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Petroleum Science
Article . 2007 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Application of an improved ISODATA method to pipeline leak detection

Authors: Hu Jinquiu; Zhang Laibin; Wang Zhaohui; Liang Wei;

Application of an improved ISODATA method to pipeline leak detection

Abstract

Increasingly serious leak problem in pipeline transportation has not only affected the operation of pipelines but also caused loss of precious resource and environmental damage. Based on the analysis of the occurrence of negative pressure waves and the unsupervised learning of pattern recognition, the Interactive Self-organizing Data Analysis Technique Algorithm (ISODATA) method was used to classify the negative pressure waves and then the states of pipelines could be determined. K_L transformation was used to eliminate the correlativity of feature parameters and to reduce the dimensionality of feature vector space to speed up calculation. Experimental results validated the accuracy and practical value of this method.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Top 10%
Average
gold