化工学报2018，Vol.69Issue(3)：998-1007,10.DOI:10.11949/j.issn.0438-1157.20170807
基于PCR-多案例融合的焦化烟气脱硝过程指标优化设定
PCR-multi-case fusion method for setting optimal process indices of coking flue gas denitration
摘要
Abstract
Due 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 NOxoutlet concentration within process specification, and greatly reduce power consumption of the equipment.关键词
炼焦烟气/脱硝/优化设定/案例推理/主成分回归Key words
coking flue gas/denitration/optimal setting/case-based reasoning/PCR分类
信息技术与安全科学引用本文复制引用
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):998-1007,10.基金项目
国家自然科学基金项目(U1701262) （U1701262）
2016年工信部智能制造试点示范项目(2016ZXFM06005).supported by the National Natural Science Foundation of China[U1701262]and the 2016 Intelligent Manufacturing Project of the Ministry of Industry and Information Technology of China(2016ZXFM06005). （2016ZXFM06005）
