Hongxun Lv
Papers
1
Total Citations
2
H-Index
1
About
Hongxun Lv is a researcher specializing in intelligent fault detection and industrial vision systems, with a primary focus on enhancing safety and efficiency in power plant operations. His most notable contribution is the development of an improved Faster R-CNN framework for leakage detection and identification in power plant pipelines, addressing critical steam and oil leak hazards. By replacing the standard VGG16 with a ResNet101 backbone, Lv’s work enriches feature extraction with deeper semantic information, while integrating a Convolutional Block Attention Module (CBAM) to sharpen detection accuracy. This system, detailed in his 2022 paper, has garnered early citations and represents a practical step toward automated, real-time monitoring in high-risk industrial environments. Lv’s research bridges deep learning and industrial engineering, offering a scalable solution for predictive maintenance. His work underscores a commitment to applying cutting-edge AI to real-world infrastructure challenges, making him a key figure in the evolution of smart power plant diagnostics.
Research Focus
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Top Papers
- 1