Acquisition and pre-processing of three phase induction motor stator current signal for fault diagnosis using FPGA, NI Compact-RIO real time controller

Induction motor plays a key role in ensuring functional execution and smooth progression of modern industries. But due to several harsh operational environments, different types of faults, in the form of stator winding fault, rotor fault etc. develop in the motor. If these faults, which are mostly minor in nature initially, don't get detected in earlier stages then they may inflict major damage in the motor and consequently may disrupt the plant's production capacity. So far, several studies primarily focusing on signature, model and expert system based techniques have been performed for conditioning monitoring of induction motors. Among all these techniques MCSA (Motor Current Signature Analysis) technique has been identified to be the most effective tool for diagnosis of induction motor faults. Most of the traditional condition and monitoring methods, using MCSA, that have been used till date are offline. Such offline analysis leads to delayed fault detection, resulting in plant production being eventually hampered, thus indirectly increasing the production cost. That is why, modern day industries demand online fault diagnosis methods which would analyze faults in real time and prevent any unforeseen production mishaps. FPGA or DSP where the signal is processed in hardware unit can be used for online analysis. This paper deals with 3-phase induction motor stator current acquisition using LABVIEW, FPGA embedded with NI cRIO-9075 real time controller and NI-9227 analog current input module looking towards online fault diagnosis.