Abstract: A method of constructing a water supply pipeline leakage identification model based on deep learning and an application thereof are provided, which relate to the technical field of nondestructive detection and positioning of municipal water supply pipeline leakage. By extracting Mel-frequency cepstral coefficient of leakage sound signals as a basis for distinguishing pipeline leakage, a neural memory network is introduced to learn leakage features and establish a leakage feature neural network model, and the features of a signal of a point to be detected are input into the model to determine whether the point leaks, so as to realize accurate positioning of the pipeline leakage position.