Natural gas leak location with K–L divergence-based adaptive selection of Ensemble Local Mean Decomposition components and high-order ambiguity function

Abstract

In this study, a time-delay estimation method based on Ensemble Local Mean Decomposition (ELMD) method and high-order ambiguity function (HAF) is proposed for locating natural gas pipeline leaks. The leakage signals were decomposed using ELMD, and numerous production functions (PFs) were obtained. An adaptive selection method based on Kullback–Leibler (K–L) divergence was proposed to process these PF components and choose the characteristic PFs that contain most of the leakage information. The HAF was employed to analyze the instantaneous parameters of the characteristic PFs and calculate the difference in arrival time of characteristic frequencies. From the time difference and the signal propagation speed, the natural gas pipeline leakage location can be determined. The experiment results show that the proposed method can locate leaks with higher accuracy than cross-correlation method.