The invention discloses a GIS insulation defect partial discharge atlas pattern recognition method. Analysis is conducted on a typical discharge atlas of GIS insulation defects, the phase and amplitude characteristics of the GIS insulation defects are analyzed according to the atlas of GIS insulation defects, and a mathematical model is built. Then a simulated atlas is generated through the mathematical model, and whether the simulated atlas is consistent with the original atlas is verified. After the verification succeeds, a large amount of discharging data are produced through the built model to be respectively used as a training sample and a testing sample. After the data are obtained, an RBF neural network is constructed, wherein a K-average value clustering method is adopted during trainings. The training samples are input into the neural network for training, the test data is input when the training is finished, and the identification result is obtained through calculation. Finally, a training error allowable value delta is adjusted, so that a high training speed and a high identification correct rate are achieved.