An improved combination of Hilbert and Park transforms for fault detection and identification in three-phase induction motors

摘要

In this work we propose an original fault signature based on an improved combination of Hilbert and Park transforms. Starting from this combination we can release two fault signatures: Hilbert modulus current space vector (HMCSV) and Hilbert phase current space vector (HPCSV). These two signatures are subsequently analyzed using the classical fast Fourier transform (FFT). The effects of HMCSV and HPCSV spec-trums are described and the related frequencies are determined. A comparative study is presented of the suggested signature (HPCSV) and the MCSA which is the signature more recently proposed in the literature. The proposed signature shows its effectiveness and its robustness in both electrical and mechanical fault detection. The magnitudes of spectral components relative to the studied faults are extracted in order to develop the input vector necessary for the pattern recognition tool based on support vector machine (SVM) approach with an aim of classifying automatically the various states of the induction motor. This approach was applied to a 1.1 kw induction motor under normal operation and with the following faults: unbalanced voltage, broken rotor bar, air-gap eccentricity and outer raceway ball bearing defect.