Whole-flame image analysis using geometric and complexity measures

Inefficient operation and control in commercial and industrial furnaces and boilers are responsible for wasting large amounts of fuel and releasing excess greenhouse gases (CO₂ and N₂O) and pollutants (CO, NO_x). In the United States only a fraction of fossil-fueled utility and industrial combustion systems is subject to advanced diagnostics and closed-loop control which could improve efficiency and reduce emissions. It is now recognized that continuous monitoring and control of both individual burners and groups of burners in boilers is essential to meet and sustain ever more stringent greenhouse and pollutant emission limits. This has become especially true as incremental improvements in burner performance have become disproportionately more difficult, and this difficulty is exacerbated by variations in fuel properties. In this work, we outline how recent developments in video image and signal processing and computational power enable video-based monitoring and analysis of flames based on their whole luminous extent, not just small portions of the flame as is the case in many burner-monitoring systems. Using a laboratory-scale gas burner, we demonstrate geometric and complexity measures which can provide information about flame stability. Especial emphasis is placed on complexity measures which account for the inherent nonlinear behavior of unstable flames, such as those exhibiting intermittent liftoff. Such discriminating metrics will be needed for the next generation of commercial burner-monitoring systems.