Date of Award
Fall 2007
Document Type
Thesis - Restricted
Degree Name
Master of Science (MS)
Department
Electrical and Computer Engineering
First Advisor
Mirafzal, Behrooz
Second Advisor
Demerdash, Nabeel A.O.
Third Advisor
Johnson, Michael T.
Abstract
In this thesis, a condition monitoring vector (CMV) technique for poly-phase induction motor stator inter-tum short-circuit faults is presented. To be more specific, the CMV includes the swing angle, the negative sequence component of motor terminal currents and voltages, as well as the input power of the induction motor. The effectiveness of the CMV is illustrated for the inter-tum short circuit diagnostics using the Time Step Finite Element (TSFE) method, as well as experimental test results of a 5-hp, 6-pole, 460-Volts, 60-Hz induction motor. Furthermore, the momentum (speed) of swing angle variation is introduced for demonstrating the deterioration process of the stator winding when the motor starts to diverge from the healthy situation to a severe faulty condition. Moreover, the Time-Averaging method is applied to improve the robustness of the condition monitoring vector concept.
Recommended Citation
Cao, Bojian, "A Condition Monitoring Vector (CMV) Technique for Poly-Phase Electric Machine Fault Diagnostics" (2007). Master's Theses (1922-2009) Access restricted to Marquette Campus. 4016.
https://epublications.marquette.edu/theses/4016