Abstract
Induction motors are the workhorse component of many industries and are frequently integrated into equipment. Many industries faced one of the serious problems regarding its maintenance issues. According to Neale and Wowk, the maintenance expenditure can be up to 80% of the total cost of motor. According to the reliable study by Electric Power Research Institute, the inter-turn short-circuit faults approximately contribute 37% of the induction motor failures. In the literature, most of the techniques are reviewed that are used to diagnose the fault in stator winding and it is found that majority of motor failures are due to insulation breakdown. It is found the unbalanced voltage is one of the major sources of insulation failure. And most of the exiting techniques to diagnose this fault are off-line or sensor bases. In this work, noninvasive online method is proposed; first of all, an analytical expression is derived for the conductor segments in the stator winding that are responsible for the generation of magnetomotive force (MMF). Therefore, stator windings are partitioned down into two set of segments (slot conductors and end conductors). The slot conductors are of major interest because their axial arrangement in the slots provides a room to establish MMF in order to generate a torque. Further, in this paper, an expression for MMF is derived through winding function approach. It was found that besides the fundamental MMF, there exist waves with a different number of poles. This MMF will induce a voltage in a stator winding through rotor side. In addition, the effect of MMF is considered on the current spectrum of induction motor because the knowledge of current spectrum under faulty regimes is the point of interest to diagnose a motor fault in a noninvasive way. Moreover, a new series of rotor harmonic frequency component are introduced to diagnose unbalanced voltage supply. Finally, the proposed analytical models and new series of rotor harmonic sheds a light on stator current components to diagnose and distinguish between balanced and unbalanced voltage supply in a real-time scenario. To validate the proposed method, two experimental hardware setups were designed comprising of a three-phase induction motor, two-axis magnetic field sensor, 8821-2A variable power source, current transformer, FLUKE 435 II series power quality energy analyzer, and Pasco interface for data acquisition. The appearance and significant increase in the magnitude of a new series of harmonics under unbalanced voltage are the indication of unbalanced voltage supply. Thus, the experimental data clearly justify and validate the proposed analytical model with the results of hardware setup.
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