Title: Intelligent integrated predictive model for BTP in lead-zinc sintering process

Authors: Chun-Sheng Wang, Min Wu

Addresses: School of Information Science and Engineering, Central South University, Changsha, Hunan 410083, China. ' School of Information Science and Engineering, Central South University, Changsha, Hunan 410083, China

Abstract: Based on the uncertainty of vertical burning speed and the abnormal sintering states in lead-zinc imperial sintering process, an intelligent integrated predictive model for burning through point (BTP) is proposed. First, a fuzzy T-S predictive model based on the character of piecewise linearity is established to deal with the uncertainty of vertical burning speed. Then, considering the sintering states may be abnormal, a fuzzy relation predictive model based on expert experience is also established. In the end, an integrated predictive model based on the fuzzy T-S predictive model and the fuzzy relation predictive model is presented by combining these two models with a fuzzy classifier. Results of numerical simulation show that the integrated predictive model is more accurate and robust against the uncertainty of vertical burning speed.

Keywords: lead zinc sintering process; LZSP; burning through point; BTP; fuzzy T-S predictive models; fuzzy relation predictive models; fuzzy classifiers; integrated predictive modelling; vertical burning speed; numerical simulation; uncertainty.

DOI: 10.1504/IJESMS.2010.035111

International Journal of Engineering Systems Modelling and Simulation, 2010 Vol.2 No.3, pp.162 - 168

Published online: 04 Sep 2010 *

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