A Decision Support System for Filtering and Analysis of Carbon Dioxide Capture Data

Abstract

This paper presents the development process of a decision support system for pre-filtering and analysis of data for the carbon dioxide (CO2) capture process. Chemical absorption is becoming 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. Monitoring the vast amount of data can be complex, and data filtering and analysis processes are desirable. Specifically, invalid data captured as the equipment is started and shut down need to be filtered, and the filtered data need to be analyzed for different purposes. The data analysis support system not only filters out invalid data using different expert rules, but can also modify or reuse filtering settings, and export the filtered data to various file formats for further analysis. During development of the decision support system, knowledge acquisition was emphasized. The system was designed based on the model-view-control (MVC) design pattern. Source code management (SCM) software and strategy were applied to allow multiple developers to work together. Embedded database technology, Java event delivery techniques and extensible Markup Language (XML) were also included in development of the system.