Novel FPGA-based Methodology for Early Broken Rotor Bar Detection and Classification Through Homogeneity Estimation

Abstract

Early detection of induction-motor faults has been an increasing matter of research in the last few years. The reliable identification of broken rotor bars (BRB) is still under investigation as it is one of the most common and difficult-to-detect faults in induction motors. Many methods have been proposed to deal with this issue. Recent approaches combine techniques looking for improving the performance of the diagnosis. Their major disadvantage is the high computational requirements, which restrains them from being used in online detection. The contribution in this paper is twofold. The first one is a novel methodology for induction motor BRB detection and the fault severity classification using homogeneity as index, which, to the best of our knowledge, has never been used as an indicator for fault diagnosis, analyzing one phase of the induction motor startup-transient current. Because of the low computational complexity in homogeneity calculation, the second contribution of this paper is a hardware-processing unit based on a field programmable gate array device for online detection and classification of BRB. Obtained results demonstrate the high efficiency of the proposed methodology as a deterministic technique for incipient BRB diagnosis in induction motors, which can detect and differentiate among half, one, or two BRBs with a certainty greater than 99.7%.