Research On Boiler Combustion Optimization System Based On The Neural Network

Boiler combustion optimization is to improve boiler efficiency and reduce nitrogen oxide emissions from boiler through adjustment of boiler operation. This paper put forward a new method based on artificial neural network and particle swarm optimization.Firstly, the paper analyzed the influential factors of boiler operating economy and established a simplified boiler model adapted combustion optimization. Secondly, the paper researched on the creation mechanism and control method of NO. Thirdly, the a BP neural network model has been built for predicting the boiler's performance, including NO emission, carbon content of the fly ash and exhaust gas temperature. At last, the paper researched on PSO algorithm and it's use in numerical optimization, and this algorithm was employed to perform a search to determine the optimum solution of combustion optimization.