DocumentCode :
2560377
Title :
Leak detection of oil transport pipelines based on prediction and modeling
Author :
Yang, Hongying ; Ye, Hao ; Ge, Chauanhu ; Wang, Guizeng ; Tan, Dongje ; Lu, Guoliang
Author_Institution :
Dept. of Autom., Univ. of Tsinghua, Beijing
fYear :
2008
fDate :
2-4 July 2008
Firstpage :
2049
Lastpage :
2053
Abstract :
For solving the problem of discriminating leaks and valve adjusting operations in leak detection of oil pipeline based on dynamic pressure transducer (DPT). In this paper, the fuzzy neural system (FNS) based chaos time series prediction method is used to detect and locate the leakage based on DPT pressure signals. Offline tests based on the real historical data demonstrate that the proposed method can not only discriminate the leak from valve adjusting operations effectively, but also achieve satisfying detection and location precision.
Keywords :
fuzzy neural nets; leak detection; pipelines; pressure sensors; production engineering computing; time series; chaos time series prediction method; dynamic pressure transducer; fuzzy neural system; leak detection; oil transport pipelines; Chaos; Fuzzy systems; Leak detection; Petroleum; Pipelines; Prediction methods; Predictive models; Testing; Transducers; Valves; Chaos; Fuzzy; Leak detection; Oil transport pipeline; Pressure transducer;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
Type :
conf
DOI :
10.1109/CCDC.2008.4597686
Filename :
4597686
Link To Document :
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