Localization of buried non-metallic pipelines by acoustic reflection method based on joint denoising of echo signals

Abstract To address the low signal-to-noise ratio (SNR) of echo signals caused by noise interference, which significantly degrades pipeline localization accuracy, this paper proposes a joint denoising method based on ensemble empirical mode decomposition (EEMD) and optimized wavelet thresholding. The method first employs wavelet thresholding to preprocess the noisy signal, effectively filtering out high-frequency noise. Subsequently, EEMD decomposition is performed, and intrinsic mode function components containing residual noise are selected through correlation analysis. A secondary wavelet denoising step is then applied to precisely suppress low-frequency non-stationary noise. Finally, the denoised signal is reconstructed. Simulation results demonstrate that the proposed joint denoising method improves the output SNR by 5.5%–15.2% compared with the standalone wavelet thresholding method and by 1.9%–14.1% compared with the EEMD-only method, indicating its superior denoising performance. To validate the practicality of the optimized reflection delay method and the joint denoising approach, field tests were conducted for pipeline localization. The results show that the joint denoising method reduces pipeline localization errors by 4.690% compared with the wavelet thresholding method and by 3.004% compared with the EEMD method. The echo signals processed by the joint denoising method exhibit a significantly enhanced SNR, providing a reliable basis for the precise localization of underground pipelines.