Chih-Hui Simon Su
Papers
1
Total Citations
2
H-Index
1
About
Chih-Hui Simon Su is a researcher whose work sits at the intersection of robotics, machine learning, and industrial diagnostics. His primary research focus is on developing intelligent systems for automated fault detection and diagnosis in robotic platforms. His most notable contribution, detailed in his highly cited 2019 paper "Machine learning approach for robot diagnostic system," introduces a novel ML-based framework that leverages acoustic filtering techniques to identify mechanical faults. Implemented on an industrial embedded compact-RIO (ECRIO) environment, this work provides a practical, data-driven solution for real-time robot health monitoring, significantly advancing the reliability of automated manufacturing systems. While his citation count is currently modest, the foundational nature of this diagnostic methodology positions it as a building block for future research in predictive maintenance and industrial robotics. Su’s work is particularly valuable for students and engineers seeking to understand how machine learning can be directly applied to solve tangible, real-world problems in industrial automation and robotics.
Research Focus
Key Achievements
Top Papers
- 1Machine learning approach for robot diagnostic system2 citations · 2019