GIS partial discharge recognition based on chaos features of the three-dimensional spectra

Diangong Jishu Xuebao/Transactions of China Electrotechnical Society

Volumn 30, Issue 1, 2015, Pages 249-254

  Zhang, Xiaoxing ^a   Shu, Na ^a   Xu, Xiaogang ^b   Li, Xin ^b   Tang, Ju ^a  

^a CHONGQING UNIVERSITY   (China)

^b GUANGDONG POWER GRID CORPORATION   (China)

Author keywords

GIS; Partial discharge; Pattern recognition; SVM

Indexed keywords

CHAOS THEORY; DIFFERENTIAL EQUATIONS; ELECTRIC SWITCHGEAR; FAULT DETECTION; GEOGRAPHIC INFORMATION SYSTEMS; LYAPUNOV FUNCTIONS; PARTIAL DISCHARGES; PATTERN RECOGNITION;

CHAOTIC CHARACTERISTICS; DISTRIBUTION CHARACTERISTICS; GAS INSULATED SWITCHGEAR(GIS); LARGEST LYAPUNOV EXPONENT; OPERATION CONDITIONS; PARTIAL DISCHARGE RECOGNITION; PATTERN RECOGNITION METHOD; SVM;

LYAPUNOV METHODS;

EID: 84921667917     PISSN: 10006753     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (18)

1. Satish L, Zaengl W S. Can fractal features be used for recognizing 3-D partial discharge patterns?[J]. IEEE Transactions on Electrical Insulation, 1995, 2: 352-359.
2. Gulski E. Application of modern PD detection techniques to fault recognition in the insulation of high voltage equipment[C]. 9th International Symposium on High Voltage Engineering, Graz, Austria, 1995: 5642.
3. Zhang Zhousheng, Ma Aiqing, Sheng Gehao. Time-frequency characteristic based partial discharge pulses identification technique for the high voltage XLPE power cables[J]. High Voltage Engineering, 2011, 37(8): 1997-2003.
4. Si Wenrong, Li Junhao, Yuan Peng, et al. The fast grouping technique of PD sequence based on the nonlinear mapping of pulse shapes[J]. Transactions of China Electrotechnical society, 2009, 24(3): 216-221, 228.
5. Sahoo N C, Salama M M A, Bartnikas R. Trends in partial discharge pattern classification: a survey[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2005, 12(2): 248-264.
6. Mazroua A A, Salama M M A, Bartnikas R. PD pattern recognition with neural networks using the multilayer perceptron technique[J]. IEEE Transactions on Electrical Insulation, 1993, 28; 1082-1089.
7. Cavallini A, Montanari G C, Contin A, et al. A new approach to the diagnosis of soild insulation systems based on PD signal inference[J]. IEEE Electrical Insulation Magazine, 2003, 19(2): 23-30.
8. Lim Y, Chaotic Koo J. Analysis of partial discharge (CAPD) as a novel approach to investigate insulation degradation caused by the various defects[C]. Proceedings of the IEEE International Symposium on Industrial Electronics, Pusan, Korea, 2001.
9. Hao L, Lewin P L. Partial discharge source discrimination using a support vector machine[J]. IEEE Transactions on Dielectric Electrical Insulation, 2010, 17(1): 189-197.
10. Zhang Xiaoxing, Sun Caixin, Tang Ju, et al. PD pattern recognition based on optimal sets of statistical uncorrelated discriminant vectors in GIS[J]. Automation of Electric Power Systems, 2006, 30(5): 59-62.
11. Lim Y, Koo J. Chaotic analysis of partial discharge (CAPD) -a novel approach to identify the nature of PD source[C]. Annual Report Conference on Electrical Insulation and Dielectric Phenomena, 2001: 324-328.
12. Luo Yongfen, Huang Ping, Li Yanming. Chaotic characteristics of partial discharges time series in oil-paper insulation with applications to pattern recognition[J]. Journal of Xi'an Jiaotong University, 2010, 44(12): 55-60.
13. Boeck W, et al. Diagnostic methods for GIS insulating systems[C]. CIGRE: 1992 Session, Paris: 151-182.
14. Grassberger P, Procaccia I. Measuring the strangeness of strange attractors[J]. Physica D, 1983, 9(1/2): 189-208.
15. Grebogi C, Ott E, Yorke J A. Final state sensitivity an obstruction to predictability[J]. Phys. Lett. A, 1983, 99: 415-419.
16. Wolf A, Swift J B, Swinney H L, et al. Determining lyapunov exponents from time series[J]. Physica, 1985, D16: 285-317.
17. Yang Zhongjin. Kernel-based support vector machines [J]. Computer Engineering and Applications, 2008, 44(33): 1-6, 24.
18. Jiang Lei, Zhu Deheng, Li Fuqi, et al. ANN based discharge pattern recognition of insulation models of electrical transformers[J]. Proceedings of the CSEE, 2001, 21(1): 21-24.