ABSTRACT
Artificial intelligence (AI) technologies, such as the neural network–based methods and multi objective optimization, have been applied in industry to improve the efficiency of control systems. In addition, computational fluid dynamics simulation technology is widely applied in the power-generation industry to analyze combustion process, improve boiler design, and adjust burner-tilt angle in offline fashion after an overhaul or upgrade at a power plant. Nondominated sorting in genetic algorithm is one of the AI-based multi objective optimizations and is widely used to successfully optimize industry processes. The boiler-combustion process optimized using the AI-based boiler-optimization methods can not only maintain a higher heat transfer of the water wall but also keep the temperature in areas close to the sides of the furnace of the boiler within the ash-melting temperature limit. Furthermore, the software has been developed using CORBA C++ combined with ANSYS Fluent 14.5 to realize the AI-based boiler-optimization methods.
