Title :
Condition-based monitoring and prognostic health management of electric machine stator winding insulation
Author :
Babel, Andrew S. ; Strangas, Elias G.
Author_Institution :
Dept. of Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI, USA
Abstract :
A comprehensive diagnostic and prognostic method is introduced for assessing the condition of stator winding insulation and predicting its failure time. A diagnostic method is developed by building an analytical model of the stator winding. Degradation is simulated by altering the permittivity and conductivity of the insulation in a finite element model simulation and changing the analytical model accordingly. The diagnostic method is performed with an oscilloscope and other common hardware. A prognostic method is introduced which is used to predict the remaining useful life of the insulation based on fitting insulation current measurements to an exponential decay model. The diagnostic method is verified with the analytical model for multiple levels of degradation and experimentally for the healthy case. The prognostic method is verified with simulated degradation data.
Keywords :
condition monitoring; electric current measurement; finite element analysis; machine insulation; oscilloscopes; permittivity; stators; common hardware; condition-based monitoring; diagnostic method; electric machine stator winding insulation; exponential decay; failure time; finite element model simulation; fitting insulation current measurements; insulation conductivity; insulation permittivity; oscilloscope; prognostic health management; Capacitance; Conductors; Current measurement; Degradation; Insulation; Leakage currents; Monitoring; AC machines; condition monitoring; dielectric losses; dielectrics; electric machines; insulation; prognostics and health management;
Conference_Titel :
Electrical Machines (ICEM), 2014 International Conference on
Conference_Location :
Berlin
DOI :
10.1109/ICELMACH.2014.6960436
