Recognition of gas-liquid two-phase flow patterns based on improved local binary pattern operator

Document Type

Article

Publication Date

7-12-2010

Abstract

A new method to pattern recognition of gas-liquid two-phase flow regimes based on improved local binary pattern (LBP) operator is proposed in this paper. Five statistic features are computed using the texture pattern matrix obtained from the improved LBP. The support vector machine and back-propagation neural network are trained to flow pattern recognition of five typical gas-liquid flow regimes. Experimental results demonstrate that the proposed method has achieved better recognition accuracy rates than others. It can provide reliable reference for other indirect measurement used to analyze flow patterns by its physical objectivity. © 2010 Elsevier Ltd.

Identifier

77955513895 (Scopus)

Publication Title

International Journal of Multiphase Flow

External Full Text Location

https://doi.org/10.1016/j.ijmultiphaseflow.2010.06.002

ISSN

03019322

First Page

793

Last Page

797

Issue

10

Volume

36

Grant

20070410757

Fund Ref

National Natural Science Foundation of China

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