Complex Network from Nonlinear Time Series with Application to Inclined Oil-Water Flow Pattern Identification
We study the inclined oil-water two-phase flow using complex networks and construct flow pattern complex network with the conductance fluctuating signals measured from oil-water two-phase flow experiments. A new method, based on Time-Delay Embedding and modularity, is proposed to construct network from nonlinear time series. Through detecting the community structure of the resulting network using the community-detection algorithm based on K-means clustering, useful and interesting results are found which can be used to identify three inclined oilwater flow patterns. In this paper, from a new perspective, we not only introduce complex network theory to the study of oil-water two-phase flow, but also demonstrate that complex network may be a powerful tool for exploring nonlinear time series in practice.
Inclined Oil-Water Two-Phase Flow Complex Network Flow Pattern Identification Community Structure
Z.K.Gao N.D.Jin Y.B.Zong Z.Y.Wang
School of Electrical Engineering & Automation, Tianjin University, Tianjin, China
国际会议
西安
英文
543-548
2009-07-11（万方平台首次上网日期，不代表论文的发表时间）