Researchers Temirbolat Maratuly, Pakizar Shamoi, and Timur Samigulin from the Satbayev University in Kazakhstan have developed a novel approach to automate and optimize the purification process of sour water, a byproduct of crude oil processing. Their work, published in the journal Computers & Chemical Engineering, combines a fuzzy expert system with a digital twin to create an intuitive control strategy for maintaining key parameters in the purification process.
Sour water contains acidic components like hydrogen sulfide and carbon dioxide, which can cause significant environmental harm and accelerate corrosion in pipelines and equipment if not properly treated. The researchers aimed to create a system that could reduce emissions, minimize corrosion risks, enable water reuse, and lower operational costs while also reducing the need for human intervention, thereby improving worker safety.
The team developed a fuzzy expert system that mimics human reasoning to control the purification process. This system was integrated with a digital twin, a virtual replica of the industrial process, created using Honeywell UniSim Design R492. The digital twin accurately simulates real industrial behavior, allowing the fuzzy controller to be tested and refined in a virtual environment. Valve dynamics were modeled using MATLAB, and real-time data exchange between the simulator and controller was established using OPC DA.
The fuzzy controller applies split-range control to two valves and was tested under 21 different initial pressure conditions using five distinct defuzzification strategies, resulting in a total of 105 unique test scenarios. The system’s performance was evaluated using both error-based metrics and dynamic response metrics, ensuring its effectiveness and reliability.
One of the key advantages of this system is its simplicity and intuitiveness, allowing junior or non-expert personnel to interact with it effectively. Additionally, a web-based simulation interface was developed in Python using the Streamlit framework, making the system more accessible and user-friendly.
While this research focuses on sour water treatment, the proposed fuzzy expert system is general-purpose and can be applied to other industrial processes. This innovation has significant implications for the energy sector, particularly in oil and gas processing, where efficient and safe water treatment is crucial. By automating the purification process and reducing the need for human intervention, this system can help lower operational costs, improve worker safety, and minimize environmental impact.
The research was published in the journal Computers & Chemical Engineering, providing a valuable contribution to the field of industrial process control and automation.
This article is based on research available at arXiv.