Fault Feature Extraction Based on Improved EEMD and Hilbert Transform

Pei Guo Hou; Qian Zhou; Zhong Dong Wang

doi:10.4028/www.scientific.net/AMR.314-316.1126

Paper Titles

Experimental Research on Ultrasonic Vibration Deep Hole Honing of Titanium Alloy
p.1107

Preparation of Water-Based No-Clean Flux for High Temperature Lead-Free Solder
p.1112

Design and Research on the Refitment of Deep-Hole Machine Tool
p.1117

Anisotropy of Deformation Behavior of AZ31 Magnesium Alloy Sheets
p.1121

Fault Feature Extraction Based on Improved EEMD and Hilbert Transform
p.1126

Study on Material Removal in Electrorheological Fluid-Assisted Polishing
p.1131

Analysis of Forming Mechanism of Thermal Damages on Friction Surfaces of Brake Disc
p.1135

Study on Wear Properties and Mechanisms of Coated Carbide Tools in Dry Turning of 300M Steel
p.1142

Numerical Analysis of Stress Field for Simulating Pressure Vessel Nozzles
p.1146

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 314-316Fault Feature Extraction Based on Improved EEMD...

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.

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Advanced Manufacturing Technology, ADME 2011

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Periodical:

Advanced Materials Research (Volumes 314-316)

Pages:

1126-1130

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.314-316.1126

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Online since:

August 2011

Authors:

Pei Guo Hou, Qian Zhou, Zhong Dong Wang

Keywords:

End Effect, Ensemble Empirical Mode Decomposition (EEMD), Hilbert Transform, Mirror Extension, SVR

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