Sintering ignition temperature modeling prediction method based on working condition recognition

Abstract

The invention provides a sintering ignition temperature modeling prediction method based on working condition recognition. The method comprises the following steps: carrying out the clustering of a plurality of working conditions in an ignition process through an FCM clustering method, and determining the types of the working conditions; carrying out DBI index calculation on the determined workingcondition category, and determining the working condition number of the sintering ignition process; and then based on different groups of actual data obtained after clustering, establishing the determined ignition temperature prediction model PSOElman under each specific working condition. According to the invention, the defect that the precision of a single prediction model becomes poor when theworking condition in the ignition process changes is overcome, whether the working condition in the ignition process changes or not can be judged according to real-time feedback data, and if yes, thecurrent working condition can be recognized and switched to the corresponding prediction model for prediction; therefore, it is guaranteed that the ignition temperature can be predicted by the most suitable PSO-Elman prediction model under various working conditions for a long time scale, and therefore long-term and efficient prediction precision is kept.

Description

technical field [0001] The invention relates to the technical field of sintering ignition, in particular to a method for modeling and predicting sintering ignition temperature based on working condition identification. Background technique [0002] The iron and steel industry is an important basic industry for the development of the national economy. Sintering production is an important process in the ironmaking process and the main way to artificially enrich ore. The sinter produced is used for blast furnace smelting. The quality and output of sinter have a direct impact on blast furnace production. , and then affect the effect of the entire ironmaking production. The sintering production process generally includes batching, mixing and granulation, segregation and distribution, ignition, ventilation and sintering, cooling, crushing and screening, etc. Sintering ignition is an important process in sintering production, and the effect of ignition will profoundly affect the qu...

AI Technical Summary

Problems solved by technology

For the research on the ignition temperature prediction model, most of them can only have a good prediction effect when the short-time scale operating conditions are stable, and when the long-term scale operating conditions change, the prediction effect will become worse

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