Jinle Zeng
Papers
1
Total Citations
45
H-Index
1
About
Jinle Zeng is a leading researcher in intelligent welding and robotic automation, with a primary focus on advancing multi-layer/multi-pass welding (MLMPW) technology for the energy industry. His most cited work, "A Weld Position Recognition Method Based on Directional and Structured Light Information Fusion in Multi-Layer/Multi-Pass Welding" (2018, 45 citations), addresses a critical challenge in automated thick-component joining: accurately recognizing weld pass positions using visual methods. By fusing directional and structured light information, Zeng’s approach enables robots and actuators to precisely identify weld seams in real time, significantly improving the reliability and quality of automatic welding processes. This contribution has direct implications for manufacturing sectors such as shipbuilding, pipeline construction, and pressure vessel fabrication, where MLMPW is essential. Zeng’s research bridges computer vision, sensor fusion, and industrial robotics, offering practical solutions for complex welding environments. His work not only enhances automation efficiency but also reduces human error in high-stakes industrial applications. With a growing citation record and a focus on real-world impact, Jinle Zeng is recognized as an innovator in intelligent manufacturing, particularly in the integration of advanced sensing techniques for robust, adaptive welding systems.
Research Focus
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Top Papers
- 1