Intelligent integrated coking flue gas indices prediction
文献类型：会议论文
| 作者 | Li YN(李亚宁)1,2 ; Wang XL1; Tan J1; Liu CB1,2; Bai XW1,2
|
| 出版日期 | 2017-06 |
| 会议日期 | 26-28 June 2017 |
| 会议地点 | Kanazawa |
| 关键词 | Coking Flue Gas Mechanism Model Neural Networks Integrated Modeling |
| 页码 | 39-45 |
| 英文摘要 | Focus on the first China domestic coking flue gas desulfurization and denitriation integrated device, in order to solve the problem that the entrance parameters fluctuate and a detection lag exists due to the upstream coking workshop, which is extremely unfavorable to the optimal control of desulfurization and denitriation process. An intelligent integrated prediction model of flue gas SO2 concentration, O2 content and NOx concentration was proposed: the mechanism models of SO2, NOx concentration and O2 content were established according to the principle of material balance and reaction kinetics, respectively. For the prediction error, raw data was pretreated and the auxiliary variables were determined by principal component analysis, in order to improve the training speed and generalization ability of neural network, an improved RBFNN combining optimal stopping principle and dual momentum adaptive learning rate was proposed and used to compensate the error. Based on the practical data of two 55-hole and 6-meter top charging coke ovens in the coking group, the effectiveness and superiority of proposed model and method were verified by simulation via comparison of various models. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/21182]  |
| 专题 | 综合信息系统研究中心_工业智能技术与系统 |
| 作者单位 | 1.中国科学院自动化研究所 2.中国科学院大学 |
| 推荐引用方式 GB/T 7714 | Li YN,Wang XL,Tan J,et al. Intelligent integrated coking flue gas indices prediction[C]. 见:. Kanazawa. 26-28 June 2017. |
入库方式： OAI收割
来源：自动化研究所
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