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- 저자 : Shimin Zhu (검색결과 2 건)
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Ground Motion Frequency Insensitivity of Bearing-Supported Pedestrian Bridge with Viscous Dampers
Qunfeng Liu,Shimin Zhu,Wenshan Yu,Xing Wu,Fei Song,Xiang Ren 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.7
This work studies the dynamic responses of bearing-supported pedestrian bridges with Y-shaped piers and various deck widths under harmonic ground motions. To fulfill the immediate occupancy performance objective, the dynamic responses of bridges with linear or nonlinear viscous dampers are evaluated by performing nonlinear time-history analyses. The results show that the maximum transverse displacements of girder and pier top in original bridges are closely dependent on the characteristic period of ground motion. The installation of linear viscous dampers between steel girder and Y-shaped piers can effectively improve the seismic performance of bridges and hence reduce the corresponding shear demand of bearings. Further parametric studies show that, with optimal damping coefficient and velocity exponent, the seismic performances of bridges with viscous dampers can be insensitive to the characteristic period of ground motion.
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Chong Chen,Shimin Zhang,Xiaoxiao Zhu,Jingyu Shen,Zhiyao Xu 한국정밀공학회 2020 International Journal of Precision Engineering and Vol.21 No.5
Many patients with stroke are suff ering lower limb locomotor dysfunctions all over the world. Body weight supported treadmilltraining has proven to be an eff ective post-stroke rehabilitation training method for these people’s recovery. Nowadays,lower extremity rehabilitation exoskeleton composed of a pair of mechanical legs has been introduced into body weightsupported treadmill training, which can guide and assist the movements of the patient’s legs. However, active movementsof the patient are hardly to be achieved when the rehabilitation exoskeleton is controlled by a commonly utilized positionbasedpassive strategy. Considering the restriction above, a weight supported rehabilitation training exoskeleton device wasdesigned in this paper to ensure the stroke patient can participate in rehabilitation training voluntarily. To realize this goal,a patient-cooperative rehabilitation training strategy based on adaptive impedance control is adopted for the swing phase inthe training. Human–exoskeleton interaction torques are evaluated by a backpropagation neural network and a disturbanceobserver whose stability is proved by Lyapunov’s law. With no additional demand of interaction torque sensors, the complexityof this system is simplifi ed and the cost is reduced. In order to promote the involvement of patient during the rehabilitationtraining, fuzzy algorithm is used to adjust the impedance parameters according to the human–exoskeleton interaction torques. The eff ectiveness of the whole rehabilitation control strategy is demonstrated by experimental results.
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