Earticle

초록

영어

Acoustic Emission (AE) source localization is a useful implement to diagnose the incipient faults in rotating machine. This paper proposes an improved Near-field Multiple Signal Classification method using four-order cumulants (NFC-MUSIC) to accurately locate the faults position. In order to overcome dispersion effect and revised velocity, the feature sub narrow band is extracted by Wavelet Packet reconstitution (WPR) and Modal Plate Wave Theory (MPWT). For multi-source decorrelation and increasing localized resolution, the four-order cumulants of observed signal can be selected for localization. The experiment results indicate that the improved method can accurately locate multi-rubbing faults. It is an efficient way to assist incipient rubbing faults diagnosis.

목차

Abstract
 1. Introduction
 2. The Pre-Processing of AE Signals
 3. The Proposed AE Source Localization Algorithm
 3. Experiments
 4. Simulations and Evaluations
  4.1. WPT for Zero-Order Modal Extraction
  4.2. NFC-MUSIC Algorithm Localization Results
 5. Conclusions
 References

키워드

저자

• Jing Li [ School of Information Engineering, Southeast University, Nanjing, China ]
• Yong Yang [ School of Resources and Geosciences, China University of Mining and Technology, Xuzhou, China / School of Information and Electrical Engineering, Xuzhou, China ]
• Xinghua Li [ Chengdu BOE Optoelectronics Technology Co., Ltd., Chengdu, China ]
• Li Zhao [ School of Information Engineering, Southeast University, Nanjing, China ]

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