Tianpeng Yan
Papers
1
Total Citations
8
H-Index
1
About
Tianpeng Yan is a researcher focused on the intersection of artificial intelligence and power system safety, with key contributions in deep learning-based target detection for electrical equipment. His most cited work, "Research on the state detection of the secondary panel of the switchgear based on the YOLOv5 network model" (2021, 8 citations), introduces a novel application of the YOLOv5 algorithm to automate the monitoring of switchgear panels—a critical component in power systems where manual inspection is inefficient and error-prone. By leveraging deep learning for real-time state detection, Yan addresses a pressing need to enhance operational reliability and reduce downtime in electrical infrastructure. This work underscores his broader expertise in applying computer vision to industrial monitoring, bridging the gap between advanced AI models and practical energy sector challenges. Though early in his career, Yan’s research demonstrates significant potential for impact, offering scalable solutions for the vast number of switchgears in power grids. His contributions are particularly valuable for students and researchers exploring AI-driven automation in critical infrastructure, highlighting how modern algorithms can transform traditional maintenance practices.
Research Focus
Key Achievements
Top Papers
- 1