Title :
Profiling and Characterization of Flame Radicals by Combining Spectroscopic Imaging and Neural Network Techniques
Author :
Krabicka, Jan ; Lu, Gang ; Yan, Yong
Author_Institution :
Control & Embedded Syst. Res. Group, Univ. of Kent, Canterbury, UK
fDate :
5/1/2011 12:00:00 AM
Abstract :
This paper presents the development of an instrumentation system for visualizing and characterizing free radicals in combustion flames. The system combines optical splitting, filtering, intensified imaging and image processing techniques for simultaneous and continuous monitoring of specific flame radicals ( OH*, CN*, CH*, and C2*). Computing algorithms are developed to analyze the images and quantify the radiative characteristics of the radicals. Experimental results are obtained from a gas-fired combustion rig to demonstrate the effectiveness of the system. The information obtained by the system is used to establish relationships between radical characteristics and air-to-fuel ratios of combustion gases, helping to obtain an in-depth understanding of burn characteristics.
Keywords :
combustion; free radicals; image intensifiers; imaging; neural nets; combustion flame; free radicals; gas fired combustion; image processing technique; instrumentation system; intensified imaging; neural network technique; spectroscopic imaging; Artificial neural networks; Charge coupled devices; Combustion; Fuels; Optical imaging; Optical sensors; Electron-multiplying charge-coupled device (EMCCD); flame; flame radicals; image processing; neural networks; principal component analysis (PCA);
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2010.2102411