Induction Motors Fault Detection Using Square-Root Transformed Cubature Quadrature Kalman Filter

被引：29

作者：

Zarei, Jafar ^{[1
]}

Kowsari, Elham ^{[1
]}

Razavi-Far, Roozbeh ^{[2
]}

机构：

[1] Shiraz Univ Technol, Dept Control Engn, Sch Elect & Elect Engn, Shiraz 715555313, Iran

[2] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada

来源：

IEEE TRANSACTIONS ON ENERGY CONVERSION | 2019年 / 34卷 / 02期

关键词：

Induction motors; fault detection; broken rotor bars; state estimation; cubature quadrature Kalman filter; square root; BROKEN ROTOR BARS;

D O I：

10.1109/TEC.2018.2877781

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper proposes a novel approach for simultaneous state estimation and broken rotor bars (BRBs) detection in induction motors. The proposed method is named square-root transformed cubature quadrature Kalman filter (SR-TCQKF). The accuracy of the filter has been improved by a transformation on the filter's sigma points, whereas the filter becomes more stable due to the use of the SR version of the covariance matrix. Accordingly, the SR-TCQKF is more accurate and stable than the standard cubature quadrature Kalman filter. The efficiency of the SR-TCQKF has been evaluated for speed estimation and BRB detection in induction motors. The attained results showthe efficiency of the proposed approach.

引用

页码：870 / 877

页数：8

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