基于多域特征提取的气液两相流流型识别

doi:10.3969/j.issn.1000-1158.2023.10.05

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Abstract A multi-domain feature processing scheme is proposed for the accurate identification of gas-liquid two-phase flow. The electrical resistance tomography (ERT) system is used to obtain the flow data of vertical rising pipeline. From the perspective of measurement data and cross-sectional conductivity distribution image, the time-domain features are extracted after dimensionality reduction of high-dimensional measurement data, and the spatial features of the reconstructed image are extracted by linear back projection (LBP) algorithm. Further, Walsh-Hadamard transform is performed on the image to extract column rate domain features. The uniform manifold approximation and projection (UMAP) algorithm is used to reduce the dimension of the quantized multi-domain features, and finally a support vector machine (SVM) is built to realize flow pattern recognition. The results show that the classification accuracy of bubble flow, bubble-slug transition flow, slug flow and severe slug flow are 98.1%,96.3%,95.2% and 94.8%, respectively.

Key words： metrology flow pattern recognition electrical resistance tomography Walsh-Hadamard transform uniform manifold approximation and projection multi-domain feature;gas-liquid two-phase flow

Received: 06 April 2022 Published: 10 October 2023

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TB937

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	ZHANG Li-feng
	WANG Zhi

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ZHANG Li-feng,WANG Zhi. Gas-Liquid Two-Phase Flow Pattern Recognition Based on Multi-domain Feature Extraction[J]. Acta Metrologica Sinica, 2023, 44(10): 1509-1516.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2023.10.05 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2023/V44/I10/1509

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