Jianmin Wu

Papers

Total Citations

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About

Jianmin Wu is a researcher at the forefront of intelligent robotics and computer vision, with a focused application in critical energy infrastructure. His work addresses the pressing need for automation in the maintenance of Ultra-High Voltage (UHV) substations, where the aging of transformer oil poses a significant risk to power system stability. Wu’s most cited contribution, "Visual system for oil sampling robot based on YOLO v5 and OpenCV model" (2022, 2 citations), introduces a novel integration of deep learning and classical computer vision to guide robotic oil sampling. By leveraging the YOLO v5 object detection algorithm alongside OpenCV, his system enables precise, autonomous visual recognition and manipulation, reducing the need for human intervention in hazardous environments. This work not only enhances operational safety but also improves the reliability of long-term power grid monitoring. Wu’s research exemplifies the practical synergy between modern AI and traditional engineering, offering a scalable solution for industrial automation. His contributions are particularly notable for their direct impact on the maintenance of UHV systems, a cornerstone of modern electrical grids.