Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 6, Pages: 1-11
Abi P. Mathew1*, A. Asokan2 , K. Batri3 and D. Sivakumar2
1St. Joseph’s College of Engineering and Technology, Palai, Bharananganam Pravithanam Road, Choondacherry – 686579, Kerala, India; [email protected] 2Department of Instrumentation, Annamalai University, Rukmani Lakshmipathy Road, Egmore, Chennai – 600008, Tamil Nadu, India; [email protected], [email protected] 3PSNA College of Engineering and Technology, Kothandaraman Nagar, National Highway 209, Dindigul – 624622, Tamil Nadu, India; [email protected]
*Author for Correspondence
Abi P. Mathew
St. Joseph’s College of Engineering and Technology, Palai, Bharananganam Pravithanam Road, Choondacherry – 686579, Kerala, India; [email protected]
Background/ Objective: This article identifies the best feature of the flame video, captured with a camera with frequency response in visible spectrum, from which the flame temperature can be estimated. Methods/Statistical analysis: The flame videos at different air and fuel inlets with different boiler temperatures were recorded from a diesel fired boiler prototype. In the video frames, the flame region was localised by intensity based adaptive thresholding. The correlation between boiler temperature and measures of central tendency and dispersion of different colour channels of the video frames were investigated. Findings: Among the features of the flame video, Standard deviation of blue channel grey levels above 32.95, variance greater than 1293 and mean absolute deviation (MAD) above 30.38 could efficiently represent the region of optimum combustion air supply at which boiler temperature is maximum above 684 degree Celsius. Range of green channel grey levels, interquartile mean, variance and mean absolute deviation of blue channel grey levels are the video features exhibiting maximum correlation (ρ>-0.96) with boiler temperature. Applications/Improvements: The features of the flame video which are correlated with its temperature can be utilised to develop non-intrusive methods of temperature measurement. This will enable efficient control of combustion process.
Keywords: Combustion, Flame Image Processing, Flame Temperature Measurement, Image Features, Video Processing
Subscribe now for latest articles and news.