Research On Three-dimensional Temperature Field Reconstruction Technology Of Bioler Furnace

The combustion of pulverized-coal in large-scale boiler is a complexly physical and chemical reaction, which is occurred in large space, fluctuating frequently, with conspicuous three-dimension character. Monitoring the combustion status is very important for boiler's safety, economic benefits, clean operation. Because of the variety of burning flame in furnace of large-scale boiler, in order to know and control the condition of the burning flame in furnace, it is the key to research on how to reconstruct the three-dimensional temperature field in furnace.It is a non-contact measurement based on image processing technology to research on the three-dimensional temperature distribution of burning flame in furnace, which is modern high-tech control means. The investigation on BP neural networks and the simulation on reconstruction of three-dimensional temperature field make reconstructio -n technology more practical.In the paper, firstly, the basic method getting flame image temperature values is introduced in use of colorimetry and BP neural networks. BP neural networks model is delved into in depth and an improved BP neural networks is given, by which three-dimensional temperature distribution could be gotten, and which is superior to the traditional optimizing method. Then, the method selecting sample, network layer, the optimum values of study step and other parameters is to train the network and to modify it. Finally, a series of simulation and analysis with the trained network are done and the network is validated by the experiment of measuring temperature point to point with thermocouple. The result is ideal in degree. It is feasible to use BP neural networks to get three-dimensional temperature distribution.