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Research Of WSN Aggregation Node Information Fusion Algorithm

Posted on:2015-04-01Degree:MasterType:Thesis
Country:ChinaCandidate:L XuFull Text:PDF
GTID:2322330509958856Subject:Carrier Engineering
Abstract/Summary:PDF Full Text Request
Automatic monitoring for a single lamp of airport airfield lighting is an inevitable trend for fault inspection of airfield lighting. In the monitoring system of airport airfield lighting single lamp based on wireless sensor network(WSN, Wireless Sensor Network), the rapid data processing of aggregation node is critical to the emergency response of monitoring system. Using pulse coupled neural network(PCNN, Pulse Coupled Neural Network) to process fault message of airfield lighting. It has a very important significance to improve the life and reliability of the monitoring system of airfield lighting, strengthen the airport airfield lighting emergency timeliness response capability and ground support capability, and ensure the safety of aircraft.Firstly, the data fusion methods based on wireless sensor networks are described. To deal the data fusion with high efficiency, improve system timeliness and guarantee failure information classification accuracy, we propose an aggregation node data fusion method based on pulse coupled neural network. Based on this approach, we did data fusion experiments to make a comparison with BP neural network in software implementation. The simulation results show that this network is superior to BP neural network in data fusion. It can carry out failures emergency treatment effectively, save system resources and improve the fault classification accuracy and speed. Due to the real-time requirements of airport airfield lighting monitoring in emergency treatment when airport airfield lighting failed, so the FPGA hardware implementation is used as a platform. We take full advantage of multi-chip hardware multiplier which can perform parallel computation in the chip to carry out data fusion algorithm and can obtain higher fusion speed. Preliminary experiments show that using the WSN aggregation node pulse coupled neural network data fusion processing can improve the timeliness and accuracy to achieve fault information judgment and emergency aids of airfield lighting.
Keywords/Search Tags:pulse coupled neural network, aggregation node, data fusion, airfield lighting
PDF Full Text Request
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