Intelligent control of sintering mixture moisture based on RBF model of permeability

Guo Li, Guang Ming Zhang, Xiang Ling

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The process of lead-zinc sintering presents nonlinear, time-varying and strong coupling characteristics. Sintering mixture granulation water is an important part of lead-zinc smelting. By analysis mechanism and the relativity of technology parameters, the RBF neural network model of permeability is developed. Combining with the synthesize estimation model of permeability, an intelligent control method of sintering mixture moisture based on permeability is established. The model then further optimized through intelligent search algorithm. Thereby controlling the granulation mixture moisture to improve permeability. Simulation results show the proposed model could achieve better results. It could improve the quality and yield of sintering production.

Original languageEnglish
Title of host publicationIndustrial Design and Mechanics Power II
Pages686-689
Number of pages4
DOIs
StatePublished - 2013
Event2nd International Conference on Industrial Design and Mechanics Power, ICIDMP 2013 - Nanjing, China
Duration: 24 Aug 201325 Aug 2013

Publication series

NameApplied Mechanics and Materials
Volume437
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference2nd International Conference on Industrial Design and Mechanics Power, ICIDMP 2013
Country/TerritoryChina
CityNanjing
Period24/08/1325/08/13

Keywords

  • Intelligent control
  • Moisture
  • Permeability
  • RBF
  • Sintering

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