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Mathematical Problems in Engineering
Volume 2015, Article ID 101757, 6 pages
http://dx.doi.org/10.1155/2015/101757
Research Article

Mechanical Fault Diagnosis for HV Circuit Breakers Based on Ensemble Empirical Mode Decomposition Energy Entropy and Support Vector Machine

1HLJ Province Key Lab of Senior-Education for Electronic Engineering, Heilongjiang University, Harbin 150080, China
2College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China

Received 8 April 2015; Revised 19 June 2015; Accepted 28 June 2015

Academic Editor: Jean-Charles Beugnot

Copyright © 2015 Jianfeng Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

During the operation process of the high voltage circuit breaker, the changes of vibration signals can reflect the machinery states of the circuit breaker. The extraction of the vibration signal feature will directly influence the accuracy and practicability of fault diagnosis. This paper presents an extraction method based on ensemble empirical mode decomposition (EEMD). Firstly, the original vibration signals are decomposed into a finite number of stationary intrinsic mode functions (IMFs). Secondly, calculating the envelope of each IMF and separating the envelope by equal-time segment and then forming equal-time segment energy entropy to reflect the change of vibration signal are performed. At last, the energy entropies could serve as input vectors of support vector machine (SVM) to identify the working state and fault pattern of the circuit breaker. Practical examples show that this diagnosis approach can identify effectively fault patterns of HV circuit breaker.