A novel integral extension LMD method based on integral local waveform matching

被引：4
作者：
Liu, W. Y. [1 ,2 ]
Zhou, L. Q. [1 ]
Hu, N. N. [1 ]
He, Z. Z. [1 ]
Yang, C. Z. [1 ]
Jiang, J. L. [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：
NEURAL COMPUTING & APPLICATIONS | 2016年 / 27卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Integral extension; Integral local waveform matching; Local mean decomposition (LMD); End effect; DECOMPOSITION;
D O I：
10.1007/s00521-015-1894-z
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposed a novel integral extension local mean decomposition (IELMD) method, which can be widely applied in wind turbine fault diagnosis. Firstly, the characteristic waveform and its corresponding integral values are calculated. Then, the similar waveform is established according to signal extreme points and their integral values. The similar waveform and characteristic waveform are compared in order to obtain an optimal waveform, which can match the characteristic waveform in the best way. Finally, the optimal waveform is used to extend the left side and right side of the original signal. According to the simulation experimental analysis, the novel IELMD method is reasonable and effective in suppressing LMD end effect, and this method can be applied in wind turbine fault diagnosis.
引用
收藏
页码：761 / 768
页数：8
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