An improved Empirical Mode Decomposition（EMD）adaptive denoising algorithm based on Detrended Fluctuation Analysis (DFA) and wavelet transform (WT) is proposed. The noisy signal is adaptively decomposed into several Intrinsic Mode function (IMF) components by EMD, the scale index of each IMF is calculated by DFA, and the low-frequency useful components with long-range correlation are adaptively selected, the high frequency components are processed by WT. Finally, the selected low-frequency useful components and the high-frequency components after wavelet processing are used to reconstruct the denoised signal. Theoretical analysis and experiments show that the output signal-to-noise ratio of EMD-DFA and wavelet denoising methods after denoising are 12.3458dB and 13.7369dB, respectively.Compared with the single denoising algorithm, the output signal-to-noise ratio of the improved algorithm EMD-DFA-WT is 14.4513dB, and the signal-to-noise ratio is significantly improved, which effectively eliminates the noise in the leakage signal of the natural gas pipeline, highlights the signal characteristics, and achieves the purpose of noise reduction.