Online condition monitoring of induction motors through signal processing

Abstract

Induction motor is critical component in many power plants & industrial processes and is frequently integrated in commercially available equipment. Safety, reliability, efficiency and performance are some of the major concerns of induction motor applications. Due to high reliability requirements, and cost of breakdown, the issue of condition monitoring of induction motors and diagnosis is of increasing importance. For these reasons, there has been a continually increasing interest and investigations into the fault detection and diagnosis of induction motors. This paper describes the utility of online monitoring technique for detection of various faults that can be applied to existing motors without dismantling or shut down. The technique presented here is based on the monitoring of the current when the machine is normally operated and analyzing the same in frequency domain for detection of the faults. The technique can detect online the presence of various faults such as broken bar in the rotor cage of induction motor, bearing faults, eccentricity faults and stator turn to turn short, by monitoring and analyzing the line current. These different faults within induction motor are simulated in the laboratory and they are detected by online monitoring of current and analyzing same in frequency domain. This technique was also applied for condition monitoring of motors at a nuclear power station. The technique can be used as a diagnostic tool for condition monitoring of motors.