Earticle

초록

영어

In order to guarantee the effectiveness of the CNC system and reach expected reliability level, reliability prediction model was established for the CNC system by BP neural network algorithm based on the particle swarm optimization. The weight and threshold value of BP neural network were optimized with the particle swarm optimization algorithm, the three-layer BP neural network prediction model was established, and practical failure data verification was conducted for the model established. Through the simulation verification, the result suggested that this scheme is accurate and effective. The improved algorithm improves the convergence rate and BP network learning ability, carries out successful prediction for the reliability of the CNC system, and provides basis for the design decision of the CNC system.

목차

Abstract
 1. Introduction
 2. Establishment of the reliability prediction model for CNC system
 3. Improved BP neural network algorithm
  3.1.BP neural network
  3.2.Improved BP Neural network based on the particle swarm optimization
 4. Application example
 5. Result analysis
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Yan Gu [ College of Mechanical Science and Engineering, Jilin University Changchun, Jilin (China), Ningbo Institute of Technology, Zhejiang University Ningbo, Zhejiang(China) ]
• Yiqiang Wang [ Ningbo Institute of Technology, Zhejiang University Ningbo, Zhejiang(China) ] Corresponding Author
• Xiaoqin Zhou [ College of Mechanical Science and Engineering, Jilin University Changchun, Jilin (China) ]
• Xiuhua Yuan [ Ningbo Institute of Technology, Zhejiang University Ningbo, Zhejiang(China) ]
• Mingyang Ma [ College of Mechanical Science and Engineering, Jilin University Changchun, Jilin (China) ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605