Detection and identification of stator inter-turn faults in three-phase induction motor in presence of supply unbalance condition

Abstract

Induction machines play a vital role in process industries due to their low cost, ruggedness and low maintenance. Even though the induction machine is very reliable, many failures can occur due to their non-ideal operating conditions. Literature survey reveals that stator faults occupy a prominent place among the reasons for such failures. In particular, an undetected stator inter-turn fault may progressively lead to a permanent damage of the machine. Hence, early detection of stator inter-turn faults is essential for preventing damage to the adjacent coils and the core of the stator. Also, detection of stator inter-turn faults in the presence of supply unbalance is another challenging task. This paper proposes a new adaptive approach based on wavelet multi-resolution analysis for detecting and identifying the stator inter-turn faults. A fault index is defined based on the slope of detail coefficients to compare with an adaptive threshold for setting the flags. A fault is detected when the flag count reaches 6 over a moving window of 10 samples. Severity of the fault is identified by defining a sensitivity index based on the three phase energies of 4th level approximate coefficients. The proposed method is verified by using experimental data considering supply unbalance as well. Results indicate the effectiveness of the proposed method.