Kaiping Yu

Work place: Department of Astronautical Science and Mechanics, Harbin Institute of Technology, Harbin, Heilongjiang, China

E-mail: yukp@hit.edu.cn

Website:

Research Interests: Engineering

Biography

Kaiping Yu received the B.Sc. degree in engineering mechanics from Shanghai Jiao Tong University, Shanghai, China in 1989 and the M.Sc. degree in Vibration, Shock and noise and the Ph.D. degree in General mechanics and mechanics foundation from Harbin Institute of Technology, Harbin,China, in 1996 and 2000, respectively. He achieved his civil-engineering Post-doctor in Institute of engineering mechanics, China earthquake administration in 2002.He had been engaged in space station design in Department of Aircraft Design, Samara State University, Samara Oblast, Russia, from October, 1998 to March, 1999. He worked as a visiting scholar in Launch vehicle and spacecraft, Department of Special machine Manufacturing, Bauman Moscow State Technical University, Moscow, Russia from October, 2003 to October, 2004. His current research interests are computational mechanics, Structure Dynamics and control, vibration theory and its application, Dynamical theory of high-speed underwater vehicle and its trial Since 2005, he has been a professor in Department of Astronautical Science and Mechanics, Harbin Institute of Technology, Harbin, Heilongjiang, China.

Author Articles
Fast Time-varying modal parameter identification algorithm based on two-layer linear neural network learning for subspace tracking

By Kai Yang Kaiping Yu

DOI: https://doi.org/10.5815/ijieeb.2011.01.03, Pub. Date: 8 Feb. 2011

The key of fast identification algorithm of time-varying modal parameter based on subspace tracking is to find efficient and fast subspace-tracking algorithm. This paper presents a modified version of NIC(Novel Information Criterion) adopted in two-layer linear neural network learning for subspace tracking, which is applied in time-varying modal parameter identification algorithm based on subspace tracking and get a new time-varying modal parameter identification algorithm. Comparing with the original subspace-tracking algorithm, there is no need to set a key control parameter in advance. Simulation experiments show that new time-varying modal parameter identification algorithm has a faster convergence in the initial period and a real experiment under laboratory conditions confirms further its validity of the time-varying modal identification algorithm presented in this paper.

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