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Research on Three-dimensional Temperature Field Reconstruction Technology of Bioler Furnace
Author: LiuXiaoYang
Tutor: YuYang
School: Shenyang University of Technology
Course: Detection Technology and Automation
Keywords: Boiler Flame radiation image BP algorithm Three-dimensional temperature field
CLC: TP399-CA
Type: Master's thesis
Year: 2009
Downloads: 83
Quote: 0
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Abstract
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A large boiler pulverized coal combustion occurs in the range of large space , constantly pulsating , obvious three-dimensional characteristics of physical and chemical processes , combustion condition monitoring for boiler safety , economic efficiency , clean run of great significance . Diversity for large boiler burning flame changes , in real-time the status of the furnace flame furnace three-dimensional temperature field reconstruction technology has become the key to solve the problem . Based on image processing techniques for solving the three-dimensional combustion flame temperature distribution of the non- contact measurement , is a modern high-tech means of control . BP neural network and reconstruction of three - dimensional temperature field simulation and experimental verification , the application of three-dimensional temperature field reconstruction techniques even more practical significance . This paper begins with a brief introduction to colorimetry and BP neural network to the intake of the value of the temperature of the flame picture . In-depth discussions on the BP neural network model , put forward an improved BP neural network method , the means of the three-dimensional temperature distribution as a strike , its traditional optimization solving method does not have a lot of advantages . Second, the best values ??of the parameters of this paper, sample selection , the determination of the network layers , as well as learning step , and are based on the modified side edge training . Finally, with the trained BP network is a series of simulation and analysis , and experimental verification by the thermocouple point measurement value of the network , verify the results , but also proved that the BP neural network for the three-dimensional temperature distribution is evaluated taken is feasible.
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