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Data fusion in dual-mode tomography for imaging oil–gas two-phase flow
- Source :
- Flow Measurement and Instrumentation. 37:1-11
- Publication Year :
- 2014
- Publisher :
- Elsevier BV, 2014.
-
Abstract
- Process tomography (PT) techniques have been developed rapidly for visualizing the internal behavior of industrial processes, e.g. multi-phase flow measurement. Most of tomography systems employ a single measurement technique, such as computerized tomography (CT), optical tomography (OT), electrical resistance tomography (ERT) or electrical capacitance tomography (ECT). It is now possible to fit two or more tomographic systems to an industrial process. Detailed information from different modalities can be gained by inspection of separate tomographs, and the advantage of the strongest features provided by each unit can be taken. A combined tomogram can be produced of superior quality to any of the separate tomograms. To maximize the information available from the combined tomographic system, data fusion is the better option. In this paper, a dual-mode tomography system based on capacitance sensor and gamma sensor was developed to capture oil–gas two-phase flow. The two modalities can work at the same time. Two fusion methods, namely image fusion method and data fusion method, are proposed. Both simulation and static experiments for oil–gas two-phase flow were conducted. The reconstruction results of different fusion methods and modalities were compared and discussed.
- Subjects :
- Image fusion
medicine.diagnostic_test
Computer science
business.industry
Industrial computed tomography
Electrical capacitance tomography
Iterative reconstruction
Sensor fusion
Computer Science Applications
Modeling and Simulation
medicine
Computer vision
Tomography
Artificial intelligence
Electrical and Electronic Engineering
Optical tomography
Industrial process imaging
business
Instrumentation
Subjects
Details
- ISSN :
- 09555986
- Volume :
- 37
- Database :
- OpenAIRE
- Journal :
- Flow Measurement and Instrumentation
- Accession number :
- edsair.doi...........ad7425f4434669f47e1d14ac69349b06