Detection of broken bars in induction motor using the Extended Kalman Filter (EKF)

Abstract

Estimation of rotor resistance rapidly and accurately has received a lot of attention due to its significance in improving the performance of Induction Motor (IM). This paper deals with the diagnostic of broken bars in induction motors. The hypothesis on which detection is based is that the apparent rotor resistance of an induction motor will increase when a rotor bar breaks. To detect rotor fault we propose an Extended Kalman Filter approach for rotor resistance estimation. In particular, rotor resistance is estimated and compared with its nominal value to detect broken bars.

Deep machine learning with grey wolf algorithm and central deference Kalman filter based broken rotor bars detection in induction motor

“…IMs are defined via fifth-order nonlinear differential equations with two control variables (voltages of the stator), four electrical variables (fluxes and currents) and one mechanical variable (speed of the rotor) [23]. In axes a − −b set in the stator, the voltages of the stator and the states can be:…”

“…IMs are defined via fifth‐order nonlinear differential equations with two control variables (voltages of the stator), four electrical variables (fluxes and currents) and one mechanical variable (speed of the rotor) [23]. In axes $$a - - b$$ set in the stator, the voltages of the stator and the states can be: $$\begin{equation}{Z^T} = [ {{i_a} {i_b}{\varphi _a}{\varphi _{b }}\omega } ] \end{equation}$$ $$\begin{equation} {U^T} = [ {{u_a} {u_b}} ] \end{equation}$$ $$\begin{equation} Y = [ {{i_a} {i_b}} ] \end{equation}$$…”

Diagnosis of inter-turn short-circuit faults and power supply faults of a PMSM controlled by input-output linearization without speed sensor

“…Therefore, in this situation, using observers, a model-based or parametric approach to diagnosis is required. Many other observer architectures, including the sliding mode observer, MRAS, the Luenberger observer, and the Extended Kalman Filter (EKF), have been proposed in the literature [17,20]. An excellent optimal estimate of states or parameters for nonlinear systems is provided by the EKF, a stochastic observer.…”