Wang, Q, Jia, X orcid.org/0000-0001-8590-7477 and Wang, M orcid.org/0000-0003-0941-8481 (2020) Fuzzy Logic Based Multi-Dimensional Image Fusion for Gas–Oil-Water Flows With Dual-Modality Electrical Tomography. IEEE Transactions on Instrumentation and Measurement, 69 (5). pp. 1948-1961. ISSN 0018-9456
Abstract
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Decision tree, dual-modality electrical tomog-raphy, fuzzy logic, gas–oil–water flow, multi-dimensional datafusion, multiphase flow visualization |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/H023054/1 Innovate UK - KTP fkaTechnology Strategy Board (KTP) KTP9752 |
Depositing User: | Symplectic Publications |
Date Deposited: | 29 Jul 2019 16:16 |
Last Modified: | 08 May 2020 02:31 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/TIM.2019.2923864 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:149072 |