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A secure and sensitive wavelet transform based technique for stator fault detection in the cases of line‐connected and inverter‐fed induction machines
Author(s) -
Nazemi Mohammad Hossein,
Gallehdar Davar,
Haghjoo Farhad,
Cruz Sérgio
Publication year - 2021
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 97
eISSN - 1751-8679
pISSN - 1751-8660
DOI - 10.1049/elp2.12084
Subject(s) - stator , line (geometry) , inverter , wavelet transform , fault detection and isolation , computer science , control theory (sociology) , fault (geology) , induction motor , wavelet , control engineering , engineering , artificial intelligence , electrical engineering , mathematics , voltage , biology , actuator , control (management) , paleontology , geometry
Here a new sensitive fault detection criterion is proposed, based on the stationary wavelet transform (SWT) decomposition components of the stator currents, for the online detection of stator winding turn‐to‐turn faults at an early stage of development. The energies of the desired detail components are calculated and the normalized Euclidean distance of the energy differences between the three phases is used as a new fault detection criterion. The robustness of the proposed technique against the presence of rotor turn‐to‐turn faults and loading variations is demonstrated. In addition, an adaptive threshold level as a function of the voltage unbalance factor is proposed to guarantee the robustness of the diagnostic technique against unbalanced voltage sources. Experimental results demonstrate the effectiveness and sensitivity of the proposed diagnostic approach for the detection of stator faults in line‐connected and inverter‐fed motors.

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