期刊
MEASUREMENT & CONTROL
卷 56, 期 1-2, 页码 396-402出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/00202940221088713
关键词
Cyber-physical system; deep belief network; empirical mode decomposition; leak detection; support vector machine
A method for pipeline leak detection based on EMD and DBN is proposed, achieving higher recognition accuracy compared to TWSVM, SVM, and BPNN.
Leak detection of an oil pipeline can prevent environmental and financial losses. A method for the cyber-physical system of pipeline leak detection is proposed based on the empirical mode decomposition (EMD) and deep belief network (DBN). Experiment data are acquired from an oil pipeline company. The EMD is suitable for noise removal and signal reconstruction from raw pressure signals, and the reconstructed signals are used to establish a DBN model of pipeline leakage. Our proposed method obtains higher-recognition-accuracy results (98% accuracy) and can more effectively identify leak detection than the twin support vector machine (TWSVM), support vector machine (SVM), and back-propagation neural network (BPNN).
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