摘要
介绍了采用神经网络模型对催化裂化分馏塔的产品质量进行在线预测分析,采用模糊推理的方法,开发基于网络环境下实时在线的故障诊断专家系统。这两种技术相结合,克服了各自的缺陷,实现了优势互补。结果表明该模型具有较高的精度,与化验值的拟合程度较好,给予了在线操作指导,减少质量事故,提高经济效益。
The online estimation of FCC oil product qualities is realized by BP neural network and the real time faults in the FCC fractional column is diagnosed by fuzzy theory.The combinations both fuzzy diagnosis and BP neural network make them overcome disadvantages and realize the combination of strong points.The results have been accurately proved by the experiments.The model can give online guiding operations,decrease quality accidents and increase economic profit.
出处
《石油化工自动化》
CAS
2004年第5期37-41,共5页
Automation in Petro-chemical Industry
基金
天津市科技发展计划项目(993109511)
天津市科学技术成果(津20040002)