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EN
The three-dimensional (3D) coordinate measurement of radio frequency identification (RFID) multi-tag networks is one of the important issues in the field of RFID, which affects the reading performance of RFID multi-tag networks. In this paper, a novel method for 3D coordinate measurement of RFID multi-tag networks is proposed. A dual-CCD system (vertical and horizontal cameras) is used to obtain images of RFID multi-tag networks from different angles. The iterative threshold segmentation and the morphological filtering method are used to process the images. The template matching method is respectively used to determine the two-dimensional (2D) coordinate and the vertical coordinate of each tag. After that, the 3D coordinate of each tag is obtained. Finally, a back-propagation (BP) neural network is used to model the nonlinear relationship between the RFID multi-tag network and the corresponding reading distance. The BP neural network can predict the reading distances of unknown tag groups and find out the optimal distribution structure of the tag groups corresponding to the maximum reading distance. In the future work, the corresponding in-depth research on the neural network to adjust the distribution of tags will be done.
EN
Quayside container crane is a kind of large dimension steel structure, which is the major equipment used for lifting container at modern ports. With the aim to ensure the safety and reliability of the crane under seismic loads, an anti-seismic device is designed. To validate the efficiency and reliability of the anti-seismic device, elastic-plastic time history analysis under rare seismic intensity is carried out. And the results of elastic-plastic time history analysis when the crane installed anti-seismic device and uninstalled the device are compared.
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