Online temperature estimation of Shell coal gasification process based on extended Kalman filter
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Online temperature estimation of Shell coal gasification process based on extended Kalman filter
Online temperature estimation of Shell coal gasification process based on extended Kalman filter
中国化学工程学报(英文版)2022年47卷第7期 页码:134-144
Affiliations:
1. Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University,Beijing,China,100084
2. School of Engineering, Merz Court, Newcastle University, Newcastle upon Tyne NE1 7RU, United Kingdom
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纸质出版:2022
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Kangcheng Wang, Jie Zhang, Dexian Huang. Online temperature estimation of Shell coal gasification process based on extended Kalman filter[J]. 中国化学工程学报(英文版), 2022,47(7):134-144.
Kangcheng Wang, Jie Zhang, Dexian Huang. Online temperature estimation of Shell coal gasification process based on extended Kalman filter[J]. Chinese Journal of Chemical Engineering, 2022, 47(7): 134-144.
Kangcheng Wang, Jie Zhang, Dexian Huang. Online temperature estimation of Shell coal gasification process based on extended Kalman filter[J]. 中国化学工程学报(英文版), 2022,47(7):134-144.DOI:
Kangcheng Wang, Jie Zhang, Dexian Huang. Online temperature estimation of Shell coal gasification process based on extended Kalman filter[J]. Chinese Journal of Chemical Engineering, 2022, 47(7): 134-144.DOI:
Online temperature estimation of Shell coal gasification process based on extended Kalman filter
Obtaining the temperature inside the gasifier of a Shell coal gasification process (SCGP) in real-time is very important for safe process operation. However
this temperature cannot be measured directly due to the harsh operating condition. Estimating this temperature using the extended Kalman filter (EKF) based on a simplified mechanistic model is proposed in this paper. The gasifier is partitioned into three zones. The quench pipe and the transfer duct are seen as two additional zones. A simplified mechanistic model is developed in each zone and formulated as a state-space representation. The temperature in each zone is estimated by the EKF in real-time. The proposed method is applied to an industrial SCGP and the effectiveness of the estimated temperatures is verified by a process variable both qualitatively and quantitatively. The prediction capability of the simplified mechanistic model is validated. The effectiveness of the proposed method is further verified by comparing it to a Kalman filter-based single-zone temperature estimation method.
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相关作者
Yu Fan
Liang-Zhi Qiao
Shan-Jing Yao
Dong-Qiang Lin
Jianliang Xu
Qinfeng Liang
Zhenghua Dai
Xiaolei Guo
相关机构
Key Laboratory of Biomass Chemical Engineering of Ministry of Education, Zhejiang Key Laboratory of Smart Biomaterials, College of Chemical and Biological Engineering, Zhejiang University
Shanghai Engineering Research Center of Coal Gasification, East China University of Science and Technology