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首页> 外文期刊>IEEE transactions on industrial informatics >A Novel Multiplex Network-Based Sensor Information Fusion Model and Its Application to Industrial Multiphase Flow System
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A Novel Multiplex Network-Based Sensor Information Fusion Model and Its Application to Industrial Multiphase Flow System

机译：基于多重网络的新型传感器信息融合模型及其在工业多相流系统中的应用

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摘要

Increasingly advanced technology allows the monitoring of complex systems from a wide variety of perspectives. But the exploration of such systems from a multichannel sensor information viewpoint remains a complicated challenge of ongoing interest. In this paper, first, based on a well-designed double-layer distributed-sector conductance (DLDSC) sensor, systematic oil–water and gas–liquid two-phase flow experiments are carried out to capture abundant spatiotemporal flow information. Second, well flow parameter measurement performance of the DLDSC sensor is effectively validated from the perspective of normalized conductance. Third, 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.
机译：越来越先进的技术可以从多种角度监视复杂的系统。但是，从多通道传感器信息的角度出发，对此类系统的探索仍然是持续关注的复杂挑战。在本文中，首先，基于设计良好的双层分布扇区电导（DLDSC）传感器，进行了系统的油-水和气-液两相流实验，以捕获大量的时空流信息。其次，从归一化电导率的角度有效地验证了DLDSC传感器的井流参数测量性能。第三，提出了一种新颖的基于多路复用网络的模型，以实现数据挖掘和表征流动力学的演变。结果表明，该模型对于研究两相流从非均质性到随机性的空间流行为具有强大的作用。

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