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Hong, D.S.;Shim, J.C.;Jong, B.H.;Yun, S.Y.;Bae, Y.C.;Ryu, C.W.;Yim, H.Y.
- Proceedings of the KIEE Conference
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- 2001.07d
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- pp.2184-2186
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- 2001
The research presented in this paper focuses on a method for the detection of High Impedance Fault(HIF). The method will use the fast wavelet transform and neural network system. HIF on the multi-grounded three-phase four-wires primary distribution power system cannot be detected effectively by existing over current sensing devices. These paper describes the application of fast wavelet transform to the various HIF data. These data were measured in actual 22.9kV distribution system. Wavelet transform analysis gives the frequency and time-scale information. The neural network system as a fault detector was trained to discriminate HIF from the normal status by a gradient descent method. The proposed method performed very well by proving the right state when it was applied staged fault data and normal load mimics HIF, such as arc-welder.
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지남현;전병민
- The Journal of the Korea Contents Association
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- v.3 no.2
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- pp.31-38
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- 2003
This paper proposes method to insert soong Watermark considering dull HVS properties to big change of Edge and Texture area. While conversion of existent Fourier form can acquire information for whole frequency ingredient of image, but Wavelet transform can look for Edge and Texture area locally. Therefore, use Wavelet transform to use HVS properites, and compare with Xia's Watermarking techniques to use Wavelet transform simply arid experimented these proposal algorithm. Experimented about fidelity and robusthness by attack method that is used in existing paper, and as a result, confirmed that proposal algorithm that use HVS properties is more superior than Xia's techniques.
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