlab/Simulink
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Yunlin Huang [ School of Mechanical Engineering, Nanjing University of Science and Technology Nanjing 210094, China ]
• Juntang Yuan [ School of Mechanical Engineering, Nanjing University of Science and Technology Nanjing 210094, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605