A Study on Locating Two Leaks in Water Supply Pipelines Based on CEEMD-SVD-FCMSS

In the field of leakage localization in water supply pipelines using acoustic-based methods, limited research has focused on addressing multiple leaks. The interaction among multiple leakage sources complicates the localization process. Targeting two leakage sources, this study presents a novel hybrid approach named complementary ensemble empirical modal decomposition, singular value decomposition, and frequency-domain convolutive mixed source separation (CEEMD-SVD-FCMSS) for accurately localizing leakage points in water supply pipes. In this method, complementary ensemble empirical modal decomposition (CEEMD) and singular value decomposition (SVD) are jointly proposed to adaptively extract the effective leakage signals, and frequency-domain convolutional mixed source separation (FCMSS) is innovatively proposed for estimating the time delay of each leakage source. In signal simulation, the effectiveness of the method is verified and the results show that after CEEMD-SVD noise reduction, the signal-to-noise ratios (SNRs) of two signals are improved significantly by 6.75 and 6.68 dB, respectively, and the time delays of the leak sources are found by the FCMSS. The comparative analysis highlights CEEMD-SVD’s superior noise reduction capabilities over conventional methods, while FCMSS effectively avoids the issue of large leaks masking smaller ones observed with the correlation method. A comprehensive full-size experiment further corroborates the method’s effectiveness and superiority in leakage localization in practical scenarios.