Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography.

Mat-Dan, A. A. and Mohamad-Saleh, J and Ahmad, M. A. (2004) Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography. In: 1st National Postgraduate Colloquium School of Chemical Engineering, USM, 2004, School of Chemical Engineering, USM.

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    Abstract

    Recognition of gas-liquid flow regimes in pipelines is important in an industrial control process such as for oil production. In oil production, gas-liquid flows are normally concealed in a pipe the actual type of flows cannot be easily determined. Also, obtaining measurements corresponding to the flow distribution becomes almost impossible.

    Item Type: Conference or Workshop Item (Paper)
    Subjects: T Technology > TK Electrical Engineering. Electronics. Nuclear Engineering > TK1-9971 Electrical engineering. Electronics. Nuclear engineering
    Divisions: Kampus Kejuruteraan (Engineering Campus) > Pusat Pengajian Kejuruteraaan Elektrik & Elektronik (School of Electrical & Electronic Engineering)
    Depositing User: ARKM Al Rashid Automasi
    Date Deposited: 24 Mar 2009 15:15
    Last Modified: 13 Jul 2013 11:56
    URI: http://eprints.usm.my/id/eprint/8612

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