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Gas pipeline leakage will lead to great economic losses. So, the study of leak detection on gas pipelines is very important. A leak detection method based on Hilbert-Huang transform (HHT) has been proposed. First, the signal is transformed via HHT, than the Hilbert marginal spectrum will be acquired, which can reflect changing regularity of the signal amplitude. Through compare the marginal spectrum...
In order to identify oil pipeline work conditions accurately and quickly, fuzzy C-means algorithm method is applied to this paper. For obtaining clustering standard, sixteen groups of raw data, which include each work condition, are selected from massive pressure data collected in the field. Analyzed data for convenience, each group of raw data is normalized with mean zero and high-frequency noise...
It is well known that the work condition of pipeline, the leak included, can be identified by a pressure signal analysis. Because of the high frequency data collection and always on-line pipeline leak detection, the pressure signal brings up massive data. A methodology for pipeline leak detection using data mining technology and work condition identification is presented here. Sixteen groups of raw...
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...
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