Yingjie Mei
Papers
1
Total Citations
6
H-Index
1
About
Yingjie Mei is a researcher specializing in precision measurement and geometric parameter extraction for aerospace components. Their work focuses on developing automated, high-efficiency methods for quantifying complex geometries, particularly in the context of aero-engine fan blades—a critical area for manufacturing quality control and performance optimization. Mei’s most cited paper, "An efficient automated measurement method for aero-engine fan blade geometric parameters" (2024), introduces a novel approach that significantly reduces manual inspection time while improving accuracy, addressing a long-standing bottleneck in aerospace production. With 6 citations in its first year, this work has already drawn attention from both industrial and academic communities, signaling its practical relevance. Mei’s contributions lie at the intersection of optical metrology, algorithm design, and mechanical engineering, offering scalable solutions for high-precision industries. Their research is particularly valuable for students and engineers seeking to understand how automation and computational geometry can transform traditional measurement workflows. By streamlining the inspection of critical engine components, Mei’s work supports safer, more reliable aviation technology.
Research Focus
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Top Papers
- 1