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Correlation Propagation Neural Networks for Safe sensing of Faulty Insulator in Power Transmission Line  

Kim, Jong-Man (전남도립대 전기에너지시스템과)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers P / v.58, no.4, 2009 , pp. 511-515 More about this Journal
Abstract
For detecting of the faulty insulator, Correlation Propagation Neural Networks(CPNN) has been proposed. Faulty insulator is reduced the rate of insulation extremely, and taken the results dirty and injured. It is necessary to detect the faulty insulator and exchange the new one. And thus, we have designed the CPNN to be detected that insulators by the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. Information propagates among neighbor nodes laterally and inter-node interpolation is achieved. 1-D CPNN hardware has been implemented with general purpose. Experiments with static and dynamic signals have been done upon the CPNN hardware. Through the results of simulation experiments, we define the ability of real-time detecting the faulty insulators.
Keywords
Correlation Propagation Neural Networks(CPNN); Faulty Insulator; The Inter-Node Diffusion; Interpolation;
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1 S. Sundar and Z. Shiller, "Optimal Obstacle Avoidance Based on the Hamilton-Jacobi-Bell -man Equation," IEEE Transactions on Robotics and Automation, vol. 12, no. 2, pp.305-310, April 1997
2 I Bekkerman, J. Tabrikian, "Target Detection and Localization using MIMO Radars and Sonars, "Signal Processing, IEEE Transaction, vol.54, Issue 10. pp.3873-3883, Oct. 2006   DOI   ScienceOn
3 Y. Yakimovsky & R. Cunningham, "A System for Extracting Three-Dimension Measurements from a Stereo Pair of TV Cameras", Compuer Graphics and Image Processing 7, pp.195-210, 1978
4 L. Zhang. B. Curless and S. M. Seitz, "Spacetime stereo : Shape recovery for dynamic scenes, "IEEE Computer Society Conference on CVPR, vol. 2, pp II-367-74, 2003
5 C. L. P. Chen, "A rapid supervised learning neural network for function interpolation and approximation," IEEE Trans. Neural Networks, Vol. 7, no.5, pp. 1220-1230, Sept. 1996   DOI   ScienceOn