A Comprehensive Review of Shaft Voltages and Bearing Currents, Measurements and Monitoring Systems in Large Turbogenerators
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...
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MDPI AG
2025-04-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/8/2067 |
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| author | Katudi Oupa Mailula Akshay K. Saha |
| author_facet | Katudi Oupa Mailula Akshay K. Saha |
| author_sort | Katudi Oupa Mailula |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-67f9be05a2ce42f58aa9db412f67d4ef |
| institution | OA Journals |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-67f9be05a2ce42f58aa9db412f67d4ef2025-08-20T02:17:20ZengMDPI AGEnergies1996-10732025-04-01188206710.3390/en18082067A Comprehensive Review of Shaft Voltages and Bearing Currents, Measurements and Monitoring Systems in Large TurbogeneratorsKatudi Oupa Mailula0Akshay K. Saha1Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, South AfricaDiscipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, South AfricaTurbine 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.https://www.mdpi.com/1996-1073/18/8/2067bearing currentcirculating currentcondition monitoringcommon-mode voltagefault detectionmachine learning |
| spellingShingle | Katudi Oupa Mailula Akshay K. Saha A Comprehensive Review of Shaft Voltages and Bearing Currents, Measurements and Monitoring Systems in Large Turbogenerators Energies bearing current circulating current condition monitoring common-mode voltage fault detection machine learning |
| title | A Comprehensive Review of Shaft Voltages and Bearing Currents, Measurements and Monitoring Systems in Large Turbogenerators |
| title_full | A Comprehensive Review of Shaft Voltages and Bearing Currents, Measurements and Monitoring Systems in Large Turbogenerators |
| title_fullStr | A Comprehensive Review of Shaft Voltages and Bearing Currents, Measurements and Monitoring Systems in Large Turbogenerators |
| title_full_unstemmed | A Comprehensive Review of Shaft Voltages and Bearing Currents, Measurements and Monitoring Systems in Large Turbogenerators |
| title_short | A Comprehensive Review of Shaft Voltages and Bearing Currents, Measurements and Monitoring Systems in Large Turbogenerators |
| title_sort | comprehensive review of shaft voltages and bearing currents measurements and monitoring systems in large turbogenerators |
| topic | bearing current circulating current condition monitoring common-mode voltage fault detection machine learning |
| url | https://www.mdpi.com/1996-1073/18/8/2067 |
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