Induction Motors Fault Detection Using Square-Root Transformed Cubature Quadrature Kalman Filter
Document Type
Article
Publication Date
6-1-2019
Publication Title
IEEE Transactions on Energy Conversion
Volume
34
Issue
2
First Page
870
Keywords
broken rotor bars, cubature quadrature Kalman filter, fault detection, Induction motors, square root, state estimation
Last Page
877
Abstract
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.
DOI
10.1109/TEC.2018.2877781
ISSN
08858969
Recommended Citation
Zarei, Jafar; Kowsari, Elham; and Razavi-Far, Roozbeh. (2019). Induction Motors Fault Detection Using Square-Root Transformed Cubature Quadrature Kalman Filter. IEEE Transactions on Energy Conversion, 34 (2), 870-877.
https://scholar.uwindsor.ca/electricalengpub/129
