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Wireless Personal Communications
Published in: Wireless Personal Communications 1/2018

02-03-2018

Feature Extraction Method for Condition Monitoring of Rolling Element Bearings Based on Dual-Tree Complex Wavelet Packet Transform and VMD

Authors: Qiming Niu, Qingbin Tong, Junci Cao, Feng Liu, Yihuang Zhang

Published in: Wireless Personal Communications | Issue 1/2018

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Abstract

The feature extraction of rolling element bearings vibration signals is one of the key issue for high-speed rotating machinery condition monitoring. A new scheme based on Dual-Tree Complex Wavelet Packet Transform (DTCWPT) and Variational Mode Decomposition (VMD) for extracting vibration condition monitoring feature is proposed. First, DTCWPT is used to reduce noise and pseudo frequency components from vibration signals by the energy ratio. Second, a set of Intrinsic Mode Function components (IMFs) can be got by VMD. Then, the energy ratio between the screening vibration signal and IMFs are calculated. And, the corresponding IMFs are selected according to the energy ratio threshold. Finally, applying the spectrum analysis technology, the condition monitoring feature can be extracted from the reconstructing signal. The experimental results of simulation signals and practical rolling element bearings vibration signals show that the scheme is feasible and effective for extracting the bearings operation state feature.
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Metadata
Title
Feature Extraction Method for Condition Monitoring of Rolling Element Bearings Based on Dual-Tree Complex Wavelet Packet Transform and VMD
Authors
Qiming Niu
Qingbin Tong
Junci Cao
Feng Liu
Yihuang Zhang
Publication date
02-03-2018
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 1/2018
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-018-5480-4

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