Adaptive Kalman Estimation of Phase Holdup of Water-Continuous Oil-Water Two-Phase Flow | Zendy

Guangzhi Fu | Zendy; Chao Tan | Zendy; Hao Wu | Zendy; Feng Dong | Zendy

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Adaptive Kalman Estimation of Phase Holdup of Water-Continuous Oil-Water Two-Phase Flow

Author(s) -

Guangzhi Fu,

Chao Tan,

Hao Wu,

Feng Dong

Publication year - 2017

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2017.2670549

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Phase holdup measurement of the two-phase flow is of significance in industrial process. Accurate and real-time measurement of phase holdup is a critical problem requiring urgent solutions. Conductance sensors determine the flowparameters by detecting the change of electrical parameters. Kalman filter is widely applied in state estimation, and oil-water two-phase flow holdup measurement is considered as a state estimation problem in this paper. By using upstream and downstream measuring fluctuation information, an adaptive Kalman estimation model based on discrete cross-correlation with adaptive state transition matrix, and a serial estimation model based on unscented Kalman filter carrying out linear and nonlinear estimations successively are proposed combining with specific flow state. The proposed methods have been validated by online experiments, and the average error of phase holdup estimate is 1.5%.

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