Adaptive leak signal extraction based on EMD-CC for water pipeline leak location

Abstract

When using acoustic methods for water pipeline leak localization, noise will significantly affect the accuracy of localization, especially for the case that the noise intensity far exceeds the signal intensity, the traditional noise reduction methods will be ineffective. Therefore, an empirical mode decomposition and cross-correlation (EMD-CC) method for leak localization is proposed, which can adaptively extract effective leak signals from low signal-to-noise ratio (SNR) detection signals, and then can significantly improve the accuracy of localization. In this paper, the principle and steps of the algorithm are elaborated, and the effectiveness is verified in simulations and experiments. In the simulations, the SNR of the reconstructed signal −15 dB is dramatically increased to −6 dB. Compared with conventional noise reduction methods, the time-delay value estimation of EMD-CC is more accurate, more reliable, and more noise resistant. In full-size experiments, the accuracy of localization after processing is significantly improved.