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

Zhongke Gao; Weidong  Dang; Chaoxu Mu; Yuxuan  Yang; Shan Li; Celso Grebogi

doi:10.1109/TII.2017.2785384

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

Tianjin University

Research output: Contribution to journal › Article › peer-review

71 Citations (Scopus)

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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 language	English
Article number	TII-17-2463
Pages (from-to)	3982-3988
Number of pages	7
Journal	IEEE Transactions on Industrial Informatics
Volume	14
Issue number	9
Early online date	20 Dec 2017
DOIs	https://doi.org/10.1109/TII.2017.2785384
Publication status	Published - 4 Aug 2018

Bibliographical note

This work was supported by National Natural Science Foundation of China under Grant No. 61473203, and the Natural Science Foundation of Tianjin, China under Grant No. 16JCYBJC18200.

Keywords

signal analysis
industrial multiphase flow
multiplex network
information fusion

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Cite this

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

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.",

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author = "Zhongke Gao and Weidong Dang and Chaoxu Mu and Yuxuan Yang and Shan Li and Celso Grebogi",

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AU - Gao, Zhongke

AU - Dang, Weidong

AU - Mu, Chaoxu

AU - Yang, Yuxuan

AU - Li, Shan

AU - Grebogi, Celso

N1 - This work was supported by National Natural Science Foundation of China under Grant No. 61473203, and the Natural Science Foundation of Tianjin, China under Grant No. 16JCYBJC18200.

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N2 - 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.

AB - 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.

KW - signal analysis

KW - industrial multiphase flow

KW - multiplex network

KW - information fusion

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JF - IEEE Transactions on Industrial Informatics

IS - 9

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

Abstract

Bibliographical note

Keywords

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