Urban hazardous chemicals pipeline leakage positioning method based on CELMD-MCKD

Yongmei Hao, Zhanghao Du, Zhixiang Xing, Juncheng Jiang, Ke Yang, Lei Ni, Xinming Yan

Research output: Contribution to journalReview articlepeer-review

9 Scopus citations

Abstract

Aiming at the difficulty of leak detection of urban hazardous chemical pipelines, this paper proposes a method for locating pipeline leaks based on the complementary ensemble local mean decomposition (CELMD) and maximum correlation kurtosis deconvolution (MCKD) secondary noise reduction. First, white noise with opposite sign was added to the original leak signal in pairs, and the noisy signal was decomposed to obtain a series of product functions (PF). Second, select the PF component containing the main leakage information according to the correlation coefficient, and perform the initial noise reduction. Then, the maximum correlation kurtosis deconvolution (MCKD) was used to perform secondary noise reduction on the filtered PF component; Finally, the PF component obtained after two screening was reconstructed, and the pipeline leakage location was completed by calculating the delay parameters of AE signal by cross-correlation. The experimental results show that compared with the cross-correlation method and the ELMD method, the method has higher recognition accuracy and positioning accuracy.

Original languageEnglish
Pages (from-to)477-493
Number of pages17
JournalNondestructive Testing and Evaluation
Volume36
Issue number5
DOIs
StatePublished - 2021

Keywords

  • Urban pipeline
  • complete ensemble local mean decomposition
  • correlation coefficient
  • leakage location
  • maximum correlated kurtosis deconvolution

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