RECOGNITION OF FURNACE FLAME COMBUSTION CONDITION BASED ON STOCHASTIC MODEL
The recognition of the furnace flame combustion condition is an important domain in the flame monitoring system. In recent years, the image processing technology is widely applied to detection of the flame combustion condition. The combustion in furnace, such as the combustion of the pulverized coal, is the complex, stochastic and unstable burning process. The flame images are static and include a lot of noise signals from different reasons; so the method based on the processing of the single image does not reflect the combustion in furnace exactly. In this paper, the stochastic model, that is, hidden Markov model (HMM) is introduced to achieve modeling and recognition of the flame combustion condition in furnace. It makes use of a hidden Markov process to characterize the image frames correlation in the image sequences and transition of image states where the model parameters are determined by the feature vectors of image frames that form the observation sequences. Experiments demonstrate that the HMM can better describe the flame combustion condition in the furnace so as to improve recognition performance.
Recognition Hidden Markov model Flame image Combustion condition Image frame
XIN ZHANG PU HAN BING WANG
Automation Department of North China Electric Power University, Baoding 071003, China;College of Ele Automation Department of North China Electric Power University, Baoding 071003, China College of Mathematics and Computer Science of Hebei University, Baoding 071002, China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
3934-3939
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）