科研之友
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摘要
A good understanding about relationships among key process parameters is important in optimizing operation and enhancing efficiency of the CO2 capture process system. This understanding would enable the operator to better analyze process conditions and become aware of ongoing trends or events so that timely and effective control actions can be taken for adjusting the relevant process parameters and efficiency of plant operations can be enhanced. The studies that focused on exploring the key parameters of the amine-based post-combustion CO2 capture process system implemented at the International Test Center of CO2 Capture (ITC) have revealed that among multiple data modeling techniques adopted, the adaptive-network-based fuzzy inference system (ANFIS) modeling approach generated satisfactory models for adequately describing the process system. This paper presents development and application of the four ANFIS models for solving four real-life problems encountered in operation of the CO2 capture process system. The testing results of the four developed models show that they can be applied for satisfactory solution of these problems. Some lessons and observations made during the application process are also discussed.
- 出版日期2013-7
