DocumentCode :
3169181
Title :
Energy features extraction of oil theft signal in buried pipeline based on lifting wavelet package
Author :
Ying-chun, Li ; Qin Xue ; Xing-jian, Fu
Author_Institution :
Electron. Eng. Dept., North China Inst. of Astronaut. Eng., Langfang, China
fYear :
2010
fDate :
29-30 Oct. 2010
Firstpage :
534
Lastpage :
537
Abstract :
The system to collect stress wave signal of oil theft was briefly introduced, and data acquisition steps on-the-spot were given. According to the different energy distribution features that stress wave signal exhibits on wavelet domain, a new analyzed method based on the lifting scheme wavelet packet was presented. In the method, the stress signal was decomposed with lifting wavelet packet transform and the energy proportion in each sub-band is calculated. Analyses of experimental results show that identification of oil theft signal can be done through the differences of energy distribution features. The method, which can be computed fast with a simple implementation, provides a new approach for identification of oil theft signal.
Keywords :
lifting; mining; petroleum industry; pipelines; wavelet transforms; buried pipeline; data acquisition; energy distribution features extraction; energy proportion; lifting wavelet packet transform; oil theft signal; stress wave signal; Electric shock; Shock waves; Silicon; data acquisition; energy distribution; identification; lifting wavelet package; oil theft;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Education (ICAIE), 2010 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-6935-2
Type :
conf
DOI :
10.1109/ICAIE.2010.5641105
Filename :
5641105
Link To Document :
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