Title :
Leak detection in pipelines based on PCA
Author :
Hu, Rong ; Ye, Hao ; Wang, Guizeng ; Lu, Chen
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
Leak detection of oil pipelines is an important issue for safe operation of pipelines, reducing oil loss and environmental pollution. A new approach based on principal component analysis (PCA) method to detect leaks of oil pipelines is proposed in this paper. In order to detect leaks, a classifier is designed to recognize negative pressure wave curve by training set. Results indicate that the method can detect many leak faults from a pressure curve, which might not be effectively detected by a traditional signal processing based method but can be recognized easily by human visual perception.
Keywords :
leak detection; mechanical engineering computing; pipelines; principal component analysis; PCA; environmental pollution; leak detection; leak faults; negative pressure wave curve; oil loss reduction; oil pipelines; principal component analysis; Covariance matrix; Fault detection; Humans; Leak detection; Oil pollution; Petroleum; Pipelines; Principal component analysis; Signal processing; Wavelet transforms;
Conference_Titel :
Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th
Print_ISBN :
0-7803-8653-1
DOI :
10.1109/ICARCV.2004.1469466