Prediction method of blast furnace gas generation and calorific value based on gas composition change

Abstract

The invention provides a method for predicting the amount of blast furnace gas and its calorific value based on the change of gas composition. A gas composition analyzer is installed behind the blast furnace gas gravity dust collector or bag dust removal device, and the blast furnace top gas composition in the blast furnace production process is analyzed. On-line analysis is carried out, and at the same time, the blast furnace gas composition, blast furnace blast volume, and oxygen-enriched amount are used as the main variables, and the calculated value of the balance of blast furnace blast and N2 in the gas is used as the benchmark to predict in advance the blast furnace gas generated during the ironmaking production process and its Calorific value of coal gas, through this method, the generation of blast furnace gas and its calorific value can be predicted with high precision (≥95%), which lays a technical foundation for the realization of dynamic optimal scheduling of corporate gas and the detection and application of gas calorific value by downstream blast furnace gas users ; It plays an important role in realizing zero emission of gas in enterprises and online regulation of air-fuel ratio by downstream gas users.

Description

technical field [0001] The invention relates to the technical field of iron and steel production, in particular to a method for predicting the amount of blast furnace gas generated and its calorific value based on gas composition changes. Background technique [0002] Gas is the most important secondary energy for iron and steel enterprises. It is the "blood circulation" system on which iron and steel enterprises rely. The ultimate goal of enterprise gas management. The basis for realizing zero emission of gas is the dynamic balance scheduling of gas to ensure that the amount of gas generated in each period is consistent with the amount used. The purpose of gas balance scheduling is to predict the gas volume and user consumption of gas in the future period, and realize the gas balance in the future period by adjusting the operating parameters of gas generation equipment and equipment (including buffer equipment). However, due to the many and complex factors affecting the a...

AI Technical Summary

Problems solved by technology

One is the time series forecasting method, which is based on the principle of continuity. Only when the assumption of "the past is so, and the future will be the same" is met, can the historical data be used to predict its future. Once this assumption is not established, the prediction results are often biased larger

The second is the causal relationship prediction method, which is based on the "causal relationship" prediction principle. Only when the precondition of "cause determines the result" is established, can the deterministic relationship (functional relationship) or non-deterministic relationship (correlation relationship) between related variables be established. relationship, such as data regression analysis method, artificial neural network method) to predict its future; but because there are many factors affecting the prediction of blast furnace gas production and its calorific value (such as: coke ratio, coal injection ratio, coke ratio, hot blast temperature, blast volume, oxygen enrichment rate, blast furnace operation, etc.), and the correlation is not clear, the collected data is incomplete, the data is inaccurate, etc., making the prediction accuracy difficult to meet the actual needs of production

There are deficiencies in the two forecasting methods, which need to be further studied and solved

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