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

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 4^th 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.