Wenxi Wang
Papers
19
Total Citations
229
H-Index
8
About
Wenxi Wang is an emerging researcher specializing in robotic grinding, precision manufacturing, and intelligent machining systems, with particular focus on the high-precision finishing of aeronautical components such as compressor blades and complex curved surfaces. Wang's work addresses some of the most challenging problems in advanced manufacturing: achieving tight profile tolerances in robotic belt grinding systems where nonlinear contact dynamics and uneven material allowances traditionally compromise accuracy. Among Wang's most impactful contributions is research on path accuracy enhancement for industrial robots in complex surface grinding (51 citations), alongside pioneering work integrating aerodynamic performance considerations directly into the robotic machining of transonic compressor blade leading edges (27 citations). Wang has also advanced intelligent monitoring through U-Net-based deep learning approaches for belt wear quantification (26 citations), bridging AI and precision manufacturing. Notable innovations include region-based force control strategies for seven-axis linkage grinding systems, dynamic observer-based contact force algorithms, and model predictive impedance control frameworks — collectively pushing robotic finishing toward greater autonomy and consistency. Wang's more recent explorations into 3D-printed compliant tooling reflect a forward-thinking approach to confined-space machining challenges. With over 180 cumulative citations across a focused body of work, Wang represents a rising voice in intelligent robotic manufacturing research.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10