摘要
干气制乙苯反应器在生产过程中催化剂不断失活,为了使产品质量满足要求,需要不断调解反应器温度,保证催化剂的活性。本文利用现场生产数据,采用基于遗传算法的人工神经网络对干气制乙苯反应器温度进行模拟预测,仿真结果显示模型准确度高,运行速度快,此项技术应用前景广阔,能够对企业的生产管理带来很好的收益。
Deactivation of catalyst in dry gas-to-ethylbenzene reactor often occurs during the production process.In order to make the product quality meet our requirements,temperature in the reactor need to be constantly adjusted to enhance activity of the catalyst.In this paper,according to production data,prediction model for reaction temperature in the dry gas-to-ethylbenzene reactor was established by using genetic algorithm-artificial neural network（ANN）.The results show that the model can accurately predict temperature in dry gas-to-ethylbenzene reactor,and its running speed is very fast.This technology has well application prospect and can bring distinct profit for enterprises.
出处
《辽宁化工》
CAS
2011年第4期391-394,共4页
Liaoning Chemical Industry
关键词
干气制乙苯
BP
遗传算法
优化
Dry gas-to-ethylbenzene reactor
BP network model
Genetic algorithm
Optimization
