Multi-Resolution Analysis for Induction Motor Health Assessment: A Review Approach

Abstract

Recently, multiresolution analysis (MRA) techniques have been introduced into the field of condition monitoring and fault diagnosis of induction motors, which made valuable steps towards being able to operate signals on different time-frequency scales at the same time. This systematic review focuses on the latest literature trends of MRA-based methods used in induction motor health assessment, particularly wavelet transforms, empirical mode decomposition (EMD), variational mode decomposition (VMD), and several hybrid techniques. The efficiency of these methods in the presence of bearing defects, stator winding faults, rotor bar breaks, or eccentricity is analysed in this paper. The review also considers signal acquisition processes, feature extraction techniques, and classification algorithms de rigueur for diagnostic systems based on MRA. Identifies current limitations and suggests future research paths, which include integrating AI, IoT-based monitoring systems, and signal processing. This paper is a reference material for researchers and practitioners on induction motor CM.