Pipeline leak detection using artificial neural network: Experimental study

Mohammad Burhan Abdulla, Randa Omar Herzallah, Mahmoud Ahmad Hammad

Research output: Chapter in Book/Published conference outputConference publication

Abstract

Pipeline transportation of resources is considered a vital method due to low operational cost, and simple design and implementation. However, potential leaks compromise the integrity of this method. Pipeline leaks consequences are major concerns due to resources loss, environmental impact and potential human injuries and fatalities. This paper investigates neural network based probabilistic decision support system for detecting the presence of leak in pipeline transportation systems. The probabilistic model correlates measurements of inlet and outlet pressures and flow to leak status. Several pipeline leak detection methods have been developed, nevertheless, noisy data, and changes in operational conditions are the main challenges that limit the performance of leak detection leading to high false alarms. ANN properties of noise-immunity characteristics, parallel structure and correspondingly fast processing and classification capabilities provide enhanced performance of leak detection.

Original languageEnglish
Title of host publication2013 Proceedings of International Conference on Modelling, Identification and Control, ICMIC 2013
PublisherIEEE
Pages328-332
Number of pages5
ISBN (Print)9780956715739
Publication statusPublished - 24 Oct 2013
Event2013 5th International Conference on Modelling, Identification and Control, ICMIC 2013 - Cairo, Egypt
Duration: 31 Aug 20132 Sep 2013

Publication series

Name2013 Proceedings of International Conference on Modelling, Identification and Control, ICMIC 2013

Conference

Conference2013 5th International Conference on Modelling, Identification and Control, ICMIC 2013
Country/TerritoryEgypt
CityCairo
Period31/08/132/09/13

Keywords

  • artificial neural networks
  • negative pressure wave
  • Pipeline leak detection
  • stochastic noise
  • uncertainty

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