On the Use of Spectral Kurtosis for Diagnosis of Electrical Machines

被引：0

作者：

Fournier, E. ^{[1
,2
,3
,4
,5
]}

Picot, A. ^{[1
,2
,3
,4
,5
]}

Regnier, J. ^{[1
,2
,3
,4
,5
]}

Yamdeu, M. Tientcheu ^{[6
]}

Andrejak, J-M. ^{[6
]}

Maussion, P. ^{[1
,2
,3
,4
,5
]}

机构：

[1] Univ Toulouse, 2 Rue Charles Camichel,BP 7122, F-31071 Toulouse 7, France

[2] UPS, INPT, F-31071 Toulouse 7, France

[3] LAPLACE Lab Plasma & Convers Energie, F-31071 Toulouse 7, France

[4] ENSEEIHT, F-31071 Toulouse 7, France

[5] CNRS, LAPLACE, F-31071 Toulouse, France

[6] Moteurs LEROY SOMER, F-16000 Angouleme, France

来源：

2013 9TH IEEE INTERNATIONAL SYMPOSIUM ON DIAGNOSTICS FOR ELECTRIC MACHINES, POWER ELECTRONICS AND DRIVES (SDEMPED) | 2013年

关键词：

Spectral Kurtosis; Electrical Machine Diagnosis; Statistical Analysis;

D O I：

暂无

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：

This paper explores the efficiency of Spectral Kurtosis (SK) in the area of electrical machines diagnosis. In the literature, Spectral Kurtosis is mainly presented as a tool used to detect non-stationary components in a signal. However, classical use of SK is unsuitable for detection of new stationary components or slow evolutions in a spectrum. In order to detect different types of faults, three indicators are designed from the original definition of the Spectral Kurtosis. These indicators are first tested and compared on synthetic signals. Then, their performance are demonstrated for unbalance detection in a Induction Machine (IM) using current signal.

引用

页码：77 / 84

页数：8

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