An architectural framework for developing intelligent systems for the CO2 capture process

This paper presents the architectural framework for developing intelligent systems for the CO₂ capture process (CO2AFIS). Chemical absorption is one of the dominant CO₂ capture technologies because of its efficiency and low cost. Since the chemical absorption process consists of dozens of components, it generates more than a hundred different types of data. Effective monitoring, analysis and diagnosis of the complex process could be difficult. The framework proposed in this paper is designed and constructed to integrate various data-driven, analytical, and knowledge-based approaches for developing intelligent support solutions for the CO₂ capture process. The framework has good extensibility. It supports efficient development and integration of artificial intelligent (AI) and non-AI decision support systems, and has a robust and well-defined library that facilitates development of intelligent systems.