Time-Frequency Analysis Based on Minimum-Norm Spectral Estimation to Detect Induction Motor Faults

Tomas A. Garcia-Calva, Daniel Morinigo-Sotelo, Oscar Duque-Perez, Arturo Garcia-Perez and Rene de J. Romero-Troncoso
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Tomas A. Garcia-Calva: HSPdigital-Electronics Department, University of Guanajuato, Salamanca 36700, Mexico
Daniel Morinigo-Sotelo: HSPdigital-ADIRE, ITAP, University of Valladolid, 47011 Valladolid, Spain
Oscar Duque-Perez: HSPdigital-ADIRE, ITAP, University of Valladolid, 47011 Valladolid, Spain
Arturo Garcia-Perez: HSPdigital-Electronics Department, University of Guanajuato, Salamanca 36700, Mexico
Rene de J. Romero-Troncoso: HSPdigital-Mechatronics Department, Autonomous University of Querétaro, San Juan del Río 76806, Mexico

Energies, 2020, vol. 13, issue 16, 1-12

Abstract: In this work, a new time-frequency tool based on minimum-norm spectral estimation is introduced for multiple fault detection in induction motors. Several diagnostic techniques are available to identify certain faults in induction machines; however, they generally give acceptable results only for machines operating under stationary conditions. Induction motors rarely operate under stationary conditions as they are constantly affected by load oscillations, speed waves, unbalanced voltages, and other external conditions. To overcome this issue, different time-frequency analysis techniques have been proposed for fault detection in induction motors under non-stationary regimes. However, most of them have low-resolution, low-accuracy or both. The proposed method employs the minimum-norm spectral estimation to provide high frequency resolution and accuracy in the time-frequency domain. This technique exploits the advantages of non-stationary conditions, where mechanical and electrical stresses in the machine are higher than in stationary conditions, improving the detectability of fault components. Numerical simulation and experimental results are provided to validate the effectiveness of the method in starting current analysis of induction motors.

Keywords: fault detection; induction motors; signal processing; spectrogram; spectral analysis; stator current; transient regime; time-frequency analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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