Transient Modeling and Recovery of Non-Stationary Fault Signature for Condition Monitoring of Induction Motors

• Main Authors: Bilal Asad, Toomas Vaimann, Anouar Belahcen, Ants Kallaste, Anton Rassõlkin, Payam Shams Ghafarokhi, Karolina Kudelina
• Format: Article
• Language: English
• Published: MDPI AG 2021-03-01
• Series: Applied Sciences
• Subjects: condition monitoring; fault diagnosis; Fourier transform; induction motors; modeling; wavelet transform
• Online Access: https://www.mdpi.com/2076-3417/11/6/2806

This paper presents the modeling and the broken rotor bar fault diagnostics by time–frequency analysis of the motor current under an extended startup transient time. The transient current-based nonstationary signal is retrieved and investigated for its time–frequency response to segregate the rotor faults and spatial harmonics. For studying the effect of reduced voltage on various parameters and the theoretical definition of the fault patterns, the winding function analysis (WFA)-based model is presented first. Moreover, an algorithm to improve the spectrum legibility is proposed. It is shown that by efficient utilization of the attenuation filter and consideration of the area containing the maximum power spectral density, the diagnostic algorithm gives promising results. The results are based on the machine’s analytical model and the measurements taken from the laboratory setup.