Data reduction processing method and device for blast furnace molten iron silicon content prediction model

A technology of blast furnace molten iron and prediction model, which is applied in the fields of electrical digital data processing, special data processing applications, instruments, etc.

Active Publication Date: 2017-12-12
CENT SOUTH UNIV
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Problems solved by technology

[0004] However, due to the limitations of the definition of reduction, there are multiple reduction results in an original data set, and traditional reduction algorithms often only randomly calculate one result

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  • Data reduction processing method and device for blast furnace molten iron silicon content prediction model
  • Data reduction processing method and device for blast furnace molten iron silicon content prediction model
  • Data reduction processing method and device for blast furnace molten iron silicon content prediction model

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Embodiment Construction

[0073] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0074] Such as figure 1 and figure 2 As shown, a data reduction processing method for the prediction model of silicon content in blast furnace molten iron includes the following steps:

[0075] Step1, by analyzing the operation mechanism of the blast furnace smelting process, calculate the correlation of the collected blast furnace smelting data, and formulate the priority sequence P of the blast furnace smelting condition attribute data in combination with the actual operation experience of the on-site workers;

[0076] The blast furnace smelting data refers to oxygen enrichment rate, standard wind speed, air permeability index, cold air flow, bosh gas volume, bosh gas index, theoretical combustion temperature, top pressure, oxygen enrichment pressure, cold air pressure, total pressure difference, hot air Pressure, actual wind speed, hot blast tempe...

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Abstract

The invention discloses a data reduction processing method and device for a blast furnace molten iron silicon content prediction model. According to the method, process characteristics, data characteristics and practical experience of workers of blast furnace molten iron smelting are introduced and converted into property priority sequences, a necessary set conflict detection mechanism and a recursive method are utilized, and therefore it is guaranteed that solved reduction is unique and is most matched with an application. The set necessary set BS guarantees non-redundancy of properties in a reduction set R and is used for judging a core property conflict; a recursive mode is adopted to solve the most matching reduction, and by use of site protection of recursion, the simplest mode is directly used to return to the last state one by one when the core property conflict is encountered without the need for performing state recovery; and the whole processing process is easy to operate, the calculation result is accurate, and the method has high popularization value.

Description

technical field [0001] The invention relates to a data reduction processing method and device for a blast furnace molten iron silicon content prediction model. Background technique [0002] Prediction of silicon content in blast furnace hot metal is a key step in the optimal control of blast furnace smelting. The forecast results have a decisive influence on the adjustment of operating parameters, and are a necessary way to improve the quality, output, resource and energy utilization of molten iron. Due to the complexity of the process mechanism, the prediction method based on data modeling has become the mainstream of silicon content prediction. However, due to the different degrees of coupling between the input parameters, the existing model input parameter sets based on correlation solutions are difficult to achieve The best match of the prediction model, which will affect the prediction hit rate. Therefore, it is necessary to adopt a reasonable method to calculate the ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
CPCG16Z99/00
Inventor 尹林子程攀许雪梅蒋朝辉丁家峰李乐李靖
Owner CENT SOUTH UNIV
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