Wenlong Song

Northeast Forestry University

Papers

1

Total Citations

2

H-Index

1

About

Wenlong Song is an emerging researcher specializing in intelligent inspection systems, Internet of Things (IoT) technologies, and ultra-high voltage (UHV) power transmission infrastructure. His work addresses critical challenges in the energy sector, particularly the complex problem of conductor sag measurement and defect detection in overhead transmission lines under non-line-of-sight conditions — a technically demanding scenario with significant implications for grid safety and construction quality. Song's most notable contribution is the development of an IoT-based quality inspection robot designed specifically for UHV overhead transmission lines, published in 2025. This system integrates robotic automation with IoT connectivity to enable real-time, autonomous quality assessment during transmission line construction, offering a practical solution to a problem that has long challenged power infrastructure engineers. The work has already begun attracting citations within the research community, demonstrating its early relevance to both academia and industry. His research sits at the intersection of robotics, power systems engineering, and smart sensing technologies, reflecting a broader trend toward automation in critical infrastructure inspection. For students and researchers working in smart grid technologies or field robotics, Song's contributions represent a promising direction in applied engineering innovation.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
An IoT-based quality inspection robot for measuring conductor sag and detecting defects in ultra-high voltage overhead transmission lines
2 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Northeast Forestry University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago