Transfer Function approach based upon wavelet transform for bearing damage detection in electric motors

This study presents a Transfer Function (TF) approach based on the continuous wavelet transform (CWT) using the vibration measurements for feature extraction. This approach helps to extract the origin of the bearing damage that develops during the aging process and then, it can be used to find the potential defects, which exist in healthy motor bearings as manufacturing defects. In this manner, there are two fundamental steps of the study. They are the definition of the transfer function and feature extraction which is related to the bearing damage characterization in electric motors. The definition of the feature transfer function is done between the first scale of the CWT analysis and original vibration signal in the frequency domain. Hence, it is introduced as a new viewpoint for condition monitoring studies in induction motors.