Abstract:Aiming at the classification of natural earthquake events and blasting events, we use 80 natural earthquake events and 20 blasting events in Gansu and its surrounding areas to establish datasets, and apply deep learning convolutional neural network(CNN) method to build two models with different structures for training, and use 500 waveforms of natural earthquakes events and blasting events out of the training sets as test datasets. The accuracy of training and testing is more than 90%. The results show that two training models designed in this paper have a certain generalization ability; especially the Inception V1 model has good effect in the classification and recognition of natural earthquake events and blasting events.