Study of bearing currents in induction machine: diagnostic possibilities, fault detection, and prediction

Bearing failures in electrical machines pose significant challenges, attracting attention in diagnostic research. The widespread adoption of variable-speed drives across various motor applications has increased the effects of bearing currents, necessitating thorough exploration in both academic and industrial contexts. The paper contributes valuable insights into identifying and addressing bearing-related issues in electrical machines. It comprehensively investigates the matter, investigating damage types and diagnostic techniques specific to bearing currents in induction machines. Moreover, it provides insights from experiments conducted in controlled laboratory settings to replicate bearing current faults. As the industry integrates advanced technologies into manufacturing processes and gains traction, preventive maintenance is increasingly emphasized. Consequently, the paper expands its investigation into signal pre-processing to enhance fault prediction accuracy by optimizing machine signals. Given the dynamic nature of industrial standards and the growing demand for predictive maintenance strategies, this research presents a predictive method for early fault detection. Aiming for heightened efficiency, reduced downtime, and enhanced reliability, the perspectives outlined in this paper make a meaningful contribution to the evolving field of predictive maintenance.