Liuhao Shan
Papers
2
Total Citations
22
H-Index
2
About
Liuhao Shan is a researcher focused on advancing sensor technologies for industrial and robotic applications, with key contributions in ionic polymer–metal composite (IPMC) sensors and vibration-based health monitoring. Shan’s work addresses critical challenges in sensor sensitivity and stability, particularly through the encapsulation of IPMC sensors under optimal water content—a breakthrough that enhances practical reliability for real-world use. This highly cited 2022 paper (16 citations) demonstrates how inner water molecules govern sensor performance, offering a pathway to more durable and accurate devices. In parallel, Shan developed a Bayesian theory-based method for optimal vibration sensor placement on industrial robots, enabling more effective fault diagnosis and structural health monitoring. By combining probabilistic modeling with modal confidence analysis, this work (6 citations) provides a systematic framework for improving signal acquisition in complex robotic systems. Shan’s research bridges materials science and engineering optimization, delivering practical solutions that enhance sensor robustness and diagnostic precision. Their contributions are particularly valuable for students and researchers working on smart materials, robotics, and condition monitoring, offering both theoretical insight and actionable design principles for next-generation sensing systems.
Research Focus
Key Achievements
Top Papers
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- 2