Induction Motors Fault Detection Using Square-Root Transformed Cubature Quadrature Kalman Filter
IEEE Transactions on Energy Conversion
broken rotor bars, cubature quadrature Kalman filter, fault detection, Induction motors, square root, state estimation
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.
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.