Journal
MEASUREMENT
Volume 131, Issue -, Pages 92-99Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2018.08.028
Keywords
Oil-water two-phase flow measurement; Microwave; Deep neural network
Funding
- National Natural Science Foundation of China [61571252]
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This paper presents a microwave dual frequency correction algorithm to measure the water content of the oil-water two-phase flows, which can eliminate the influence of conductivity and obtain the water content. Subsequently, based on the advantages of dual-frequency this paper proposes a deep neural network model to predict complex nonlinear relationship between the mixture permittivity and water content. In order to avoid falling into a local optimal solution, the adaptive moment estimation algorithm is used to replace the gradient descent method. The experimental results are applied to estimate the performance of the discussed deep neural network algorithm. (C) 2018 Elsevier Ltd. All rights reserved.
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