Abstract

The goal of stator-winding turn-fault (TF) detection is to detect the fault at an early stage and shut down the machine immediately to prevent catastrophic motor failure due to the large fault current. A number of TF detection techniques have been proposed; however, there is currently no method available for distinguishing TFs from high-resistance (R) connections (HRCs), which also result in three-phase system asymmetry. It is important to distinguish the two faults, since an HRC does not necessarily require immediate motor shutdown. In this paper, new sensorless online monitoring techniques for detecting and classifying stator TFs and high-R electrical connections in induction machines based on the zero-sequence voltage or negative-sequence current measurements are proposed. An experimental study on a 10-hp induction motor performed under simulated TFs and high-R circuit conditions verifies that the two faults can be reliably detected and classified. The proposed technique helps improve the reliability, efficiency, and safety of the motor system and industrial plant and also allows maintenance to be performed in a more efficient manner, since the course of action can be determined based on the type and severity of the fault.

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