Abstract

Abstract Stator winding inter-turn short circuit faults and single-phasing faults are the major causes of failures of Electrically-Excited Synchronous Motor. This abnormality progressively grow faults leads to be complete damage of the machine. Hence in order to improve the sustainability of the system and increase the life of the motor suitable condition monitoring technique are necessary to identification of fault occurrence. In this context, this paper introduce the detection and phase identification of the turn-level short circuit faults in electrically excited synchronous machines. To detect and identify the faulty phases an algorithm is proposed based on a wavelet based multi-resolution analysis along with adaptive threshold for motor operated under different operating conditions. Stationary wavelet transform is employed to get the 3-ɸ currents fault residues and then discrete wavelet transform is employed to extract the disturbance information from the 3-ɸ residue currents. In order to find the fault location and phase identification fault index and 3-ɸ energies are compared with adaptive thresholds. Under different operating conditions finally, the algorithm is tested with practical data for single-phasing and various levels of inter-turn short circuit faults. By using acquired practical results the validity and successfulness of a proposed algorithm is clearly determined.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.