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 p...
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Published in: | 2014 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES) pp. 1 - 4 |
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Main Authors: | , , |
Format: | Conference Proceeding |
Language: | English |
Published: |
IEEE
01-12-2014
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Subjects: | |
Online Access: | Get full text |
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Summary: | 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. |
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ISBN: | 9781479963720 1479963720 |
DOI: | 10.1109/PEDES.2014.7042142 |