Title :
Monitoring of inter-turn insulation failure in induction motor using advanced signal and data processing tools
Author :
Das, S. ; Purkait, P. ; Dey, D. ; Chakravorti, S.
Author_Institution :
Dept. of Electr. Eng., Haldia Inst. of Technol., Haldia, India
fDate :
10/1/2011 12:00:00 AM
Abstract :
Detection of stator winding inter-turn insulation failure at early stages is crucial for promoting safe and economical use of induction motors in industrial applications. Whereas major insulation failures involving larger percentages of winding are easily discernible from magnitude of supply current, minor inter-turn insulation failures involving less than 5% of turns often go undetected. The present contribution reports experimental results of minor faults due to inter-turn insulation failures in stator windings of induction motor under different loading conditions being analyzed using data and signal processing tools combining Park´s Transform and Cross Wavelet Transform. Rough Set Theory (RST) based classifier has been used for fault severity monitoring.
Keywords :
failure (mechanical); failure analysis; fault diagnosis; induction motors; stators; wavelet transforms; Park transform; cross wavelet transform; data processing tools; fault severity monitoring; induction motor; inter turn insulation failure monitoring; rough set theory; signal processing tools; stator windings; supply current; Circuit faults; Induction motors; Insulation; Stator windings; Voltage fluctuations; Windings; Induction motor; Park??s transformation; cross wavelet transform; inter-turn insulation failure; rough set theory;
Journal_Title :
Dielectrics and Electrical Insulation, IEEE Transactions on
DOI :
10.1109/TDEI.2011.6032830