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Emission Control Science and Technology

Erschienen in:

22.09.2022

Steady-State NO_x Emission Model for Gas-Fired Heating and Hot Water Combi-Boilers with Factor Analysis and Artificial Neural Network

verfasst von: Weiye Zhou, Wenxue Gao, Hongting Ma, Wenbo Liu, Lijie Yang, Lin Yang

Erschienen in: Emission Control Science and Technology | Ausgabe 3-4/2022

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Abstract

In light of partial state of NO_x of gas-fired heating and hot water combi-boilers cannot be monitored or the NO_x measurement is inaccurate, an online NO_x emission model with high accuracy is essential. Seven parameters of NO_x have been selected in this study, and an effective NO_x emission model based on the factor analysis and radial basis function was developed. The prediction model is also compared to other five artificial neural network and regression methods. Twenty combi-boilers are measured, and the results are utilized for factor analysis and radial basis function model prediction, artificial neural network, and regression prediction. The results indicate that factor analysis and radial basis function model have significantly higher prediction accuracy than artificial neural network and regression models. The proposed factor analysis and radial basis function model may be a preferable solution for the development of accurate NO_x emission online monitoring system of gas-fired combi-boilers.

Vorheriger Artikel Studies on the Effect of Swirl on Nitric-Oxide Formation in Combustion—a Selected Review

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Titel: Steady-State NOx Emission Model for Gas-Fired Heating and Hot Water Combi-Boilers with Factor Analysis and Artificial Neural Network
verfasst von: Weiye Zhou
Wenxue Gao
Hongting Ma
Wenbo Liu
Lijie Yang
Lin Yang
Publikationsdatum: 22.09.2022
Verlag: Springer International Publishing
Erschienen in: Emission Control Science and Technology / Ausgabe 3-4/2022
Print ISSN: 2199-3629
Elektronische ISSN: 2199-3637
DOI: https://doi.org/10.1007/s40825-022-00216-7

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