In this paper, a 2.2 kW squirrel cage induction motor having different degrees of static eccentricity is analyzed for fault detection using multi-resolution wavelet analysis (MRWA). The reference squirrel cage induction motor was simulated by using finite element method (FEM) and verified with the test results for the reference. Multi-resolution wavelet analysis was applied to decompose the high frequency components of flux density and current of the induction motor with different levels of eccenctricity. The effects of these components on the torque and vibration characteristics were also examined. The results show that MRWA could be a good alternative to fast fourier transform (FFT) in detecting air gap eccentricity in motors.