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Article

Consistent Optimization of Blast Furnace Ironmaking Process Based on Controllability Assurance Soft Sensor Modeling

State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
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Author to whom correspondence should be addressed.
Sensors 2022, 22(12), 4526; https://doi.org/10.3390/s22124526
Submission received: 18 May 2022 / Revised: 5 June 2022 / Accepted: 9 June 2022 / Published: 15 June 2022
(This article belongs to the Section Industrial Sensors)

Abstract

The blast furnace ironmaking process is the core of steel manufacturing, and the optimization of this process can bring enormous economic and environmental benefits. However, previous data-driven optimization methods neglect the uncontrollability of part of the variables in the predictive modeling process, which brings great uncertainty to the optimization results and adversely affects the optimization effect. To address this problem, a consistency optimization framework based on controllability assurance soft sensor modeling is proposed. The method achieves the information extraction of uncontrollable variables in a process-supervised way, and improves the posterior distribution prediction accuracy. The method also proposes an integrated self-encoder regression module, which uses the regression to guide the encoding, realize the construction of latent features, and further improve the prediction accuracy of the model. Integrating the prediction module and the multi-objective gray wolf optimizer, the proposed model achieves the optimization of the blast furnace ironmaking process with only controllable variables as prediction model inputs while being capable of giving uncertainty estimates of the solutions. Empirical data validated the optimization model and demonstrated the effectiveness of the proposed algorithm.
Keywords: blast furnace; soft sensor; mixed density networks; consistency optimization blast furnace; soft sensor; mixed density networks; consistency optimization

Share and Cite

MDPI and ACS Style

Li, J.; Yang, C.; Yang, C. Consistent Optimization of Blast Furnace Ironmaking Process Based on Controllability Assurance Soft Sensor Modeling. Sensors 2022, 22, 4526. https://doi.org/10.3390/s22124526

AMA Style

Li J, Yang C, Yang C. Consistent Optimization of Blast Furnace Ironmaking Process Based on Controllability Assurance Soft Sensor Modeling. Sensors. 2022; 22(12):4526. https://doi.org/10.3390/s22124526

Chicago/Turabian Style

Li, Junfang, Chunjie Yang, and Chong Yang. 2022. "Consistent Optimization of Blast Furnace Ironmaking Process Based on Controllability Assurance Soft Sensor Modeling" Sensors 22, no. 12: 4526. https://doi.org/10.3390/s22124526

APA Style

Li, J., Yang, C., & Yang, C. (2022). Consistent Optimization of Blast Furnace Ironmaking Process Based on Controllability Assurance Soft Sensor Modeling. Sensors, 22(12), 4526. https://doi.org/10.3390/s22124526

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