According to the pulverized coal combustion flame image texture features of the rotary-kiln oxide pellets sintering process,a combustion working condition recognition method based on the generalized learning vector(GL...According to the pulverized coal combustion flame image texture features of the rotary-kiln oxide pellets sintering process,a combustion working condition recognition method based on the generalized learning vector(GLVQ) neural network is proposed.Firstly,the numerical flame image is analyzed to extract texture features,such as energy,entropy and inertia,based on grey-level co-occurrence matrix(GLCM) to provide qualitative information on the changes in the visual appearance of the flame.Then the kernel principal component analysis(KPCA) method is adopted to deduct the input vector with high dimensionality so as to reduce the GLVQ target dimension and network scale greatly.Finally,the GLVQ neural network is trained by using the normalized texture feature data.The test results show that the proposed KPCA-GLVQ classifer has an excellent performance on training speed and correct recognition rate,and it meets the requirement for real-time combustion working condition recognition for the rotary kiln process.展开更多
Based on conduction,convection and radiation heat transfer among the flue gas,kiln wall,and the pellet bed material,and on the basis of the coal combustion and analysis of reaction heat of pellet induration in the rot...Based on conduction,convection and radiation heat transfer among the flue gas,kiln wall,and the pellet bed material,and on the basis of the coal combustion and analysis of reaction heat of pellet induration in the rotary kiln,the temperature field model of rotary kiln was established.Using visual studio net,matlab and open source computer vision library as development tools,combining with the ActiveX data objects database technology,the temperature field simulation system for rotary kiln of iron ore oxidized pellet production was developed.Temperature distribution of pellet and flue gas in rotary kiln was dynamically displayed.展开更多
基金supported by China Postdoctoral Science Foundation(No.20110491510)Program for Liaoning Excellent Talents in University(No.LJQ2011027)+1 种基金Anshan Science and Technology Project(No.2011MS11)Special Research Foundation of University of Science and Technology of Liaoning(No.2011zx10)
文摘According to the pulverized coal combustion flame image texture features of the rotary-kiln oxide pellets sintering process,a combustion working condition recognition method based on the generalized learning vector(GLVQ) neural network is proposed.Firstly,the numerical flame image is analyzed to extract texture features,such as energy,entropy and inertia,based on grey-level co-occurrence matrix(GLCM) to provide qualitative information on the changes in the visual appearance of the flame.Then the kernel principal component analysis(KPCA) method is adopted to deduct the input vector with high dimensionality so as to reduce the GLVQ target dimension and network scale greatly.Finally,the GLVQ neural network is trained by using the normalized texture feature data.The test results show that the proposed KPCA-GLVQ classifer has an excellent performance on training speed and correct recognition rate,and it meets the requirement for real-time combustion working condition recognition for the rotary kiln process.
基金Sponsored by Program for New Century Excellent Talents in University of China(NCET-05-0630)
文摘Based on conduction,convection and radiation heat transfer among the flue gas,kiln wall,and the pellet bed material,and on the basis of the coal combustion and analysis of reaction heat of pellet induration in the rotary kiln,the temperature field model of rotary kiln was established.Using visual studio net,matlab and open source computer vision library as development tools,combining with the ActiveX data objects database technology,the temperature field simulation system for rotary kiln of iron ore oxidized pellet production was developed.Temperature distribution of pellet and flue gas in rotary kiln was dynamically displayed.
