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Publishing Language: Chinese | Open Access

Application of local optimal threshold segmentation algorithm in ECT phase fraction calculation

Haichao YANG, Jingxuan HUANG, Hongli HU( ), Chengcheng LU, Maojie WANG
State Key Laboratory of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, China
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Abstract

The image reconstructed by ECT image reconstruction algorithm has the problems of unclear edge and low imaging accuracy. It is easy to misjudge the interface of different mediums, and the accuracy of cross-section water content calculation depends on the accuracy of binary segmentation of the reconstructed image. Therefore, by analyzing the shortcomings of the global threshold segmentation algorithm, we propose a local threshold segmentation algorithm combined with simulated annealing algorithm. In order to verify the effectiveness, the reconstructed images of laminar flow, central flow, annular flow are segmented by local optimal threshold, and the cross-section water content is calculated. By comparing with the global threshold segmentation algorithm, it is proved that the local threshold segmentation algorithm has a relatively higher accuracy in calculating the section water content. In addition, considering the nonlinear error of ECT system, an image threshold segmentation algorithm considering the nonlinear error of ECT is adopted by combining with the local threshold segmentation algorithm. Comparing the global threshold segmentation algorithm and local threshold segmentation algorithm without considering nonlinear error, shows that the local threshold segmentation algorithm considering ECT nonlinear error has a relatively higher accuracy in the calculation of cross-section water content.

CLC number: TP911.73

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Journal of Northwest University (Natural Science Edition)
Pages 572-578

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Cite this article:
YANG H, HUANG J, HU H, et al. Application of local optimal threshold segmentation algorithm in ECT phase fraction calculation. Journal of Northwest University (Natural Science Edition), 2023, 53(4): 572-578. https://doi.org/10.16152/j.cnki.xdxbzr.2023-04-008

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Received: 31 August 2022
Published: 25 August 2023
© The Editorial Department of Journal of Northwest University(Natural Science Edition)2023.

This is an open access article under the CC BY-NC-ND 4.0 license (https://creativecommons.org/licenses/by-nc-nd/4.0/).