Blast furnace crude fuel evaluation method based on data self-learning
A technology of raw materials and self-learning, which is applied in the quality management of blast furnace raw materials and blast furnace production, and can solve the problems that a scientific and systematic evaluation system has not been formed, and the conditions of blast furnaces cannot be greatly optimized.
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[0008] Combined with the actual production of blast furnaces, and using statistical analysis principles in technology, a raw and fuel evaluation model for data self-learning was established, which accurately reflected the quality level of raw and fuels with quantitative analysis methods, and realized the scientific evaluation of the quality of raw and fuel for blast furnaces. The operation has significant guiding significance and practical value. This evaluation method has been successfully applied to the 6# blast furnace of Taiyuan Iron and Steel Co., Ltd., and achieved good results. The main benefits are as follows:
[0009] The daily output of molten iron in 6# blast furnace of TISCO was increased from 9577t / d to 10089t / d. According to the normal production and operation of iron and steel enterprises, the economic benefit brought by each ton of molten iron to the enterprise is at least 200 yuan / tFe; the fuel ratio is reduced from 513.8kg / tFe to 506.0kg / tFe (of which: the co...
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