Xiaoning Ge

State Nuclear Power Technology Company (China)

Papers

1

Total Citations

14

H-Index

1

About

Xiaoning Ge is a researcher specializing in intelligent robotics and sensor-based localization, with a particular focus on ultrasonic signal processing for industrial inspection systems. Their most cited work, "3-D Ultrasonic Localization of Transformer Patrol Robot Based on EMD and PHAT-β Algorithms" (2021, 14 citations), introduces a novel hyperboloid 3D localization method that combines Empirical Mode Decomposition (EMD) with Phase Transform-beta (PHAT-β) generalized cross-correlation to enhance the accuracy of transformer patrol robots. This contribution addresses critical challenges in noisy industrial environments by employing a linear sensor array to improve ultrasonic signal detection and localization. Ge’s research bridges the gap between advanced signal processing techniques and practical robotics applications, offering significant implications for automated infrastructure monitoring and maintenance. With a growing citation impact, their work is recognized for its methodological innovation and real-world utility, positioning Ge as an emerging voice in the fields of robotics, sensor fusion, and industrial automation. Their achievements highlight a commitment to developing reliable, high-precision systems for critical energy infrastructure.

Research Focus

Key Achievements

1
H-Index
1
Papers
14
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
3-D Ultrasonic Localization of Transformer Patrol Robot Based on EMD and PHAT-β Algorithms
14 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: State Nuclear Power Technology Company (China)

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago