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Vibration measurement system based on ZigBee and Ethernet
CAO Mengchao, LIU Hua
Journal of Computer Applications    2015, 35 (10): 3000-3003.   DOI: 10.11772/j.issn.1001-9081.2015.10.3000
Abstract405)      PDF (639KB)(367)       Save
In the traditional method of vibration measurement system, the ability of the network construction is weak and the transmission rate is slow. In order to solve these problems, a new kind of vibration measurement was designed using ZigBee and Ethernet. There are three layers in the system. ZigBee based on XBee-PRO was used to establish the communication between collector nodes and router nodes to suit the multipoint and long-span measurement. Ethernet based on LwIP was used to make the data transmitted accurately in real-time. On the end device layer, the data were stored in SD-card in a server node and offered to computers. The experimental results show that the three layers structure of the measurement system combines the strength of ZigBee's network construction ability and Ethernet's high speed and good stability. It can not only realize an effective control to the measure points, but also meet the requirements of a long-span measurement and a real-time data transmission.
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Adaptive weighted mean filtering algorithm based on city block distance
CAO Meng ZHANG Youhui WANG Zhiwei DONG Rui ZHEN Yingjuan
Journal of Computer Applications    2013, 33 (11): 3197-3200.  
Abstract834)      PDF (700KB)(317)       Save
Concerning the defect that the traditional filtering window cannot be adaptively extended and the standard mean filter algorithm could blur edges easily, a new adaptive weighted mean filtering algorithm based on city block distance was proposed. First, the noise points can be detected with switch filtering ideas. Then, for each noise point, the window was extended according to the city block distance, and the window size was adaptively adjusted based on the number of signal points within the window. Last, the weighted mean of the signal points in the window was taken as the gray value of the noise points to achieve the effective recovery of the noise points. The experimental results show that the algorithm can effectively filter out salt-and-pepper noise, especially for the larger-noise-density image, and denoising effect is more significant.
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