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Abstract
Turbine generators are essential for power generation, but the presence of shaft voltages and currents poses significant challenges to their reliability, efficiency, and operational lifespan. These phenomena, arising from electromagnetic induction, poor shaft grounding, rotor excitation systems, and varying operational conditions, can lead to severe damage to bearings and rotors, resulting in costly downtime and maintenance. This study reviews the mechanisms behind shaft voltage and current generation, their impact on turbine generators, and the effectiveness of various mitigation strategies, including shaft earthing brushes, bearing insulation, and advanced health monitoring systems. Furthermore, it explores emerging techniques for measuring and diagnosing shaft voltage and current, as well as advancements in predictive maintenance and condition monitoring. This study further explores the integration of artificial intelligence and machine learning in predictive maintenance, leveraging real-time condition monitoring and fault diagnostics. By analyzing existing and emerging mitigation strategies, this study provides a comprehensive evaluation of solutions aimed at minimizing these electrical effects. The findings underscore the importance of proactive management strategies to enhance generator reliability, optimize maintenance practices, and improve overall power system stability. This research serves as a foundation for future advancements in shaft voltage mitigation, contributing to the long-term sustainability of power generation infrastructure.
Published Version
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