Leakage detection for pipe systems with fuzzy monitoring strategy

Raheleh Jafari, Sina Razvarz, Cristobal Vargas-Jarillo, Alexander Gegov, Omar Ali

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

A Pipe is a ubiquitous product in the industries that is used to convey liquids, gases, or solids suspended in a liquid, e.g., a slurry from one location to another. Both internal and external cracking can result in structural failure of the industrial piping system and possibly decrease the service life of the equipment. The chaos and complexity associated with the uncertain behavior inherent in pipeline systems lead to difficulty in detection and localisation of leaks in real-time. The timely detection of leakage is important in order to reduce the loss rate and serious environmental consequences. To address this issue, in this paper an auto regressive with exogenous input (ARX)-Laguerre fuzzy proportional -derivative (PD) observation system is pro-posed to detect and estimate a leak in pipelines. In this work, the ARX-Laguerre model has been used to generate better performance in the presence of uncertainty. According to the results, the proposed technique can detect leaks accurately and effectively.

Original languageEnglish
Title of host publication2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781728190488
ISBN (Print)9781728190495
DOIs
Publication statusEarly online - 24 Jan 2022
Event2021 IEEE Symposium Series on Computational Intelligence - Orlando, United States
Duration: 5 Dec 20217 Dec 2021

Conference

Conference2021 IEEE Symposium Series on Computational Intelligence
Abbreviated titleSSCI 2021
Country/TerritoryUnited States
CityOrlando
Period5/12/217/12/21

Keywords

  • Autoregressive with eXogenous Input Laguerre (ARX-Laguerre)
  • Controller
  • Fuzzy
  • PD
  • PD observer
  • Pipeline

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