System and method for dynamical soft measurement of molten iron silicon content in blast furnace ironmaking process

Abstract

The invention provides a system and method for dynamic soft measurement of the molten iron silicon content in the blast furnace ironmaking process. The system comprises an actual data collection unit, a normalization pretreatment unit and a dynamic soft measurement unit. The method includes the steps that the parameters required by dynamic soft measurement of the blast furnace molten iron silicon content are obtained and comprise the operating parameters of the current furnace charge, the operating parameters of the previous furnace charge and the molten iron silicon content of the previous furnace charge; normalization pretreatment is conducted on the obtained parameters required by dynamic soft measurement of the blast furnace molten iron silicon content; and dynamic soft measurement of the molten iron silicon content is conducted through a model of dynamic soft measurement of the molten iron silicon content in the blast furnace ironmaking process. Compared with existing manual measurement or analysis of the molten iron silicon content, the workload of operators is reduced, measurement uncertainty introduced by manual operation is lowered, measurement timeliness and accuracy are improved, and the confidence level is high. The method has universality in prediction of the molten iron silicon content in the blast furnace ironmaking process, and closed-loop integrated control over the blast furnace molten iron quality and optimized operation can be achieved easily.

Description

technical field [0001] The invention relates to the technical field of automatic control of blast furnace smelting, in particular to a dynamic soft measurement system and method for silicon content in molten iron during the blast furnace ironmaking process. Background technique [0002] Blast furnace production is a continuous dynamic time-varying nonlinear multi-variable coupling system carried out under airtight conditions where high temperature, high pressure, multi-physical fields coexist, and chemical reactions and transfer phenomena occur simultaneously. The key factor of high yield, high quality and low consumption. During the smelting process, the quality of furnace temperature control directly affects the fluctuation of furnace conditions, and the fluctuation of furnace conditions determines the control mode of furnace temperature. "Too high" or "too low" furnace temperature can easily induce abnormal furnace conditions. In actual production, the key technology to ...

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Problems solved by technology

[0006] Most of the methods of the above-mentioned patents and related documents use all relevant variables collected by the blast furnace as input variables, making full use of the rich data features, but also introducing more noise and time-consuming problems.

In addition, in the actual production process, due to the failure of detection instruments and transmitters and other devices and the influence of complex electromagnetic interference, there are many unknown interferences in the measurement data, and its actual industrial background has a high impact on the robustness of the algorithm itself. However, the method reported in the above-mentioned patent has not considered the robustness issue. In view of changes in smelting conditions and abnormal jitter, the generalization ability of the silicon content prediction model in molten iron will be greatly reduced.

In addition, the above method does not consider the input-output timing and process time-delay relationship, so it cannot capture the inherent dynamic characteristics of the smelting process well

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