Monitoring Turbulent Nonpremixed Flames in an Industrial Boiler Using Multivariate Image Analysis (MIA)

An on-line digital imaging system is developed for monitoring flames in an industrial boiler system. The information extracted from the RGB flame images is used to predict the performance of the boilar system. Multivariate Image Analysis (MIA) methods are the key methodologies used to efficiently extract information from the rapidly time-varying flame images, and to relate them to boiler performance. The methodologies are illustrated using two case studies. The performance of the boiler and the NOx and SO2 concentrations in the off-gas are successfully monitored using the information from the flame images. The approach is very general and can be applied to a wide range of combustion processes.