佛山科学技术学院学报（自然科学版）2025，Vol.43Issue(5)：25-31,38,8.
一种瓦楞纸板生产线生产速度的智能预测方法
An intelligent prediction method for production speed of corrugated cardboard production line
摘要
Abstract
The wet-part production speed of corrugated board lines is an important indicator representing the production efficiency.Its intelligent prediction can guide the enterprises to reasonably arrange the production and enhance the control level of the production line,which is of great significance for the efficient and green production of corrugated board.Firstly,data cleaning is performed on multi-type sampled data.The Bessel filters and quartile statistics methods are used to select the data of production speed in the stable interval,and the production parameters corresponding to B-corrugated and BC-corrugated are extracted respectively.Secondly,a BP neural network(GELU as the activation function)and a LightGBM(Light Gradient Boosting Machine)model are established to predict the production speed of the corrugated board line,and the hyperparameters of the two models are optimized by the Bayesian optimization and grid search respectively.The prediction results of the two models are combined by the grey wolf optimization algorithm(GWO).The results show that compared with the BPNN-XGBoost combined model the proposed method can significantly reduce prediction time while maintaining the same prediction accuracy,which greatly facilitates the online prediction of production speed in corrugated board lines.关键词
瓦楞纸板生产线/湿部生产速度/数据驱动建模/灰狼优化算法Key words
corrugated cardboard production line/wet end production speed/data-driven modeling/Grey Wolf Optimization algorithm分类
通用工业技术引用本文复制引用
黄淙琪,蒋勉,黄玮,谢威炜..一种瓦楞纸板生产线生产速度的智能预测方法[J].佛山科学技术学院学报（自然科学版）,2025,43(5):25-31,38,8.基金项目
广东省普通高校新一代信息技术重点领域专项项目(2021ZDZX1057) （2021ZDZX1057）
佛山市南海区重点领域科技攻关项目(2230032004654) （2230032004654）
