Fault Diagnosis of Shaft-Earthing Systems in Turbo-Generators Using Shaft Voltage and Current Signatures—Case Studies

Accurate monitoring of shaft voltages and bearing currents in large turbo-generators is essential for promoting the sustainable operation of critical power infrastructure. Conventional monitoring systems often rely on threshold triggers that fail to identify early-stage degradation in shaft-earthing brushes. This paper presents an advanced diagnostic approach based on real-time shaft voltage and current measurements collected from four large utility-scale steam turbine generators. Through detailed analysis of time-domain waveforms, frequency-domain spectra, and current scatter plots, characteristic electrical signatures were established for four operational case studies for faults: (i) a floating voltage brush, (ii) a floating current brush, (iii) a worn brush, and (iv) oil/dust contamination. This study demonstrates that each fault produces a distinctive pattern, such as the suppressed RMS shaft voltage with transient spikes in floating voltage brushes, elevated DC offsets and even-order harmonics in floating current brushes, erratic waveforms and intermittent surges in worn brushes, and elevated DC bias with increased current under contamination. These findings establish actionable thresholds for predictive maintenance, fostering enhanced reliability, optimized asset life, and reduced maintenance-related environmental impact.