2025-07-112025-07-112025-09Anweiler, S., Krok, M., Kołodziej, S., Chacartegui, R., Becerra Villanueva, J.A., Sikora, M.,...,Przysiężniuk, D. (2025). Vision-based adaptive control system for fluidized bed reactors. Measurement, 255, 118046. https://doi.org/10.1016/j.measurement.2025.118046.0263-22411873-412Xhttps://hdl.handle.net/11441/175251This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).In process engineering, precise, automatic, and dynamic identification of two-phase structures remains a challenging yet essential task, particularly for effectively controlling pneumatic systems handling solid particles. Complex interactions between gas and solid phases and variable flow geometries complicate the precise control of fluidized beds. This study evaluates an adaptive, vision-based flow control system designed for fluidized bed reactors, using real-time image analysis to characterize flow structures. A self-developed air flow valve regulator system, combined with a programmable logic controller (PLC) and dynamic image feedback, enables this innovative control approach. By analyzing grey-level signals within specified regions of interest (ROIs), the system accurately differentiates between critical fluidization regimes: bubbling, plugging, and turbulent flow. The control algorithm dynamically adjusts the flow rate, achieving a mean square error of 6.98 m3/h, underscoring the system’s reliability and potential for further optimization. Additionally, safeguards were implemented to prevent material loss at high airflow thresholds, enhancing system stability and safety. The findings demonstrate the potential of adaptive vision-based control for fluidized bed automation, offering an advanced solution for real-time monitoring and precise flow regulation in complex two-phase processes.application/pdf14 p.engAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/Two-phaseFluidizationVisualizationImage analysisPneumatic valve controlPLCAutomatic controlinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccesshttps://doi.org/10.1016/j.measurement.2025.118046