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Vibration control and genetic algorithm based design optimization on self-sensing active constrained layer damped rotating plates

English Abstract

This thesis investigates the vibration of a rotating constrained layer damped plate system. Although currently, most existing research utilizes rotating structures as modeled beams, this work however, models rotating structures as plates with constrained layer damping. Through the models investigated, this thesis develops a single layer plate finite element model for a rotating structure to improve in both accuracy and versatility. Concurrently, existing research shows that the damping of the active constrained layer can provide more damping than the damping of the passive constrained layer Therefore, in this work the constraining layer is made of piezoelectric material and thus, will work as both the self-sensing sensor and the actuator. In addition, a proportional control strategy is implemented to effectively control the damping in the rotating plate; parametric study is also conducted to explore the impact of some design parameters on structure’s modal characteristics. Furthermore, due to a large number of design variables in the complex model incorporating visco-elastic damping, this work examines the application of genetic algorithm (GA) in optimizing the first two resonance amplitudes of the driving point mobility at the center of the rotating plate. A genetic algorithm is applied to simultaneously determine several design parameters which maximize an objective function. Compared with a typical gradient search approach Quasi-Newton method, GA can be more efficient and effective in finding the optimum configuration with the highest objective function value in the numerical example.

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Chong, Ian Ian


Faculty of Science and Technology


Department of Electromechanical Engineering





Genetic algorithms

Damping (Mechanics)


Wong, Pak Kin

Xie, Zheng Chao

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