论文部分内容阅读
多效蒸发是重要的化工过程。目前,在实际生产中多效蒸发工序多采用离线浓度检测和人工手动控制,致使浓度的检测和控制严重滞后,影响了出口溶液的质量。本文根据氧化铝生产的多效蒸发过程特点,选取BP人工神经网络作为多效蒸发系统的建模方法,仿真结果显示,该模型可有效地对出口浓度进行预测。
Multi-effect evaporation is an important chemical process. At present, in the actual production of multi-effect evaporation process to use more off-line concentration detection and manual control, resulting in a serious lag in the detection and control of concentration, affecting the quality of the export solution. According to the characteristics of multi-effect evaporation process of alumina production, this paper selects BP artificial neural network as the modeling method of multi-effect evaporation system. The simulation results show that this model can effectively predict the outlet concentration.