A Sparsity-Driven Method to Iteratively Extract Motor Fault Signatures in Varying-Speed Operations

Motors are typically operating at varying speed conditions, especially when they are driven by inverters for high efficiency. However, it is challenging to extract motor faults under varying-speed conditions due to the frequency variation of fault signatures, spectrum distortion, and other interference. Even the fault signature is detected, the fault severity is often underestimated and not robust. To address these issues, we propose a sparsity-driven method to iteratively extract speed-dependent fault frequency components from the stator current, considering frequency variations due to the varying speed. Experiments show that our method can extract frequency signatures of different faults with significantly better results compared to other state-of-the-art methods. The proposed method can be applied to inverter-fed motor drive system for robust fault detection.