Yasmin, Abdul Wahab and Syazwani Amanina, Syakyean and Zainah, Md. Zain and Nor Maniha, Abd Ghani and Maziyah, Mat Noh (2018) Initial study of multiple excitation source for electrical resistance tomography in steel pipe application. In: Proceedings of the 10th National Technical Seminar on Underwater System Technology 2018. Lecture Notes in Electrical Engineering . Springer Singapore, Singapore, pp. 353-359. ISBN 978-981-13-3708-6
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Abstract
Tomography is a method of reconstructing the image of an object’s interest within the sensing zone. Electrical resistance tomography (ERT) system operates when using current as an excitation source and output voltage is meas-ured at the detection electrode and the research will result in the changes of elec-tric potential distribution. A lot of researches have been made using ERT to iden-tify a liquid-gas regime in the steel pipe focused on improving image resolution of the regime. However, a common excitation source of ERT used only a single excitation. Thus, this research uses COMSOL Multiphysics as a platform for sim-ulation of multiple excitations of electrical resistance tomography for liquid-gas regime identification in steel pipe. The analysis and performance of new simula-tion which applies multiple excitation sources have been compared with the sin-gle excitation. Besides, the project is limited to 54mm inner diameter of the steel pipe. As a conclusion, 50% of the excitation source can increase the image reso-lution of those regimes especially in the middle of the steel pipe.
Item Type: | Book Chapter |
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Additional Information: | Indexed by Springer |
Uncontrolled Keywords: | ERT; Multiple Excitation Source; Steel Pipe |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Faculty/Division: | Faculty of Electrical & Electronic Engineering |
Depositing User: | Pn. Hazlinda Abd Rahman |
Date Deposited: | 24 Dec 2018 08:32 |
Last Modified: | 27 May 2019 08:25 |
URI: | http://umpir.ump.edu.my/id/eprint/22973 |
Download Statistic: | View Download Statistics |
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