Study on Topology-Based Identification of Sources of Vulnerability for Natural Gas Pipeline Networks

Wang, Peng; Yu, Bo; Sun, Dongliang; Ao, Shangmin; Zhai, Huaxing

doi:10.1007/978-3-319-93713-7_13

Cited by 1 publication

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References 2 publications

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“…The transportation of natural gas through pipelines is a mode of transportation involving various substances, spanning multiple regions, and affecting numerous factors [1]; as a result, * The data cannot be made publicly available upon publication because they contain commercially sensitive information. The data that support the findings of this study are available upon reasonable request from the authors.…”

Section: Introductionmentioning

confidence: 99%

Pipeline leak location method based on SSA-VMD with generalized quadratic cross-correlation^*

Peng,

Hu,

Zhang

et al. 2024

Meas. Sci. Technol.

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Natural gas pipelines are an essential part of the economy. Natural gas pipelines may leak after aging, strong vibration signals may be generated in the pipeline when leakage occurs, and vibration signals may be noisy. Traditional variational mode decomposition (VMD) noise reduction methods need to set parameters in advance, and so may not achieve the best decomposition effect. To solve this problem, this paper proposes a method for pipeline leakage location based on the sparrow search algorithm (SSA) optimization of VMD combined with generalized quadratic cross-correlation. The method first calculates the original signal-to-noise ratio, and if the signal-to-noise ratio is low, wavelet threshold denoising is used to process the signal. Then, SSA optimization is used to refine the two key parameters of VMD (penalty parameter α and mode decomposition number K) based on sample entropy. Subsequently, the signal undergoes decomposition into K intrinsic mode function (IMF) components through VMD according to the obtained analysis parameter combination. Then, the IMF components are screened to obtain the reconstructed signal. Finally, the noise reduction signal is obtained. The signal delay after noise reduction is obtained through a generalized quadratic cross-correlation and the accurate leakage position is obtained using the delay. Experiments showed that the minimum relative error of this method could reach 0.6%, which was more accurate than the traditional VMD method, and effectively improved the accuracy of noisy signals in pipeline leakage locations.

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Section: Introductionmentioning

confidence: 99%

Pipeline leak location method based on SSA-VMD with generalized quadratic cross-correlation^*

Peng,

Hu,

Zhang

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

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Study on Topology-Based Identification of Sources of Vulnerability for Natural Gas Pipeline Networks

Cited by 1 publication

References 2 publications

Pipeline leak location method based on SSA-VMD with generalized quadratic cross-correlation^*

Pipeline leak location method based on SSA-VMD with generalized quadratic cross-correlation^*

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Study on Topology-Based Identification of Sources of Vulnerability for Natural Gas Pipeline Networks

Cited by 1 publication

References 2 publications

Pipeline leak location method based on SSA-VMD with generalized quadratic cross-correlation*

Pipeline leak location method based on SSA-VMD with generalized quadratic cross-correlation*

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Product

Resources

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Pipeline leak location method based on SSA-VMD with generalized quadratic cross-correlation^*

Pipeline leak location method based on SSA-VMD with generalized quadratic cross-correlation^*