Jafari, R orcid.org/0000-0001-7298-2363, Razvarz, S, Vargas-Jarillo, C et al. (2 more authors) (2022) Pipeline Leak Detection and Estimation Using Fuzzy PID Observer. Electronics, 11 (1). 152. ISSN 1450-5843
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 behaviour 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. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. 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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | autoregressive with exogenous input Laguerre (ARX–Laguerre); fuzzy; pipeline; PID; controller; PID observer |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Arts, Humanities and Cultures (Leeds) > School of Design (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Mar 2022 11:06 |
Last Modified: | 25 Jun 2023 22:55 |
Status: | Published |
Publisher: | University of Banja Luka |
Identification Number: | 10.3390/electronics11010152 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:184246 |