DocumentCode :
569751
Title :
Study of Gas Pipeline Leak Detection Based on Hilbert Marginal Spectrum
Author :
Hedeng, Yang ; Laibing, Zhang ; Wei, Liang ; Yingchun, Ye ; Yijing, Ren
Author_Institution :
Coll. of Mech. & Transp. Eng., China Univ. of Pet., Beijing, Beijing, China
fYear :
2012
fDate :
17-19 Aug. 2012
Firstpage :
1259
Lastpage :
1262
Abstract :
Gas pipeline leakage will lead to great economic losses. So, the study of leak detection on gas pipelines is very important. A leak detection method based on Hilbert-Huang transform (HHT) has been proposed. First, the signal is transformed via HHT, than the Hilbert marginal spectrum will be acquired, which can reflect changing regularity of the signal amplitude. Through compare the marginal spectrum curve between normal condition and leak condition, then the character frequency band of the signal will be acquired. The energy in the character frequency band is treated as the feature vector. Markov distance between the test data and sample data is established, and it is used to judge the working conditions of the gas pipeline. The validity of this leak detection approach has been assessed via experiment. According to the difference of the leak arrival time for both the upstream and downstream and sound speed in the gas of the pipeline, we can get the localization of the leak point.
Keywords :
Hilbert transforms; Markov processes; acoustic waves; environmental factors; leak detection; pipelines; HHT; Hilbert marginal spectrum; Hilbert-Huang transform; Markov distance; feature vector; gas pipeline leak detection; marginal spectrum curve; signal amplitude; Educational institutions; Feature extraction; Leak detection; Markov processes; Pipelines; Transforms; Vectors; HHT; feature vector; leak detection; leak location; pipeline;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-2406-9
Type :
conf
DOI :
10.1109/ICCIS.2012.296
Filename :
6301348
Link To Document :
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