Liyun Zhong
Papers
1
Total Citations
7
H-Index
1
About
Liyun Zhong is a researcher focused on intelligent monitoring and automation in underground mining environments, with particular expertise in machine vision, robotics, and roadway deformation detection. Their most-cited work, "Application of Roadway Deformation Detection Method Based on Machine Vision for Underground Patrol Robot" (2020, 7 citations), addresses critical challenges in coal mine safety by designing a track patrol robot system that automates the monitoring of roadway conditions and equipment. This system not only reduces the high labour intensity of human patrols but also enhances data collection and storage of environmental parameters through automatic cruise modes. Zhong’s contributions are significant for improving safety and efficiency in hazardous underground settings, where inadequate monitoring poses serious risks. By integrating machine vision with robotic patrol, their work offers a practical solution for real-time deformation detection, a key factor in preventing mine collapses. While citation counts are modest, the applied nature of this research underscores its value for industrial deployment and further innovation in mining automation.
Research Focus
Key Achievements
Top Papers
- 1