AC motor fault diagnosis at incipient stage using programmable logic controller

Alternating Current (AC) motors are extensively used in the industries and it is essential to protect these motors from unexpected breakdowns and to detect faults at incipient level so that planned maintenance could be done. In the last three decades various fault diagnosis techniques has been developed but these techniques are considered intrusive as they require accessability to motor for data collection. Also the electromechanical devices, sensors and integrated circuits used in these techniques are expensive and not reliable. Special attention is given to non-invasive techniques to detect defects without accessing the machines. This paper attempts to provide a new approach for condition monitoring of AC motors through intelligent fault diagnosis based on programmable logic controllers. The stator current analysis which is non-invasive and economical method is used with LabVIEW signal processing tools. The current signal is analyzed via Fast Fourier Power spectrum to detect the bearing faults at incipient stages. The technique is validated at three different speeds.