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

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 th...

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Bibliographic Details
Published in:IEEE transactions on energy conversion 2019-06, Vol.34 (2), p.870-877
Main Authors: Zarei, Jafar, Kowsari, Elham, Razavi-Far, Roozbeh
Format: Article
Language:English
Subjects:
Bars
broken rotor bars
Covariance matrices
Covariance matrix
cubature quadrature Kalman filter
Fault detection
Induction motors
Kalman filters
Resistance
Rotors
square root
State estimation
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Summary: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 show the efficiency of the proposed approach.
ISSN:0885-8969
1558-0059
DOI:10.1109/TEC.2018.2877781