http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Zefei Zhu (검색결과 5 건)
- 무료
- 기관 내 무료
- 유료
-
Probabilistic analysis of micro-film buckling with parametric uncertainty
Ying, Zuguang,Wang, Yong,Zhu, Zefei Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.50 No.5
The intentional buckling design of micro-films has various potential applications in engineering. The buckling amplitude and critical strain of micro-films are the crucial parameters for the buckling design. In the reported studies, the film parameters were regarded as deterministic. However, the geometrical and physical parameters uncertainty of micro-films due to manufacturing becomes prominent and needs to be considered. In the present paper, the probabilistic nonlinear buckling analysis of micro-films with uncertain parameters is proposed for design accuracy and reliability. The nonlinear differential equation and its asymptotic solution for the buckling micro-film with nominal parameters are firstly established. The mean values, standard deviations and variation coefficients of the buckling amplitude and critical strain are calculated by using the probability densities of uncertain parameters such as the film span length, thickness, elastic modulus and compressive force, to reveal the effects of the film parameter uncertainty on the buckling deformation. The results obtained illustrate the probabilistic relation between buckling deformation and uncertain parameters, and are useful for accurate and reliable buckling design in terms of probability.
-
Probabilistic analysis of micro-film buckling with parametric uncertainty
Zuguang Ying,Yong Wang,Zefei Zhu 국제구조공학회 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.50 No.5
The intentional buckling design of micro-films has various potential applications in engineering. The buckling amplitude and critical strain of micro-films are the crucial parameters for the buckling design. In the reported studies, the film parameters were regarded as deterministic. However, the geometrical and physical parameters uncertainty of micro-films due to manufacturing becomes prominent and needs to be considered. In the present paper, the probabilistic nonlinear buckling analysis of micro-films with uncertain parameters is proposed for design accuracy and reliability. The nonlinear differential equation and its asymptotic solution for the buckling micro-film with nominal parameters are firstly established. The mean values, standard deviations and variation coefficients of the buckling amplitude and critical strain are calculated by using the probability densities of uncertain parameters such as the film span length, thickness, elastic modulus and compressive force, to reveal the effects of the film parameter uncertainty on the buckling deformation. The results obtained illustrate the probabilistic relation between buckling deformation and uncertain parameters, and are useful for accurate and reliable buckling design in terms of probability.
-
Zhiyu Zhou,Jiusen Guo,Yaming Wang,Zefei Zhu 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.9
Uncalibrated visual servoing control still encounters some challenges, such as calculating the interaction matrix with less cost and keeping the current image features within a camera’s field of view (FOV) in a noisy system environment. To solve these problems, we propose a new control method that uses a random vector functional link network with L21 norm regularization to calculate the interaction matrix and further estimate it with a robust information filter (RIF). L21 norm regularization can deal with the global sparsity of input weights and reduce the inherent complexity of a model. The RIF limits noise variance within a certain range to reduce the influence of uncertain noise on the servoing task. We also design a method that reacts to the control law in accordance with the coordinates of image features. It can adjust running speed in real time and keep image features within a camera’s FOV. We apply this method to a six-degrees-of-freedom eye-in-hand manipulator, and several simulations are performed. Simulation results show that the proposed algorithm performs well in the task and achieves good performance in terms of noise resistance. Image features barely escape from the camera’s FOV through the proposed constraint method.
-
( Zhiyu Zhou ),( Junjie Wang ),( Yaming Wang ),( Zefei Zhu ),( Jiayou Du ),( Xiangqi Liu ),( Jiaxin Quan ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.11
Object detection and tracking is the basic capability of mobile robots to achieve natural human-robot interaction. In this paper, an object tracking system of mobile robot is designed and validated using improved multiple instance learning algorithm. The improved multiple instance learning algorithm which prevents model drift significantly. Secondly, in order to improve the capability of classifiers, an active sample selection strategy is proposed by optimizing a bag Fisher information function instead of the bag likelihood function, which dynamically chooses most discriminative samples for classifier training. Furthermore, we integrate the co-training criterion into algorithm to update the appearance model accurately and avoid error accumulation. Finally, we evaluate our system on challenging sequences and an indoor environment in a laboratory. And the experiment results demonstrate that the proposed methods can stably and robustly track moving object.
-
Zhiyu Zhou,Yanjun Hu,Jiangfei Ji,Yaming Wang,Zefei Zhu,Donghe Yang,Ji Chen 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.8
Visual servoing (VS) based on the Kalman filter (KF) algorithm, as in the case of KF-based image-based visual servoing (IBVS) systems, suffers from three problems in uncalibrated environments: the perturbation noises of the robot system, error of noise statistics, and slow convergence. To solve these three problems, we use an IBVS based on KF, African vultures optimization algorithm enhanced extreme learning machine (AVOA-ELM), and fuzzy logic (FL) in this paper. Firstly, KF online estimation of the Jacobian matrix. We propose an AVOA-ELM error compensation model to compensate for the sub-optimal estimation of the KF to solve the problems of disturbance noises and noise statistics error. Next, an FL controller is designed for gain adaptation. This approach addresses the problem of the slow convergence of the IBVS system with the KF. Then, we propose a visual servoing scheme combining FL and KF-AVOA-ELM (FL-KF-AVOA-ELM). Finally, we verify the algorithm on the 6-DOF robotic manipulator PUMA 560. Compared with the existing methods, our algorithm can solve the three problems mentioned above without camera parameters, robot kinematics model, and target depth information. We also compared the proposed method with other KF-based IBVS methods under different disturbance noise environments. And the proposed method achieves the best results under the three evaluation metrics.
KISS연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
