Stator current bi-spectrum patterns for induction machines multiple-faults detection

Inspecting the literature, the most used techniques proposed for induction machines diagnosis are focused on detecting single faults. There is a lack of works dealing with the diagnosis and identification of multiple combined faults. In this framework, this paper presents the stator current bi-spectrum analysis to detect two types of faults mixed together which may appear in three phase induction motors. Based on real experimental data, the detection study concerns isolated rotor broken bars and damage in the bearing's inner race rolling element. For multiple faults detection, and for lack of experimental data, only synthetic data are used. To deal with the frequency analysis, a mathematical model of the stator current has been derived and used into the bi-spectrum formulas. The main contribution of this paper is the development of a theoretical method which may help the user to assess the presence of fault frequencies in induction motors in both settings namely single or multiple combined faults. To highlight the superiority of the bi-spectrum tool over the spectrum, receiver operating characteristics (ROC) analysis has been carried out. Therefore, simulation results are performed in noisy environment showing that the bi-spectrum is able to detect frequency faults better.