Earticle

초록

영어

A modified method for ensemble empirical mode decomposition (MEEMD) is studied in this paper. Mutual information is applied to the algorithm, and the decomposition effect is improved. Two white noises with opposite signs are added to the original signal, and the mode mixing problem is inhibitted. False IMFs are eliminated by the mutual information operation after average calculating procedure is processed. The available intrinsic mode functions are retained by comparing the mutual information with the threshold. Simulated analysis illustrates that the modified algorithm has better decomposition effect. The new algorithm has been used to fault diagnosis for the rolling bearing, and the decomposition results are shown. To the vibration signal, the envelope spectrums for two different algorithms are given. The detailed analysis is carried out. Experiment results show that the modified algorithm has better performance, and the decomposition effect is optimal.

목차

Abstract
 1. Introduction
 2. Mutual Information
 3. The MEEMD Algorithm
  3.1. The EEMD Algorithm
  3.2. The MEEMD Algorithm
 4. Simulation and Analysis
 5. Application Study
 6. Conclusions
 Acknowledgements
 References

키워드

저자

• Xiangbin Sun [ Electrical ＆Electionic Experment Training Center, Yantai University, Yantai, 264005, China ]
• Guang Yang [ Electrical ＆Electionic Experment Training Center, Yantai University, Yantai, 264005, 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