Prediction for permeability index of blast furnace based on VMD–PSO–BP model

doi:10.1007/s42243-023-01097-y

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (0 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract The permeability index is one of the important production indicators to monitor the operation of blast furnace. It is crucial to grasp the trends of changes in the new permeability index in time. For the complex vibration spectrum of the permeability index, a prediction model of the permeability index based on the VMD–PSO–BP (variational mode decomposition–particle swarm optimization–back propagation) method was proposed. Firstly, the key factors that affect the permeability index of blast furnace were studied from multiple perspectives. Then, the permeability index was divided into multiple sub-modes based on the difference of frequency bands by the VMD algorithm, and a PSO–BP prediction model was established for each sub-mode. Finally, the prediction results of each sub-mode were summed to obtain the final one. The results show that the composite prediction accuracy by using the VMD algorithm is 3% higher than that of the traditional prediction method, which has better applicability.

Key words： Big data Blast furnace Air permeability Variational mode decomposition Particle swarm optimization Back propagation Model prediction

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Xiao-jie Liu
	Yu-jie Zhang
	Xin Li
	Zhi-feng Zhang
	Hong-yang Li
	Ran Liu
	Shu-jun Chen

Cite this article:

Xiao-jie Liu,Yu-jie Zhang,Xin Li, et al. Prediction for permeability index of blast furnace based on VMD–PSO–BP model[J]. Journal of Iron and Steel Research International, 2024, 31(3): 573-583.