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Fuzzy Logic based Multi-Dimensional Image Fusion for Gas-Oil-Water Flows with Dual-Modality Electrical Tomography
IEEE Transactions on Instrumentation and Measurement ( IF 5.6 ) Pub Date : 2020-05-01 , DOI: 10.1109/tim.2019.2923864 Qiang Wang , Xiaodong Jia , Mi Wang
IEEE Transactions on Instrumentation and Measurement ( IF 5.6 ) Pub Date : 2020-05-01 , DOI: 10.1109/tim.2019.2923864 Qiang Wang , Xiaodong Jia , Mi Wang
This paper proposes a novel approach, whereby fuzzy logic and decision tree are utilized to overcome the challenges in analyzing images of gas–oil–water pipeline flow obtained using electrical resistance and capacitance dual-modality tomography. The first approach generates two axially stacked concentration images from two stacks of the cross-sectional concentration tomograms reconstructed from different modalities, respectively, and then registers two generated images in temporal and spatial terms. Afterward, a fuzzy logic method is applied to perform a pixel-level fusion to integrate the registered images based on the characteristics of electrical tomograms for multiphase pipeline flow. Later, a decision tree is utilized to derive the local concentration of each individual phase according to the fusion results. Using the data from real industrial cases, both feasibility and robustness of the proposed approach are demonstrated. In addition, the proposed approach also overcomes the limitations of conventional threshold-based methods on the request of a priori knowledge for the qualitative and quantitative analyses of gas–oil–water pipeline flow.
中文翻译:
基于模糊逻辑的双模态电断层扫描油气水流多维图像融合
本文提出了一种新方法,利用模糊逻辑和决策树来克服分析使用电阻和电容双模态断层扫描获得的气-油-水管道流动图像的挑战。第一种方法分别从不同模态重建的两个横截面浓度断层图的堆叠生成两个轴向堆叠的浓度图像,然后在时间和空间方面配准两个生成的图像。然后,基于多相管道流电断层图的特征,应用模糊逻辑方法进行像素级融合,以整合配准图像。之后,利用决策树根据融合结果推导出每个单独相的局部浓度。使用来自真实工业案例的数据,证明了所提出方法的可行性和稳健性。此外,所提出的方法还克服了传统基于阈值方法的局限性,因为需要先验知识才能对气-油-水管道流量进行定性和定量分析。
更新日期:2020-05-01
中文翻译:
基于模糊逻辑的双模态电断层扫描油气水流多维图像融合
本文提出了一种新方法,利用模糊逻辑和决策树来克服分析使用电阻和电容双模态断层扫描获得的气-油-水管道流动图像的挑战。第一种方法分别从不同模态重建的两个横截面浓度断层图的堆叠生成两个轴向堆叠的浓度图像,然后在时间和空间方面配准两个生成的图像。然后,基于多相管道流电断层图的特征,应用模糊逻辑方法进行像素级融合,以整合配准图像。之后,利用决策树根据融合结果推导出每个单独相的局部浓度。使用来自真实工业案例的数据,证明了所提出方法的可行性和稳健性。此外,所提出的方法还克服了传统基于阈值方法的局限性,因为需要先验知识才能对气-油-水管道流量进行定性和定量分析。