A novel wind turbine bearing fault diagnosis method based on Integral Extension LMD

被引：55

作者：

Liu, W. Y. ^{[1
,2
]}

Gao, Q. W. ^{[1
]}

Ye, G. ^{[1
]}

Ma, R. ^{[1
]}

Lu, X. N. ^{[1
]}

Han, J. G. ^{[1
]}

机构：

[1] Jiangsu Normal Univ, Sch Mech & Elect Engn, Xuzhou 221116, Peoples R China

[2] Case Western Reserve Univ, Dept Mech & Aerosp Engn, Cleveland, OH 44106 USA

来源：

MEASUREMENT | 2015年 / 74卷

基金：

中国国家自然科学基金;

关键词：

Integral Extension Local Mean Decomposition (IELMD); Wind turbine; End effect; LMD; Fault diagnosis; DECOMPOSITION;

D O I：

10.1016/j.measurement.2015.06.005

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper proposed a novel wind turbine ball bearing fault diagnosis method based on Integral Extension Local Mean Decomposition (IELMD). Wind turbine vibration signal has the characteristic of non-Gaussian and non-stationary. Some typical time-frequency analysis methods cannot achieve ideal effects. A new method named LMD can deal with non-stationary signals and can extract obvious features. The IELMD method is proposed based on the integral local waveform matching of the right and left side of the original signal, in order to suppress the end effect of LMD method itself. Firstly, all the extreme points are scanned out, in which the left three points and right three points are specially marked. Secondly, two characteristic waveforms and two matching waveforms are established at both the left and right side. Finally, both the left and right matching waveforms are extended to finish the LMD process. The wind turbine bearing fault diagnosis experimental can improve the efficiency and validity of the novel IELMD method. (C) 2015 Elsevier Ltd. All rights reserved.

引用

页码：70 / 77

页数：8

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