NDLI: Pipeline Leakage Recognition Based on the Projection Singular Value Features and Support Vector Machine

Content Provider	The American Society of Mechanical Engineers (ASME) Digital Collection
Author	Wang, Mingda Zhang, Laibin Liang, Wei Hu, Jinqiu
Copyright Year	2010
Abstract	Identification of negative pressure waveform is the key of pipeline leakage detection. The feature extraction and the choice of the classifier are two main contents to solve the recognition problem. In this paper, a new feature extraction method based on the Projection Singular Value is presented. First of all, the two orthogonal singular value decomposition matrixes of the typical leakage waveform are extracted as the standard bases. Then the projection singular value features of the other pressure wave matrixes are extracted by being projected to the two standard bases. As the pipeline leakage is a small probability event, it is difficult to obtain the leakage samples. A multi-classification Support Vector Machine, which has the advantage of small sample learning, is constructed to classify these features in this paper. The field experiments indicate that the leakage detection based on this feature extraction and recognition model has a higher accuracy of leakage recognition.
Sponsorship	International Petroleum Technology Institute and the Pipeline Division
Starting Page	471
Ending Page	476
Page Count	6
File Format	PDF
ISBN	9780791844229
DOI	10.1115/IPC2010-31087
e-ISBN	9780791838853
Volume Number	2010 8th International Pipeline Conference, Volume 3
Conference Proceedings	2010 8th International Pipeline Conference
Language	English
Publisher Date	2010-09-27
Publisher Place	Calgary, Alberta, Canada
Access Restriction	Subscribed
Subject Keyword	Negative pressure wave Projection singular value features Pipeline leakage Matrix structure Support vector machine Leakage Support vector machines Pipelines Pressure Waves
Content Type	Text
Resource Type	Article

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