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 language | English |
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Title of host publication | 2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Number of pages | 6 |
ISBN (Electronic) | 9781728190488 |
ISBN (Print) | 9781728190495 |
DOIs | |
Publication status | Early online - 24 Jan 2022 |
Event | 2021 IEEE Symposium Series on Computational Intelligence - Orlando, United States Duration: 5 Dec 2021 → 7 Dec 2021 |
Conference
Conference | 2021 IEEE Symposium Series on Computational Intelligence |
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Abbreviated title | SSCI 2021 |
Country/Territory | United States |
City | Orlando |
Period | 5/12/21 → 7/12/21 |
Keywords
- Autoregressive with eXogenous Input Laguerre (ARX-Laguerre)
- Controller
- Fuzzy
- PD
- PD observer
- Pipeline