An Adaptive Kalman Filter-Based Condition-Monitoring Technique for Induction Motors

Health Condition Monitoring of Induction Motors

Induction motors (IMs) are commonly used in various industrial applications. A spectrum synch (SS) technique is proposed in this chapter for early IM defect detection using electric current signals; fault detection in this work will focus on defects in rolling element bearings and rotor bars, which together account for more than half of IM imperfections. In bearing fault detection, the proposed...

An indirect adaptive neuro-fuzzy speed control of induction motors

This paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. The uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. The contribution of this paper is presenting a stability analysis for neuro-fuzzy speed control of inducti...

Extended Kalman Filter Based Fuzzy Adaptive Filter

Stator Fault Detection in Induction Machines by Parameter Estimation Using Adaptive Kalman Filter

This paper presents a parametric low differential order model, suitable for mathematically analysis for Induction Machines with faulty stator. An adaptive Kalman filter is proposed for recursively estimating the states and parameters of continuous–time model with discrete measurements for fault detection ends. Typical motor faults as interturn short circuit and increased winding resistance ...

Doppler and bearing tracking using fuzzy adaptive unscented Kalman filter

The topic of Doppler and Bearing Tracking (DBT) problem is to achieve a target trajectory using the Doppler and Bearing measurements. The difficulty of DBT problem comes from the nonlinearity terms exposed in the measurement equations. Several techniques were studied to deal with this topic, such as the unscented Kalman filter. Nevertheless, the performance of the filter depends directly on the...