Hsiang-Yuan Ting
Papers
2
Total Citations
34
H-Index
2
About
Dr. Hsiang-Yuan Ting is a robotics researcher specializing in intelligent fault diagnosis, industrial robot health evaluation, and safe human-robot interaction. His most cited work, "Intelligent Fault Detection, Diagnosis and Health Evaluation for Industrial Robots" (2021, 31 citations), introduces a sophisticated system that leverages principal component analysis-based statistical process control combined with Nelson rules to enable real-time online fault detection in industrial robotic systems—a critical advancement for predictive maintenance and operational reliability. In parallel, Dr. Ting explores the human factors of robotics through his work "Importing the Human Factor into Safe Human–Robot Interaction Function Using the Bond Graph Method" (2020), which addresses post-collision safety by modeling variable stiffness actuators to reduce robot stiffness upon impact, thereby minimizing injury risk during human-robot collaboration. By bridging data-driven diagnostics with physical safety mechanisms, Dr. Ting’s research contributes directly to the development of more intelligent, safer, and more dependable robotic systems for industrial and collaborative environments.
Research Focus
Key Achievements
Top Papers
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