The present work is aimed at presenting the disturbance generated by a solar array drive assembly (SADA) driving a flexible system. Firstly, the vibration equation of SADA is obtained by simplifying and linearizing the electromagnetic torque. Secondly, the disturbance model of SADA driving a discrete flexible system is achieved based on the vibration equation established. Taking a two-dof flexible system as the study object, this disturbance model is simulated and analyzed. Lastly, a continuous flexible system, which is designed to simulate the solar array, is used to illustrate the simulation method of the disturbance emitted by SADA driving a continuous flexible system. All the achievements obtained from this project will provide a theoretical basis for the prediction of the disturbance emitted by the SADA driving solar array on the orbit.
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To efficiently implement emergency response program to port unexpected incidents, a perfect emergency supply system which including communications supplying, transportation supplying and rescue equipments supplying must be ready-to-used. Considering physical geography, harbor area, possible incident type and incident scale and other factors, using multi-objective fuzzy decision theory to set up emergency supply centers, improving sharing resource mechanism, administrative legislation and other measures are be used to improve port emergency supply system. Shanghai port’s practice prove the improve port emergency supply system is effective.
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The problem of efficient interactive extraction of a foreground object in a complex environment is the primary one in image processing and computer vision. The segmentation method based on graph cuts has been studied over the recent years. There are two main drawbacks of these studies: decrease in performance when the foreground and the background have similar colors, and long computing time when the image is large. In this paper, we present a new foreground objects extraction method using a region-based graph cuts algorithm. The image is pre-segmented into a large number of small partitions using the mean shift (MS) method. We use the partitions to represent the nodes in the graph instead of pixels. This approach can reduce the optimization time, which is closely related to the number of nodes and edges in the graph. Compared with the pixel-based method, our method can yield an excellent performance and exhibit a faster speed.
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