Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography.
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...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2004
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| Subjects: | |
| Online Access: | http://eprints.usm.my/8612/ http://eprints.usm.my/8612/1/Neural_Computation_for_Flow_Regime_Classification_Based_on_Electrical_%28PPKEElektronik%29_2004.pdf |
| Summary: | 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. |
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