Fault Detection in DC Electro Motors Using the Continuous Wavelet Transform

Abstract

Two time–frequency methods were used to detect typical faults in DC electro motors: the windowed Fourier transform and the continuous wavelet transform. Four groups containing three electro motors each were manufactured with typical faults and examined. These faults included a bearing fault, an increased unbalance, a fragmented brush and a fragmented collector. The velocity of the vibrations at selected points on the electro motors was measured with a laser probe. The parameters of both transforms were selected in order to make both methods comparable. Because of the poor frequency variance, the windowed Fourier transform was, in this case, proven to be inferior to the continuous wavelet transform. Therefore, the continuous wavelet transform was chosen as the primary tool for fault detection.