The invention provides a pipeline leakage signal identification method based on improved ELMD multi-scale entropy. The pipeline leakage signal identification method includes the steps that firstly, acquired experimental data are subjected to noise pre-processing to eliminate low-correlation components in signals; then pre-processed signals are subjected to ELMD processing to obtain PF components;an endpoint effect problem reserved by ELMD decomposition is weakened through a peak value waveform matching method; the multi-scale entropy of the PF components is calculated correspondingly, and multi-scale entropy values of leakage signals are arrayed and compared to eliminate background noise; a feature vector is constructed by selecting a principal PF component according to the multi-scale entropy values; the feature vector is used as an input vector of a BP neural network to train the network; and a to-be-tested sample is input into a trained BP neural network to obtain a pipeline leakage identification result. The pipeline leakage signal identification method based on the improved ELMD multi-scale entropy can adapt to various conditions of pipelines and has good testing accuracy.