Liqiang Li
Papers
1
Total Citations
3
H-Index
1
About
Liqiang Li is a researcher focused on advancing non-destructive evaluation (NDE) techniques, particularly in ultrasonic imaging for complex manufacturing components. His work addresses critical challenges in inspecting intricately structured parts, where conventional B-scan imaging often fails to achieve sufficient detection coverage and image contrast. Li’s most cited paper, “Robot-Assisted Track-Scan Imaging Approach with Multiple Incident Angles for Complexly Structured Parts” (2020), introduces a novel robotic system that dynamically adjusts ultrasonic incident angles to improve image quality and defect detectability. This approach represents a significant contribution to automated inspection, enabling more reliable quality control in modern manufacturing. Although his citation count is currently modest, the practical implications of his work—enhancing the safety and durability of high-value components—underscore its growing relevance. Li’s research sits at the intersection of robotics, signal processing, and materials science, offering a promising pathway for smarter, more adaptive NDE solutions. His work is particularly valuable for engineers and researchers seeking to improve inspection methodologies for complex geometries in aerospace, automotive, and energy sectors.
Research Focus
Key Achievements
Top Papers
- 1