Method for prediction of blast furnace heat tendency

Abstract

The invention discloses a method for prediction of a blast furnace heat tendency. The method includes: establishing an RBF neural network computation model, a blast furnace charge speed computation model, and a theoretical combustion temperature computation model of the Si content in blast furnace molten iron respectively, then utilizing the judgments, i.e. Index1, Index2, Index3, of the 3 models on a blast furnace heat tendency result to comprehensively judge whether the blast furnace has a heat tendency, and if the sum of delta1.Index1+delta2.Index2+delta3.Index3 is greater than or equal to 1, with delta1 belonging to [0, 1], delta2 belonging to [0, 1], and delta3 belonging to [0, 1], thus determining that the blast furnace has a heat development tendency. The method provided in the invention makes comprehensive consideration of the physical factors and chemical factors of the blast furnace on judgment of the blast furnace heat development tendency. Compared with the prior art, the method can more accurately predict the imminent heat development tendency of the blast furnace in advance, and can adopt measures to control the blast furnace temperature within a reasonable temperature range on the basis, thus avoiding deviation or misjudgment of different operators on blast furnace operation conditions, and being very beneficial to efficient blast furnace operation.

Description

technical field [0001] The invention relates to the field of blast furnace ironmaking monitoring, in particular to a method for predicting blast furnace heat tendency. Background technique [0002] Blast furnace ironmaking is the main way for modern iron and steel enterprises to produce pig iron. The production process is accompanied by a large number of strongly coupled, nonlinear, and large time-delay physical and chemical reactions. The complex process inside the blast furnace makes it difficult to use conventional methods. Advanced detection equipment and detection means to directly obtain the physical and chemical state inside the blast furnace. The thermal state inside the blast furnace is the most direct reflection of the smooth running of the blast furnace. If the blast furnace is too cool, it is not conducive to the smooth separation of iron and slag iron. Overheating will not only make the blast furnace difficult to operate but also cause a lot of energy waste. Th...

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Problems solved by technology

In view of the fact that the thermal state of the blast furnace is an important indicator reflecting the working state of the blast furnace, it is very important for the blast furnace operator to predict the trend of the blast furnace's thermal development, but the complex and changeable inside of the blast furnace determines that its thermal development trend cannot be directly obtained by the blast furnace operator

The conventional means of predicting the thermal development trend of blast furnace is to judge the thermal trend of blast furnace indirectly by means of the silicon content in blast furnace molten iron, but this method needs to solve the relationship between various process variables of blast furnace and the silicon content in blast furnace molten iron. Mathematical models, regardless of whether the mathematical model uses a time series model or an artificial neural network model to predict the development trend of the blast furnace to heat, the prediction results are not ideal

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