Wavelet Filter Selection Analysis for Air Gap Eccentricity in Three Phase Induction Motor

Abstract

Electrical machines is more important in the industrial world. To maintain a continuous production that most of the process is supported by an induction motor it must be kept in good condition so that the damage can be avoided and make the equipment ages become longer. One of the damage to the induction motor is the air gap eccentricity which, if not detected, will cause friction between the rotor and the stator. For that needed a method for early detection. This research uses wavelet method. The type of wavelet families used there are 3. Wavelet families is haar, daubechies and symlet, it takes 3 wavelets to know which wavelet filter can better to detection air gap eccentricity. In the haar wavelet the success rate of dl (detail), d4 by 10%. For daubechies wavelet the percentage of success is in d1 by 90%, d2 and d4 by 20% and d3 by 10%. While for wavelet symlet the percentage of success in d1 is 100%, d2 is 80%, d3 is 30% and d4 is 20%. So for the type wavelet filter is haar the percentage of detection success rate is very low compared to the wavelet filters of daubechies and symlet.