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基于PCR-多案例融合的焦化烟气脱硝过程指标优化设定
李亚宁1,2; 王学雷1; 谭杰1
Source Publication化工学报
2018-03
Volume69Issue:3Pages:998-1007
Other AbstractDue to complex process mechanism, frequently changeable inlet flue gas indices induced by upstream coking conditions, and severe interference of process unknowns, it is difficult to determine process indices by traditional exact mathematical models for the first domestic coking flue gas desulfurization and denitration integrated unit. A case-based reasoning method was proposed to optimize indices of the coking flue gas denitration process. Meanwhile, abrupt change of some correlation description indices, which was caused by coke oven reversion, may lead to deviation from results because single feature was used to describe current working condition in traditional case reuse method. A case retrieval and reuse method was further proposed from principal component regression multiple case fusion. The results of numerical simulation and application in the coking plant show that this method can appropriately obtain operating parameter settings at different characteristic conditions, effectively control NOx outlet concentration within process specification, and greatly reduce power consumption of the equipment.
Keyword炼焦烟气 脱硝 优化设定 案例推理 主成分回归
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21179
Collection综合信息系统研究中心
Affiliation1.中国科学院自动化研究所
2.中国科学院大学
Recommended Citation
GB/T 7714
李亚宁,王学雷,谭杰. 基于PCR-多案例融合的焦化烟气脱硝过程指标优化设定[J]. 化工学报,2018,69(3):998-1007.
APA 李亚宁,王学雷,&谭杰.(2018).基于PCR-多案例融合的焦化烟气脱硝过程指标优化设定.化工学报,69(3),998-1007.
MLA 李亚宁,et al."基于PCR-多案例融合的焦化烟气脱硝过程指标优化设定".化工学报 69.3(2018):998-1007.
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