An intelligent decision-making strategy based on the forecast of abnormal operating mode for iron ore sintering process. (December 2020)
- Record Type:
- Journal Article
- Title:
- An intelligent decision-making strategy based on the forecast of abnormal operating mode for iron ore sintering process. (December 2020)
- Main Title:
- An intelligent decision-making strategy based on the forecast of abnormal operating mode for iron ore sintering process
- Authors:
- Du, Sheng
Wu, Min
Chen, Luefeng
Cao, Weihua
Pedrycz, Witold - Abstract:
- Abstract: The abnormal operating mode of the iron ore sintering process will produce sinter ore with low yield and poor quality. It is of high economic value to ensure that the sintering process runs under normal operating mode. An intelligent decision-making strategy based on the forecast of the abnormal operating mode for the iron ore sintering process is presented in this paper. First, a fuzzy rule-based model is used to construct the forecast model of operating mode, of which inputs are selected by the one-way analysis of variance. Then, an intelligent decision-making strategy for operating parameters is proposed based on the priority. Finally, experiments are performed by using the actual running data collecting from the industrial site. The originality of this study comes with establishing a fuzzy rule-based model to forecast the operating mode and designing an intelligent decision-making strategy based on priority to improve the abnormal operating mode. The result shows that the constructed forecast model of operating mode forecasts well in abnormal operating mode. The proposed intelligent decision-making strategy can effectively improve abnormal operating mode, which has a good application prospect in the iron ore sintering process. Highlights: An intelligent decision-making framework based on the forecast of abnormal operating mode is designed. A fuzzy rule-based model is used to build the forecast model of operating mode. An intelligent decision-making strategy ofAbstract: The abnormal operating mode of the iron ore sintering process will produce sinter ore with low yield and poor quality. It is of high economic value to ensure that the sintering process runs under normal operating mode. An intelligent decision-making strategy based on the forecast of the abnormal operating mode for the iron ore sintering process is presented in this paper. First, a fuzzy rule-based model is used to construct the forecast model of operating mode, of which inputs are selected by the one-way analysis of variance. Then, an intelligent decision-making strategy for operating parameters is proposed based on the priority. Finally, experiments are performed by using the actual running data collecting from the industrial site. The originality of this study comes with establishing a fuzzy rule-based model to forecast the operating mode and designing an intelligent decision-making strategy based on priority to improve the abnormal operating mode. The result shows that the constructed forecast model of operating mode forecasts well in abnormal operating mode. The proposed intelligent decision-making strategy can effectively improve abnormal operating mode, which has a good application prospect in the iron ore sintering process. Highlights: An intelligent decision-making framework based on the forecast of abnormal operating mode is designed. A fuzzy rule-based model is used to build the forecast model of operating mode. An intelligent decision-making strategy of operating parameters based on priority is proposed. … (more)
- Is Part Of:
- Journal of process control. Volume 96(2020)
- Journal:
- Journal of process control
- Issue:
- Volume 96(2020)
- Issue Display:
- Volume 96, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 96
- Issue:
- 2020
- Issue Sort Value:
- 2020-0096-2020-0000
- Page Start:
- 57
- Page End:
- 66
- Publication Date:
- 2020-12
- Subjects:
- Abnormal operating mode -- Fuzzy rule-based model -- Intelligent decision-making -- Sintering process
Process control -- Periodicals
Fabrication -- Contrôle -- Périodiques
Process control
Periodicals
Electronic journals
660.281 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09591524 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jprocont.2020.11.001 ↗
- Languages:
- English
- ISSNs:
- 0959-1524
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5042.645000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14929.xml