Pattern recognition for partial discharge in GIS based on pulse coupled neural networks and wavelet packet decomposition

• Autorzy: Zhou J. , Tang J. , Zhang X. , Tao J.

Warianty tytułu

PL

Rozpoznawanie cech wyładowania niezupełnego w wyłącznikach gazowych z wykorzystaniem impulsowo sprzężonych sieci neuronowych i transformaty falkowej

• Języki publikacji: EN

Abstrakty

EN

Based on the characteristics of partial discharge (PD) defects in gas insulated switchgear (GIS), four typical single defects were designed for the present paper. PD three-dimensional (3D) patterns were constructed based on the ultra high frequency detection systems. The pulse-coupled neural networks (PCNN) and wavelet packet decomposition (WPD) method were used in PD feature extraction. The recognition results show that the proposed method used in PD feature extraction can effectively improve the accuracy of pattern recognition rate.

PL

Przeanalizowano defekty wyłącznika gazowego z wyładowaniem niezupełnym. Defekty te przedstawiane są jako obrazy 3D. Do ekstrakcji cech tych obrazów wykorzystuje się transformatę falkową i impulsowo sprzężone sieci neuronowe.

Słowa kluczowe

EN

gas insulated switchgear; pulse coupled neural network (PCNN); wavelet packet decomposition

PL

wyłącznik gazowy; wyładowanie niezupełne; transformata falkowa

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2012
• Tom: R. 88, nr 5b
• Strony: 44--47
• Opis fizyczny: bibliogr. 15 poz., rys., tab.

Twórcy

autor

Zhou J.

autor

Tang J.

autor

Zhang X.

autor

Tao J.

• State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University

Bibliografia

• [1] Chang C., Chang C.S., Jin J., Hoshino T., Hanai M., Kobayashi N., Source classification of partial discharge for gas insulated substation using wave shape pattern recognition, IEEE Trans. Dielect. Elect. Insul., 12(2005), No. 2, 374–386
• [2] Zhou Q., Tang J., Tang M., Xie Y., Study on mathematical model for VHF partial discharge of typical insulated defects in GIS, IEEE Trans. Dielect. Elect. Insul., 14(2007), No.1, 30–38
• [3] Iraida K., Igor K., Using electro magnetic PD sensors for diagnostics of high voltage equipment, Electrical Review, (2003), No.1
• [4] Barbara F., Paweł Z., Analysis of partial discharge forms in SF6 for diagnostics of GIS, Electrical Review, (2005), No.1
• [5] Muresan R.C., Pattern recognition using pulse-coupled neural networks and discrete Fourier transforms, Neurocomputing, 51(2003), 487-493
• [6] Godin C., Gordon M. B., Muller J. D., Pattern recognition with spiking neurons-performance enhancement based on a statistical analysis, IEEE International Joint Conference on Neural Networks, (1999), 1876-1880
• [7] Karvonen J., A simplified pulse-coupled neural network based sea-ice classifier with graphical interactive training, Proceedings of the IEEE International Geosciences and Remote Sensing Symposium, 2(2000), 681-684
• [8] Rughooputh H. C. S., Bootun H., Rughooputh S. D. D. V., Pulse coded neural network for sign recognition for navigation. IEEE International Conference on Industrial Technology, 1(2003), 103-105
• [9] Waldemark J., Becanovic V., Lindblad T., Hybrid neural networks for automatic target recognition, IEEE International Conference on System, Man, and Cybernetics, 4(1997), 4016-4021
• [10] Johnson J.L., Pulse-coupled neural nets: translation, rotation, scale, distortion, and intensity signal invariance for images, Applied Optics, 33(1994), No.26, 6239-6253
• [11] Becanovic V., Kermit M., Eide A. J., Feature extraction from photographic images using a hybrid neural network, SPIE Proceedings, Ninth Workshop on Virtual Intelligence/ Dynamic Neural network, 3728(1999), 351-361
• [12] Tang J., Sun C.X., Peng W.X., Extracting partial discharge signals from white noise by wavelet packet transform in GIS, Automation of Electric Power Systems, 28(2004), No.5, 25-29
• [13] Xu G.F., Sun C.X., Lu C.H., Compression and Reconstruction for Partial Discharge signals Based on Optimal Wavelet Packets Algorithm Combining with Multi-objective Optimization, Chinese Journal of Scientific Instrument, 25(2004), No.1, 57-60
• [14] Iraida K., Juraj K., Roman C., Multi-scale decomposition for partial discharge analysis, Electrical Review, (2008), No.9
• [15] Marcin L., Tomasz B., Wavelet analysis of the signals modeling the apparatus used in the acoustic method of partial discharge measurement, Electrical Review, (2006), No.1