Bearing Currents of Induction Machine – Fault Detection, Condition Monitoring, and Predictive Maintenance

Abstract Bearing failures in electrical machines present significant challenges, drawing attention in diagnostic research. The widespread use of variable-speed drives in various motor applications has intensified the impact of bearing currents, requiring comprehensive exploration in academic and industrial settings. This paper thoroughly investigates the issue, examining damage types and diagnostic methods specific to bearing currents in induction machines. Additionally, it offers insights from experiments conducted in controlled laboratory environments to simulate bearing current faults. By outlining the findings, the paper contributes valuable knowledge on identifying and mitigating bearing-related issues in electrical machines. With the shift towards Industry 4.0 standards, which integrate advanced technologies into manufacturing processes, there's a growing emphasis on preventing production faults. Consequently, the paper extends its inquiry into signal pre-processing to enhance fault prediction accuracy by optimizing and refining machine signals. Given the dynamic nature of industrial standards and the rising demand for predictive maintenance strategies, this research holds significance. By striving for increased efficiency, reduced downtime, and enhanced reliability, the perspectives outlined aspire to make a meaningful contribution to the advancing field of predictive maintenance.