Тип публикации: статья из журнала
Год издания: 2024
Идентификатор DOI: 10.1134/S1810232824040015
Аннотация: The production of cement clinker faces many management challenges, particularly in terms of consistently high product quality, efficient energy usage, and stable furnace operation. In this study, a machine learning model based on gradient boosting was developed for the efficient operation modes of the kiln (required quality and lowПоказать полностьюenergy consumption). The influence of process parameters on the efficiency of the clinker kiln was investigated. As a result, it was shown that stable kiln feeding improves the quality of the final product. High feeding variation leads to an increase in the dispersion of the entire setup and attempts to maintain it in a stable state by changing the volume of burned gas. When there is high feeder operation variation, the lime saturation factor has a significant impact on the outcome. The obtained results can be used to create a digital assistant for the kiln operator.
Журнал: Journal of Engineering Thermophysics
Выпуск журнала: Т. 33, № 4
Номера страниц: 675-682
ISSN журнала: 18102328
Место издания: Moscow
Издатель: Pleiades Publishing, Ltd.