Steel enterprise blast furnace by-product gas emergence size prediction method

Abstract

The invention discloses a steel enterprise blast furnace by-product gas emergence size prediction method comprising the following steps: reading emergence size data of blast furnace gas from a real time database of a steel enterprise field; preprocessing a collected original data sequence, and detecting an abnormal value in the blast furnace gas data sequence; inputting the preprocessed data sequence into a set least square support vector machine model for prediction, using an improved particle swarm algorithm to optimize a nucleus width parameter and a punishment factor parameter of the least square support vector machine, thus improving prediction precision. The method is accurate, can fast detect abnormal data in the blast furnace gas emergence size, and can replace the abnormal data in the original data; the least square support vector prediction model based on minimum structure risk is set, and optimized by the improved particle swarm algorithm, thus improving prediction precision of the model, and a prediction result can provide basis for reasonable utilization of the gas resource.

Description

Technical field [0001] The invention relates to the field of information technology, in particular to a method for predicting the amount of by-product gas generated from a blast furnace in an iron and steel enterprise. Background technique [0002] The production process of steel can be divided into: coking, ironmaking, steelmaking, steel rolling and other links. The energy required for these production links is mainly provided by fossil fuels such as coke. When fuel is consumed, a variety of combustible gases are generated, that is, coal gas as a by-product of iron and steel enterprises. The generated by-product gas will be collected in a centralized manner, and then piped to various production workshops to act as a combustion aid for smelting. According to statistics, 40% of the primary energy consumed in iron and steel production is converted into by-product gas, and among all kinds of by-product gas, the output of blast furnace gas accounts for about 45% of the total by-prod...

AI Technical Summary

Problems solved by technology

However, the recognition rate of manual judgment cannot be guaranteed, and false detections are prone to occur, which has a great impact on the establishment of subsequent BP neural network models.

This patent uses the method of BP neural network to establish a prediction model, but the BP neural network model is based on the principle of empirical risk minimization. As the prediction progresses, the generalization ability of the model will decrease, resulting in a decrease in prediction accuracy

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