Application of wavelet transform for extraction of slip frequency component from SVPWM signal

The high frequency switching noises due to space vector pulse width modulated (SVPWM) inverter driving squirrel cage induction motor (SCIM) usually contaminate voltage/current signals required for estimation of its various parameters. Various mathematical operations are required to be performed in estimating those parameters. The estimation of derivatives of these signals is difficult especially in practice due to the presence of unwanted noise and non-stationary nature of the signal of interest. Hence, wavelet transform based filtering (WTF) technique is proposed in this work to extract dominant slip frequency components from the voltage/current signals. The suggested filtering technique is effective over the useful range of the slip frequency and no tuning is necessary with change in slip. The experimental results while implementing WTF in dSPACE, confirm the effectiveness of WTF in denoising low frequency current signals contaminated with high frequency noise.