Shihai Liu

Papers

1

Total Citations

24

H-Index

1

About

Shihai Liu is a leading researcher in high-voltage insulation diagnostics, with a primary focus on partial discharge (PD) pattern recognition for gas-insulated switchgear (GIS). His work addresses a critical challenge in power systems: accurately evaluating insulation health to prevent catastrophic failures. Liu’s major contribution lies in pioneering multi-feature information fusion techniques, particularly through the analysis of phase-resolved partial discharge (PRPD) images. His most-cited paper, “GIS Partial Discharge Pattern Recognition Based on Multi-Feature Information Fusion of PRPD Image” (2022, 24 citations), overcomes the limitations of traditional single-feature methods by integrating diverse diagnostic signals, significantly boosting recognition accuracy. This innovation has practical implications for predictive maintenance in substations, reducing downtime and enhancing grid reliability. Liu’s research has garnered attention for its methodological rigor and real-world applicability, with his citation count reflecting growing influence in the field. By advancing intelligent monitoring tools, he is shaping the future of insulation diagnostics, making his work essential reading for students and engineers tackling high-voltage equipment reliability.

Research Focus

Key Achievements

1
H-Index
1
Papers
24
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
GIS Partial Discharge Pattern Recognition Based on Multi-Feature Information Fusion of PRPD Image
24 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 6

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 10 days ago