Aiming at the problems of complex process and poor effect in manual interpretation of ammunition chain motion law, a classification and recognition method of ammunition chain motion acceleration based on 1D convolutional neural network (1D-CNN) model is proposed by combining the one-dimensional characteristics of ammunition chain motion acceleration. The 1D-CNN model was built based on Keras deep learning framework. The data of ammunition chain motion acceleration signal obtained from small bore automatic gun firing test was preprocessed, and the training set and test set were made to train and test the 1D convolutional neural network model. The results show that the 1D-CNN model can realize the classification and recognition of ammunition chain motion acceleration signal, and the accuracy rate is about 84%, which achieves the expected effect.