Skip to main navigation Skip to search Skip to main content

Acoustic emission source identification technique for buried gas pipeline leak

  • Yang Jiao*
  • , Qingxin Yang
  • , Guanghai Li
  • , Jingyan Zhang
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Leaks in gas pipelines cause unnecessary waste of limited resources and produce danger factors, thus leak testing is necessary. Acoustic emission (AE) technology is one of the promising methods for pipeline leak testing. AE signals of pipeline leak carry the feature information of structure integrity (the dimension and location of leak source, etc.), which are stochastic and uncertain, and belongs to non-stationary signals. Because of the noise and the complexity of AE signal transmission, the identification of AE source is very difficult. On the basis of analyzing the characteristics of AE signal and background noise, we established a gas leak identification model for city gas pipeline in this paper. A leak identification method is presented based on spatial-temporal data fusion. The multi-data segments are fused in time and space will decrease incertitude in the process of identification. Experimental result shows that the inspection range can be up to 87m, and the identification rate can be up to 95% for Φ 1mm pinhole leak.

Original languageEnglish
Title of host publication9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06
DOIs
StatePublished - 2006
Externally publishedYes
Event9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06 - Singapore, Singapore
Duration: 5 Dec 20068 Dec 2006

Publication series

Name9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06

Conference

Conference9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06
Country/TerritorySingapore
CitySingapore
Period5/12/068/12/06

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Acoustic emission testing
  • Data fusion
  • Identification technique
  • Pipeline leak

Fingerprint

Dive into the research topics of 'Acoustic emission source identification technique for buried gas pipeline leak'. Together they form a unique fingerprint.

Cite this