Boiler fly ash carbon content prediction method and system

Abstract

The invention discloses a boiler fly ash carbon content prediction method and system, and the method comprises the steps: obtaining and standardizing a historical data set of boiler operation, and enabling a standard data set to serve as a sample point; inputting the standard data set into a linear regression model, correspondingly outputting the carbon content of the flue gas fly ash, and training to obtain the linear regression model; inputting the standard data set and the obtained characteristics of the carbon content of the flue gas fly ash into an XGBoost model, correspondingly outputting the carbon content of the flue gas fly ash to obtain an initial XGBoost prediction model, and performing parameter optimization on the initial XGBoost model to obtain an optimal XGBoost prediction model; and inputting the standard data set into a recurrent neural network, correspondingly outputting the carbon content of the flue gas fly ash, training to obtain an initial neural network model, and performing parameter optimization on the initial neural network to obtain an optimal recurrent neural network. The outputs of the three models are subjected to linear regression to obtain a fusion model, the fusion model is used for predicting the carbon content of the flue gas fly ash generated by the boiler, and the prediction precision of the emission concentration of the carbon content of the fly ash is improved.

Description

technical field

[0001] The invention belongs to the technical field of boiler fly ash carbon content control, and more specifically relates to a method and system for predicting the carbon content of boiler fly ash. Background technique

[0002] The country's requirements for environmental protection are increasing day by day. This requirement has promoted the continuous improvement of the requirements for flue gas emissions from power plant boilers in related enterprises, and has triggered related technical research on boiler nitrogen oxides and carbon content in fly ash. At present, the core technology of controlling carbon content in fly ash lies in the research on the prediction model of carbon content in fly ash at boiler outlet. Related modeling methods have been carried out for many years, but it is still only for the case of stable load, which can obtain better The prediction accuracy of carbon content in fly ash is still low under variable working conditions. [00...

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