摘要
针对置换蒸煮过程中卡伯值难以在线检测、引起操作延时、导致纸浆品质下降和能耗增大的问题,研究了基于数据驱动的置换蒸煮卡伯值在线预测方法。在分析置换蒸煮过程特点的基础上,提出了基于数据驱动的置换蒸煮卡伯值在线预测框架,给出了模式匹配的优化算法,设计了基于数据驱动的卡伯值在线预测模型。仿真结果和实际生产应用证明了该方法的有效性。
Aiming to the difficulty of Kappa value online measurement in displacement cooking, this paper proposed a data-driven method to online predict Kappa value in displacement cooking. Based on the analysis of the features of displacement cooking process, an online prediction frame of Kappa value in displacement cooking based on data-driven was proposed, a pattern-matching optimization calculation was pres-ented and a model of data-driven Kappa value online prediction was designed. The results of simulation and production application confirmed the effectiveness of the method.
出处
《中国造纸》
CAS
北大核心
2016年第12期31-36,共6页
China Pulp & Paper
基金
国家国际科技合作项目(2010DFB43660)
陕西省科技厅国际科技合作项目(2011KW-11(2))
咸阳市科技研究项目(2014k03-05)
关键词
数据驱动
置换蒸煮
卡伯值
操作模式优化
模糊神经网络
data-driven
displacement cooking
Kappa value
optimization of operation mode
fuzzy neural network
