| Comparison with traditional apparatus devices, Gas Insulated Switchgears (GIS) has salient advantages. Its appearance gives a revolution in power domain. The in service experiences show that internal GIS exists defects inevitably in spite of high reliability running. Partial discharge (PD) phenomena are most common characteristic before insulation breakdown in GIS. By PD on-line monitoring systems, GIS internal defects can be discovered in time to avoid the occurrence of fatal failure. So the research of PD detection and its pattern recognition for GIS is very important to guarantee its safe operation, to find out its insulation condition and defects type in time and to guide its maintenance. In this paper, according to the experimental study of GIS PD excited electromagnetic wave (EMW), the excitation, transmission, attenuation and leakage characteristic for the EMW show that PD signal in ultra high frequency (UHF) band could propagate in GIS, and could occur reflect and refraction, have a bit of attenuation, leak out in GIS spacer. According to the utility and the convenience, a UHF outer antenna sensor which is rectangular-patch micro-strip antenna is successfully developed, compared with the other outer antenna, it's easy to install and fix to the next circuit. The measured parameter show the received antenna of PD signal in GIS is sensitive and is suit to measure in UHF. PD sample data of different artificial defect models are got by PD detection system in laboratory, and are compared with the signals which other sensor received. Based on present various pattern recognition methods, the hybrid method on account of fractal and wavelet theory is presented. According to three kinds of experimental defects, based on hundreds test data sampled by outer antenna sensor, the PD signal feature is extracted by fractal dimension discussed theoretically. The study shows that fractal dimension is a perfect feature, and combines to wavelet configuration idea and method. This paper utilizes wavelet to decompose the PD signals in time-frequency domain. The fractal dimension feature under different simulated PD signal could be apparently be distinguished and the PD patterns could be recognized evidently. The combination of wavelet theory and fractal theory could be applied to the PD pattern recognition . The combination have a wide outlook in insulation diagnosis and have theoretical values of character information of pattern recognition for future measuring on-line in GIS.
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