Applying Neural Network Technique for prediction of NOx Emission and Combustion Dynamics of an Experimental Turbulent Swirl-stabilized Combustor using flame image processing techniques

In the present study, direct flame images obtained from an experimental swirl stabilized combustor are used to predict the output parameters of the combustor including the level of NOx emission, amounts of noise and the level of pressure fluctuations in the combustor. For this purpose, different values of overall equivalence ratios in the range of 0.7-0.9 along with various amounts of secondary fuel injection rates between

کلیدواژه ها:

swirl-stabilized combustor ، secondary fuel injection ، pressure fluctuation ، Nox emission ، combustion process ، artificial neural network