Earticle

초록

영어

Extension neural network is a new type of neural network that combines extension theory and artificial neural network. Extension neural network has been applied to pattern recognition, fault diagnosis and clustering. According to fault characteristics of rolling bearing, we propose a fault diagnostic method for rolling bearing based on extension neural network. We construct the fault diagnosis model based on extension neural network along with the learning algorithm, which are then applied to fault recognition of rolling bearing. Simulation experiment indicates that this algorithm is easy to implement and has small training error and fast convergence speed. The algorithm has both theoretical and practical value.

목차

Abstract
 1. Introduction
 2. Fault Diagnostic Methods for Rolling Bearing
 3. Extension Neural Network
 4. Simulation Experiment and Analysis
  4.1. Data Processing
  4.2. Network Training
  4.3. Comparative Analysis
 5. Conclusion
 References

키워드

저자

• Zhang Su [ College of Mechanical and Electrical Engineering, Agriculture University of Hebei, Baoding, Hebei, China ]
• Zheng Ying [ College of Mechanical and Electrical Engineering, Agriculture University of Hebei, Baoding, Hebei, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605