As the quality of the coke and the life-span of the coke oven are connected closely with the coke oven flow temperature, the temperature of coke oven flow is one of significant technical parameters in the coke oven heating system. However, it is difficult to detect the coke oven flow temperature as the high temperature always makes the thermocouple out of use and consuming much in the thermocouple. And that has been a difficult problem which puzzles people for a long time.
In the view of technical mechanism, this paper analyzed several factors associated with the coke oven flow temperature, including the temperature in the regenerator, the reverse operation of the coal gas, the operation of coke pushing, the percentage of water in the coal, the coal gas type and heat quality, the gas flowing flux and the weather and etc. Following a kind of soft sensor model was put forward, which can be divided into two sorts of sub-model, linear regress model and neural network model. The temperature at the top of the regenerator and the water percentage in coal were selected as the variables, and the flow temperature of double sides of the oven were predicted by the sub-models. In order to improve the precision of the model, the paper constructs the rules library based on the experts’ experiences. The method is valid and feasible which are proved by the simulation.
