Wavelet and PDD as fault detection techniques

被引：24

作者：

Cusido, J. ^{[1
]}

Romeral, L. ^{[1
]}

Ortega, J. A. ^{[1
]}

Garcia, A. ^{[1
]}

Riba, J. R. ^{[1
]}

机构：

[1] UPC, Dept Elect Engn, MCIA Res Grp, Terrassa 08222, Catalunya, Spain

来源：

ELECTRIC POWER SYSTEMS RESEARCH | 2010年 / 80卷 / 08期

关键词：

Rotating machinery; Current analysis; Fault detection; Signal processing; Wavelet transform; SIGNATURE ANALYSIS; INDUCTION-MOTORS; DIAGNOSIS; ROTOR; BAR;

D O I：

10.1016/j.epsr.2009.12.017

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Motor current signature analysis has been successfully used for fault diagnosis in induction machines However, this method does not always achieve good results with variable load torque This paper proposes a different signal processing method, which combines wavelet and power spectral density techniques giving the power detail density as a fault factor The method shows good theoretical and experimental results (C) 2010 Elsevier B V All lights reserved

引用

页码：915 / 924

页数：10

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