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Numerical Modeling for chaotic characteristics of oil pipeline pressure time series

Jianjun Xu, Shengnan Liu, Bin Xu, Xu Xu

Abstract



Nonlinear analysis is used to study the possibility of chaotic behavior of pipeline pressure signal in this paper. Six typical measured data of pipeline pressure are selected and reconstructed to the higher dimension phase space. And then the largest Lyapunov exponent of each data is calculated to test and verify the chaotic characteristics of the pressure signals. The approximate entropy (ApEn) has been applied to extract the nonlinear and chaotic characteristics of pipeline pressure signals. By calculating the ApEn of normal, regulation and leakage signals, the results indicate that the value ranges of three kinds of signals are above 0.35, below 0.025, and from 0.025 to 0.35. And the identification rate of pipeline leakage has reached 90.0% only based on ApEn. Thus, the more effective foundations of classification and identification of the pressure signals are provided.

Keywords


chaotic time series, oil pipeline, leakage detection, approximate entropy.

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