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《Chinese Journal of Scientific Instrument》 2014-12
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Pipeline leak aperture classification and location based on local mean decomposition analysis

Sun Jiedi;Xiao Qiyang;Wen Jiangtao;Yang Yiguang;School of Information Science and Engineering,Yanshan University;Key Laboratory of Measurement Technology and Instrumentation of He Bei Province,Yanshan University;China Petroleum and Gas Pipeline Telecommunication and Electricity Engineering Corporation;  
Aiming at natural gas pipeline leak problem,a leak apertures recognition and location method based on RMS(root mean square) entropy and time delay estimation is presented by analyzing local mean decomposition(LMD) results.The leak signals are decomposed by LMD and several PF(product function) components with clearly physical meaning are obtained.The PF components RMS is calculated,which combines information entropy to acquire RMS entropy of different leak apertures.Several RMS entropy values are chosen as the feature vectors and input to the SVM to achieve the identification.In order to improve the location accuracy of cross-correlation,the kurtosis of PF components is analyzed,and leak signals are constructed based on principal PFs to improve time delay estimation accuracy.Combining the stress wave velocity,the leak location is caccomplished.Experimental results show the proposed methods with LMD analysis can effectively identify apertures and locate the leak,and the recognition result is better than the RMS entropy based on EMD.Location accuracy is obviously improved than the direct cross-correlation method.
【Fund】: 国家自然科学基金(51204145);; 河北省自然科学基金(E2013203300)资助项目
【CateGory Index】: TE973
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