An estimation model for cross temperature measuring in blast furnace ironmaking

Abstract

The cross temperature measuring device is applied to monitor the top temperature and gas flow distribution in the blast furnace (BF) during the ironmaking process. However, the temperature of the BF roof is relatively high, which causes damage to the cross temperature measuring device. Therefore, this paper proposes an efficient estimation method. First of all, the data filtering method are used to solve the problems of noise interference. Moreover, as the fact that BF cross temperature measurement is affected by interference factors, it is easy to cause information redundancy. Aiming at this, the maximum information coefficient (MIC) correlation analysis and sequence dislocation method are used to determine the input variables and its action time of the model. Finally, an estimation model based three-layer long and short-term memory network (LSTM3) is established. The experimental results show that the LSTM3 can estimate the centre temperature of cross temperature measuring device.

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