A Novel Multiplex Network-based Sensor Information Fusion Model and Its Application to Industrial Multiphase Flow System

Zhongke Gao (Corresponding Author), Weidong Dang, Chaoxu Mu, Yuxuan Yang, Shan Li, Celso Grebogi

Research output: Contribution to journalArticle

38 Citations (Scopus)
7 Downloads (Pure)

Abstract

Increasingly advanced technology allows the monitoring of complex systems from a wide variety of perspectives. But the exploration of such systems from a multi-channel sensor information viewpoint remains a complicated challenge of ongoing interest. In this paper, firstly, based on well-designed double-layer distributed-sector conductance sensor, systematic oil-water and gas-liquid two-phase flow experiments are carried out to capture abundant spatio-temporal flow information. Secondly, well flow parameter measurement performance of DLDSC Sensor is effectively validated from the perspective of normalized conductance. Thirdly, a novel multiplex network-based model is presented to implement data mining and characterize the evolution of flow dynamics. The results demonstrate that the model is powerful for the exploration of the spatial flow behaviors from heterogeneity to randomness in the studied two-phase flows.
Original languageEnglish
Article numberTII-17-2463
Pages (from-to)3982-3988
Number of pages7
JournalIEEE Transactions on Industrial Informatics
Volume14
Issue number9
Early online date20 Dec 2017
DOIs
Publication statusPublished - 4 Aug 2018

Keywords

  • signal analysis
  • industrial multiphase flow
  • multiplex network
  • information fusion

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