Sparking is a common phenomenon in brushed DC motors. Early detection of sparks can prevent their aggravation and promptly adopt appropriate maintenance actions. In this work, we propose the application of a multifractal analysis to armature currents and stray flux signals to detect the presence of sparks in the commutation system of DC motors. Two methodologies are proposed in the paper, the first one using the spectral kurtosis of armature currents and the second one using the flux signal envelope. We apply this method to signals captured both under starting and at steady state to compare their suitability and analyze their feasibility to be used as the basis of the sparking detection method. Additionally, we also propose a quantitative indicator based on the variance of the complex cepstrum to determine the severity of the failure based on the cepstral analysis of both considered signals. Our results demonstrate the potential of the approach for sparking detection and sparking level assessment in DC motors and its suitability for potential future incorporation into autonomous systems.
This work has been published in: J. Guerra-Carmenate et al., «Multifractal Spectrum and Complex Cepstrum Analysis of Armature Currents and Stray Flux Signals for Sparking Detection in DC Motors,» in IEEE Transactions on Industry Applications, vol. 60, no. 1, pp. 164-173, Jan.-Feb. 2024, doi: 10.1109/TIA.2023.3312235.
