Aiming at the problem that it is difficult to fully extract the characteristics of small leakage signals of natural gas pipelines on a single scale, a method for identifying small leakage signals of pipelines based on the combination of variational modal decomposition (VMD) and multi-scale fuzzy entropy (MFE) is proposed. First, the VMD algorithm is used to denoise the pipeline negative pressure wave signal, and the effective mode of the VMD decomposition is determined and reconstructed by the Euclidean distance (ED) method to determine the VMD decomposition based on the principle of the highest signal-to-noise ratio of the reconstructed signal The number of modes; the multi-scale fuzzy entropy is used as the fault eigenvalue vector, and finally the support vector machine is used to classify and recognize the eigenvalue vector. The experimental results show that the overall recognition rate of the pipeline signal state by this method is 99.33%, which proves that the overall recognition effect of the method is good, and it can realize the accurate identification of small pipeline leakage signals.