Experimental identification on natural frequency of induction motor using multi-objective optimizing method

Abstract

Dynamic FEM analysis is valid for designing rotating machinery to reduce its vibration problem when we may ensure enough accuracy of the analysis. Surrogate multiple objective optimization method is one of the most effective methods for structural identification improving the FEM analysis model of a structure to adjust the natural frequency analysis results to the experimental results. In this study the structural identification method is applied to coil mounted stator core of an induction motor to determine the Young’s modulus of the principal components on the FE model minimizing the analysis errors of the natural frequencies of the 2-lobe and 3-lobe circular modes to the corresponding experimental results. The accurate FE model of the end-windings is obtained by this method.