摘要
工业上,一般采用间歇精馏提纯桃醛,为了提高工艺的综合效益,需要对间歇精馏过程进行多目标综合优化。首先通过对体系简化方法的讨论,然后建立Aspen模型,经过工业生产验证后,均匀设计安排试验方案并进行模型模拟,利用DPS数据处理系统对模拟数据进行二次多项式拟合,得到数学模型并预报最优操作参数,使多目标达到综合优化。通过优化研究,桃醛单釜收率为59.35%,操作时间30.1 h,相比于验证模型生产结果而言,收率提高了7.13%,操作时间缩短了2.9 h,达到了综合优化的效果,给企业生产带来一定的增效,为今后工业间歇精馏优化提供一种思路。
Peach aldehyde was purified by batch distillation in industry. In order to improve the comprehensive benefits of the process, it is necessary to optimize the batch distillation process. In this paper, wefirst discussed the method of system simplification,then set up Aspen model. After the verification of industrial production, the uniform design was arranged and corresponding model was simulated. To get the mathematical model and the prediction of optimal operation parameters, data was simulated by DPS data processing system, which can achieve the best target optimization. Through optimization study, the yield of peach aldehyde in a single batch was 59.35% and operation time was 30.1 h. Compared to the results of production model, the yield was increased by 7.13%, the operation time was reduced by 2.9 h. It meant that the comprehensive optimization was reached, it could bring efficiency for industrial production and provide a way for further industrial optimization to batch distillation.
出处
《香料香精化妆品》
CAS
2017年第4期1-5,共5页
Flavour Fragrance Cosmetics
关键词
间歇精馏
桃醛生产
多目标优化
均匀设计
Aspen模型
数学模型
batch distillation
peach aldehyde production
multi-objective optimization
uniform design
Aspen model
mathematical model