Multifractal Spectrum and Complex Cepstrum Analysis of Armature Currents and Stray Flux Signals for Sparking Detection in DC Motors

• Published in: IEEE transactions on industry applications Vol. 60; no. 1; pp. 1 - 11
• Main Authors: Carmenate, Jose Guerra, Iglesias-Martinez, Miguel E., Velasco-Pla, Pablo M., Daviu, Jose A. Antonino, Duna, Larisa, Conejero, J. Alberto, de Cordoba, Pedro Fernandez
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Bispectrum; Brushes; Cepstral analysis; Commutation; D C motors; DC motors; Electric motors; Fault Diagnosis; Fractal analysis; Fractals; Kurtosis; Maintenance engineering; Mathematical models; Multifractal Spectrum; Sparks; Spectral Kurtosis; Steady-state
• ISSN: 0093-9994; 1939-9367
• DOI: 10.1109/TIA.2023.3312235

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. The 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.