A GENERIC INTELLIGENT OIL-GAS FLOW CLASSIFIER BASED ON ECT SENSOR DATA

作者：Zainal Mokhtar Khursiah; Mohamad Saleh Junita^*

来源：International Journal of Innovative Computing Information and Control, 2012, 8(1B): 953-965.

• Generic classifier
• Flow regime
• Electrical capacitance tomography
• Artificial neural network

Many flow regime classification systems based on Electrical Capacitance Tomography (ECT) sensor data have been developed, but they only focused on fixed ECT sensor parameters. Due to fixed sensor parameters, the systems are not generic because they can only work with data based on the particular ECT sensor parameters. This paper presents the work on developing a generic flow classifier which can flexibly accept data obtained from different ECT sensor parameter values. The generic system employs an Artificial Neural Network (ANN) trained with ECT data based on a range of ECT parameters. The developed system has shown to be able to handle ECT data of different sensor parameters and correctly classify their corresponding flow regimes to a certain degree of accuracy. Industries are able to save design costs by using such a system.

• 出版日期2012-1