Abstract: To address the problem that the data-driven pipeline leak detection method fails to effectively utilize the spatial and temporal characteristics of the leak signal simultaneously,a pipeline leak identification method based on a combination of one-dimensional convolutional neural network（1 D-CNN）and long short-term memory network（LSTM）is proposed. The network model takes the de-noised pipeline pressure signal as the input source,the spatial and temporal dimensional features are extracted by using 1 D-CNN and LSTM successively and the correspondence is established between the pressure signal and the pipeline condition by using the spatio-temporal features extracted in two different dimensions,thus realizing the detection of pipeline leaks. The experimental results show that the features extracted by the 1 DCNN-LSTM method are more effective and reliable,and the accuracy of pipeline leak detection is significantly improved.