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作 者:Hu Jinqiu Zhang Laibin Wang Zhaohui Liang Wei
出 处:《Petroleum Science》2007年第2期97-104,共8页石油科学(英文版)
基 金:supported,by National Natural Science Foundation of China(Program number:50105015,50375103);Program for New Century Excellent Talents in University(Program number:NCET-05-0110);Fok Ying Tung Education Foundation(Program number:91051);Beijing Nova Program(Program number:2003B33);CNPC Innovation Fund.
摘 要: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.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.
关 键 词:Negative pressure wave ISODATA leak detection K_L transformation
分 类 号:TE973.6[石油与天然气工程—石油机械设备] U178[交通运输工程]
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