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RISS 인기검색어
- 검색키워드
- 저자 : Fuyang Wang (검색결과 4 건)
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Fuyang Chen,Zheng Wang,Bin Jiang,Changyun Wen 제어·로봇·시스템학회 2015 International Journal of Control, Automation, and Vol.13 No.3
In this paper, an improved nonlinear model for a 3-DOF helicopter and its self-repairing control scheme are investigated via quantum information technique. Firstly, adopting the mechanism analysis, a modified dynamic model is developed, in which the couplings among axes are considered. Such a modeling scheme is useful for applications when the accuracy of original model can not be satisfied. Then, a reconfigurable control scheme is designed for the twin rotor helicopter with multiple faults and parametric uncertainties, which combines active disturbance rejection control method with model reference adaptive control method. In addition, quantum information technique is used to increase the accuracy of self-repairing control of helicopter. Finally, simulation verification is presented in both aspects of modeling and control. The effectiveness and feasibility of the proposed scheme are verified by comparative simulations.
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Study on Dynamic Behavior of Single-Layer Reticulated Dome by Shaking Table Test
Gui-bo Nie,Xing-long Zhu,Xudong Zhi,Fuyang Wang,Jun-Wu Dai 한국강구조학회 2018 International Journal of Steel Structures Vol.18 No.2
Large-span space structures in the form of reticulated domes, which have developed rapidly in the last three decades, are widely used in large-scale public buildings . In order to have a better understanding of its mechanical performance and verify the failure pattern under seismic motion, a shaking table test of a single-layer reticulated dome was carried out. The geometric position of the structural nodes and material properties of the members were measured, such as yield strength and Young’s modulus . The dynamic characterization of the model under white-noise excitation and fast size frequency was then performed to obtain its natural vibration frequency and damping factor. Next, the mechanical performance of the model under weak and strong seismic motions was investigated experimentally. Finally, a comparison between the experimental and numerical results obtained using the fi nite element software ABAQUS was made and a satisfactory agreement was found. The occurrence of large-scale deformation and signifi cant material plasticity of these structures under severe seismic motion can be regarded as indicators of dynamic strength failure. This is the fi rst time that the pattern of dynamic strength failure has been observed via shaking table tests.
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Three-Dimensional Seismic Isolation Study of Single-Layer Reticulated Domes by Parameter Analysis
Gui-Bo Nie,Dong-fang Li,Xudong Zhi,Qiang Chen,Fuyang Wang 한국강구조학회 2021 International Journal of Steel Structures Vol.21 No.6
Spatial structures, represented by reticulated domes, have developed rapidly in the last several decades due to their reasonable mechanical properties and beautiful structural shape. However, several spatial structure collapses have occurred during the recent frequent earthquakes in China, especially the 2013 Lushan earthquake. These collapses have altered the traditional understanding that the spatial structure has good seismic performance. Real seismic damage cases reveal that a spatial structure in a severe earthquake zone with unreasonable seismic design cannot maintain its functional characteristics; therefore, there is an urgent need for improvements to enhance the seismic performance of spatial structures. This paper proposes a new three-dimensional isolation spring support (TISS). To study the mechanical properties of this support, corresponding experiments were performed, and the constitutive relation of this support was investigated. A simplifi ed fi nite element model of the new TISS was defi ned in ABAQUS to conduct a seismic isolation study of single-layer reticulated domes. And then the infl uence of diff erent parameters on the seismic isolation performance of the TISS was analysed. The parameter analysis results indicated that friction plays an important role in the mechanical properties of the support and thus causes diff erent seismic isolation eff ects under small earthquakes and severe earthquakes. At the same time, because of the design concept of the support, a non-linear relation exists between the seismic isolation eff ect and stiff ness such that under severe earthquakes. On the other hand, the TISS also has preferable isolation performance on the defective reticulated domes. Therefore, the three-dimensional isolation support presented in this paper has preferable application prospects and potential economic benefi ts that could be applied extensively in the three-dimensional isolation area of spatial structures. In addition, the numerical analysis procedure based on ABAQUS can be used to accurately analyse the isolation property and to lay the foundation for the practical function of isolation supports and the seismic design of structures.
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Fu Yang,Wang Shuo,Jia Feng,Zhou Quan,Ge Xiaolin 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.3
Due to the limited accessibility of wind turbines (WTs) and the complexity of operation and maintenance (O&M), it is increasingly important to early warn the component faults of WTs, and the difculties lie in balancing the comprehensiveness and delicacy of early warning. In this paper, a two-stage cascaded high-precision fault early warning method based on machine learning (ML) and data graphization is proposed. The frst stage copes with the early warning of the main components, in which the supervisory control and data acquisition (SCADA) data are converted into Gramian Angular Field (GAF) images to establish the potential relationship of fault features at diferent time points, and the fault characteristics are extracted by convolutional neural network (CNN) to realize fault early warning for multiple main components simultaneously. The second stage focus on the fault subcomponents inside the main components further, in which the time generative adversarial network (TimeGAN) is adopted to enhance the fault code data samples, then the enhanced data in the form of grayscale images is input into the Vision Transformer (ViT) to train the subcomponent early warning model. The proposed method is validated with real SCADA data, the results show the efectiveness of the proposed method.
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