Earticle

초록

영어

To deal with the noise from rotating machinery vibration signal and analysis the fault signal, a rotating machinery fault diagnosis method based on enforced de-noising and modified EMD is proposed. Firstly, fault signals were de-noised by the wavelet with enforced threshold in order to filter the noises in the high frequency, and then the EMD method used to decompose the fault signals into a finite number of stationary intrinsic mode function (IMFs), then the linear correlation coefficient between two sets of data is proposed to select the useful IMF. In order to restrain the endpoint effect of EMD, in this paper, the cosine window function is employ to the fault signals, and then the envelope error of the fault signals is controlled at the both endpoints of the vibration signals. Experimental results shows: this proposed method can extract the fault information effectively, with overcoming the drawbacks of EMD well.

목차

Abstract
 1. Introduction
 2. Algorithm Description Enforced De-noising and Modified EMD
  2.1. Continuous Wavelet Transform
  2.2. EMD Method
  2.3. Cosine Window Based Endpoint Processing
  2.4. Linear Relation Measurement
 3. Experimental Setup
  3.1. Experimental Platform
  3.2. Experimental Data
 4. Discussions and Analysis
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• He jun [ Guangdong University of Petrochemical of Technology, Maoming, Guangdong, 525000 ]
• Qinghua Zhang [ Guangdong University of Petrochemical of Technology, Maoming, Guangdong, 525000 ]
• Guoxi Sun [ Guangdong University of Petrochemical of Technology, Maoming, Guangdong, 525000 ]
• Ji-cheng Yang [ South China University of Technology School of Electronic and Information Engineering, Guangzhou, China ]
• Jianbin Xiong [ Guangdong University of Petrochemical of Technology, Maoming, Guangdong, 525000 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605