Paper Title:
Fault Feature Extraction Based on Improved EEMD and Hilbert Transform
  Abstract

Ensemble Empirical Mode Decomposition (EEMD) can overcome the mode mixing problem in Empirical Mode Decomposition (EMD) effectively. The Hilbert-Huang transform still exists end effect in applications, in order to improve the end effect, this paper put forward a method of fault feature extraction based on improved EEMD and Hilbert transform which combines support vector regression (SVR) machine with mirror extension to continue the signal. The analysis on simulation experiments results show that the method can restrain the end effect effectively, get a more accurate instantaneous frequency and instantaneous amplitude.

  Info
Periodical
Advanced Materials Research (Volumes 314-316)
Chapter
Mechanical Behavior & Fracture
Edited by
Jian Gao
Pages
1126-1130
DOI
10.4028/www.scientific.net/AMR.314-316.1126
Citation
P. G. Hou, Q. Zhou, Z. D. Wang, "Fault Feature Extraction Based on Improved EEMD and Hilbert Transform", Advanced Materials Research, Vols. 314-316, pp. 1126-1130, 2011
Online since
August 2011
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Price
$32.00
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