This paper describes the quantitative analysis and the pattern recognition of partial discharge signals generated by particles in GIS. Four states of particles were simulated in this paper. Partial discharge signals from each state was measured and the Ф-Q-N distribution of partial discharge signals was displayed and then the Ф-Q, the Ф-Qm, the Ф-N and the Q-N distribution were displayed. Each distribution can be quantitatively represented by statistical parameters and the parameters were used for input data of pattern recognition. As the results, it was found that the forms of each distribution were different according to the particle states. Recognition rate using neural network was about 92〔%〕 and the more input data number, the more accurate results.