Signal Processing of Infrasound Leakage in Urban Pipelines Based on Spectral Analysis

A method of urban pipeline leakage infrasound signal processing based on spectrum analysis is proposed in order to address the issues of low recognition rate of infrasound signal of urban nonmetallic pipeline leakage and the existence of false signal interference, which results in low accuracy of pipeline leakage location. Firstly, the frequency spectrum of leakage and nonleakage signals is analyzed on the basis of a large number of tests, and the frequency spectrum characteristics and leakage judgment criteria of urban nonmetallic pipeline infrasound leakage signals are summarized. Secondly, the improved complementary ensemble empirical mode decomposition (ICEEMD) method is used to decompose the infrasonic leakage signal into the effective signal component and noise signal component to remove the false signal. Finally, the fine composite multiscale entropy algorithm is used to screen and reconstruct the entropy value of each signal component to extract effective and pure infrasonic leakage signal data. The experimental application demonstrated that the proposed method’s signal-to-noise ratio (SNR) increased from 13 to 25 dB and its average root-mean square error (RMSE) decreased from 24.82% to 3.39%. This significantly increases the accuracy of the identification of infrasound signals of urban nonmetallic pipeline leakage and provides a basis for pipeline leakage location.