Earticle

초록

영어

All Electric Ship Power System (AESPS) is constituted by the core power plant system with marine generators and large power propulsion motors, and by the electrical apparatus, which is set up for providing energy for other parts of ship and transmission. Effective fault diagnosis of AESPS is the technical prerequisite to drive electric ship safely and to avoid accidents. In this paper, we used the wavelet packet transform (WPT) to separate signal from noise, and extracted the fault feature information submerged in the noise. After that, we used the Ensemble Empirical Mode Decomposition (EEMD) to analyze the reconstructed signal to get several intrinsic mode functions (IMF). Finally, we obtained the marginal spectrum through the Hilbert-Huang transform (HHT). Theoretical and experimental study results show in the end: the marginal spectrum, with WPT-EEMD method, underlines the fault feature information of power system, which is an effective way to diagnose the fault type.

목차

Abstract
 1. Introduction
 2. Denoising principle of Wavelet Packet
  2.1. Denoising Steps of Wavelet Packet Threshold
  2.2. The Selection of Threshold Function
 3. Introduction of EEMD methods
  3.1. EEMD Decomposition
  3.2. Hilbert Spectrum
 4. Research on the Application of WPT-EEMD Method in the Fault Diagnosis of AESPS
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Bao Yan [ Logistics Engineering College, Shanghai Maritime University ]
• Shi Weifeng [ Logistics Engineering College, Shanghai Maritime University ]
• Chen Peichen [ Logistics Engineering College, Shanghai Maritime University ]
• Ding Qiuyi [ Logistics Engineering College, Shanghai Maritime University ]
• Zhu Chen [ Logistics Engineering College, Shanghai Maritime University ]

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