Arte; Arqueologíaus inverters feeding induction motors with incipient rotor fault using high-resolution spectral analysis

Abstract

Recently, there has been an increased interest in fault detection on electrical machines in steady-state regimes. Several frequency estimation techniques have been developed to assist the early detection of faults in induction motors, especially in line-fed motors. However, in modern industry, the use of inverters is increasingly present. This paper presents an analysis for comprehending the challenge in detecting incipient rotor faults using the stator current signal under different inverter supplies. The approach is based on the high-resolution technique known as multiple signal classification (MUSIC). In this study, incipient rotor faults in a squirrel-cage rotor, prior to the complete breaking of a rotor bar, are better identified in some inverters than others. The proposed approach finds the adequate MUSIC order that facilitates identification of bar breakage frequencies for early fault detection in each case studied from a wide set of trials. The study has been developed to detect incipient rotor bar breakages in an inverter-fed three-phase induction motor under varying load situations.