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About

Fulei Chu is a distinguished researcher whose work bridges mechanical engineering, robotics, and intelligent fault diagnostics. His primary research areas include rotating machinery fault detection, robot mechanism theory, and humanoid robot architecture. Chu’s most impactful contribution is his novel piecewise power fitting method for normalizing vibration signals, enabling more accurate intelligent fault detection in rotating machinery—a critical advancement for industrial predictive maintenance, with his 2024 paper already garnering 11 citations. He has also made foundational contributions to screw theory, proposing a unified analytical methodology to identify principal screws of two- and three-screw systems, which advances the mathematical modeling of robotic mechanisms. His work on the free motion of robot end effectors and innovative architecture for humanoid robot lower limbs—inspired by human biomechanics—demonstrates his commitment to practical, biologically informed design. With a career spanning over a decade, Chu’s research is widely cited in both mechanical and robotics engineering communities, reflecting its impact on real-world applications from factory automation to humanoid robotics. His achievements highlight a rare ability to combine theoretical rigor with engineering innovation.