Inverse Calculation of Burden Distribution Matrix Using B-spline Model Based PDF control in Blast Furnace Burden Charging Process

Journal Article · 07 March 2022 · IEEE Transactions on Industrial Informatics

DOI: https://doi.org/10.1109/tii.2022.3157641 · OSTI ID:1996731

Zhang, Yong ^[1]; Zhou, Ping ^[2]; Lv, Donghao ^[3]; Zhang, Sen ^[4]; Cui, Guimei ^[3]; Wang, Hong ^[5]

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1. Northeastern University, Shenyang (China); Inner Mongolia University of Science and Technology, Baotou (China)
2. Northeastern University, Shenyang (China)
3. Inner Mongolia University of Science and Technology, Baotou (China)
4. University of Science and Technology Beijing (China)
5. University of Manchester (United Kingdom); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

The inverse calculation of burden distribution matrix (BDM) is one of the most important challenges in the blast furnace operation in iron-making processes. In general, blast furnace consumes 65% of the total energy for the whole steel-making. Focusing on this practical challenge, this article proposes a new burden distribution spatial model in calculating burden charging process, and develops a B-spline approximation-based probability density function (PDF) control algorithm to assign the expected thickness distribution of burden layer and, thus, develops a new method for the required inverse calculation of BDM. First, a novel method for the thickness distribution of burden layer is given using B-spline model to produce an expected distribution shape subjected to a desired tracking within a specific spatial constraint. Then, according to the coexistence of continuous and bounded discrete variables in BDM, a novel hybrid optimization control method by combining integer programming and PDF tracking is further established for the effective inverse calculation of BDM. Finally, the proposed PDF-based iterative inverse calculation of BDM using B-spline models are tested using various data from industrial examples. Furthermore, the simulation results show that the proposed method is well suited to solve the BDM inverse calculation problem in practice.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: Liaoning Revitalization Talents Program; National Natural Science Foundation of China; Natural Science Foundation of Inner Mongolia; USDOE
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 1996731
• Journal Information: IEEE Transactions on Industrial Informatics, Journal Name: IEEE Transactions on Industrial Informatics Journal Issue: 1 Vol. 19; ISSN 1551-3203
• Publisher: IEEECopyright Statement
• Country of Publication: United States
• Language: English