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Type: Artigo de periódico
Title: Leak detection in petroleum pipelines using a fuzzy system
Author: da Silva, HV
Morooka, CK
Guilherme, IR
da Fonseca, TC
Mendes, JRP
Abstract: A methodology for pipeline leakage detection using a combination of clustering and classification tools for fault detection is presented here. A fuzzy system is used to classify the running mode and identify the operational and process transients. The relationship between these transients and the mass balance deviation are discussed. This strategy allows for better identification of the leakage because the thresholds are adjusted by the fuzzy system as a function of the running mode and the classified transient level. The fuzzy system is initially off-line trained with a modified data set including simulated leakages. The methodology is applied to a small-scale LPG pipeline monitoring case where portability, robustness and reliability are amongst the most important criteria for the detection system. The results are very encouraging with relatively low levels of false alarms, obtaining increased leakage detection with low computational costs. (c) 2005 Elsevier B.V. All rights reserved.
Subject: pipeline leakage detection
pattern recognition
fuzzy systems
Country: Holanda
Editor: Elsevier Science Bv
Rights: fechado
Identifier DOI: 10.1016/j.petrol.2005.05.004
Date Issue: 2005
Appears in Collections:Unicamp - Artigos e Outros Documentos

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