DocumentCode :
1811748
Title :
Data collection in wireless sensor networks
Author :
Yin, Kaicheng ; Zhong, Chaosheng
Author_Institution :
Huaiyin Inst. of Technol. Libr., Huaiyin, China
fYear :
2011
fDate :
15-17 Sept. 2011
Firstpage :
98
Lastpage :
102
Abstract :
There are many auxiliaries with high rotating speed in a power plant, such as pumps, fans, motors and so on. To warrant their safe and reliable operation, their state of vibration has to be monitored. But because of their scattered location, the traditional way of online vibration monitoring with shielded cable connections is costly and work expensive. In this paper a novel method of vibration monitoring for auxiliaries in power plants based on wireless sensor networks has therefore been proposed to realize vibration data acquisition, on-line-detection and data analyzing in this paper, which meets the requirements of auxiliaries with less expenditure and warrants safe operation in the long run. Due to the restrictions of energy and bandwidth on wireless sensor networks, how to utilize the limited resources to acquire available and reliable data from the sensor nodes becomes a hot topic. After modelling and analyzing on mass data by time-sequence technique, a reliable data collection method based on AR(P) model with Petri Net technique are designed in order to improve the whole performance of the system, prolong the lifetime of the network and decrease the energy consumption of the sensor nodes.
Keywords :
Petri nets; energy consumption; energy management systems; sensor fusion; wireless sensor networks; Petri Net technique; energy consumption; limited resources; reliable data collection method; sensor nodes; time-sequence technique; wireless sensor networks; Data models; Mesh networks; Monitoring; Power generation; Real time systems; Vibrations; Wireless sensor networks; AR(P) model; data fusion; energy management; multi-sink topological structure; petri network; vibration; wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-61284-203-5
Type :
conf
DOI :
10.1109/CCIS.2011.6045040
Filename :
6045040
Link To Document :
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