Rotor resistance estimation using EKF for the rotor fault diagnosis in sliding mode control induction motor

The aim of this paper is the diagnosis of the rotor fault of squirrel cage induction motor controlled in sliding-mode (SMC). The faulty identification in this case is very difficult, due to the action of the control loop (SMC). Motor current signature analysis (MCSA) is the most widely used method for the faults identification in induction motors. This method generally suffers from load disturbance, speed variation. A broken rotor bar essentially leads to an increase in the rotor resistance of the induction motor. This paper present a method of broken rotor bars diagnosis based on the estimation of the rotor resistance using an Extended Kalman filter (EKF) and the spectrum analysis of stator current. The simulation results show that the presented algorithm is effective and accurate.

• rotor resistance estimation
• broken rotor bars
• squirrel cage induction motor
• sliding mode control
• extended Kalman filter
• motor current signature analysis
• fault diagnosis
• load disturbance

• Machine Fault Diagnosis Techniques
• Sensorless Control of Electric Motors
• Electric Motor Design and Analysis
• rotor resistance estimation
• broken rotor bars
• squirrel cage induction motor
• sliding mode control
• extended Kalman filter
• motor current signature analysis
• fault diagnosis
• load disturbance
• Control and Systems Engineering
• Electrical and Electronic Engineering
• Engineering