Rough case-based reasoning system for continues casting

Wenbin Su; Zhufeng Lei

doi:10.1117/12.2309438

13 April 2018 Rough case-based reasoning system for continues casting

Wenbin Su, Zhufeng Lei

Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106962F (2018) https://doi.org/10.1117/12.2309438
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria

Abstract

The continuous casting occupies a pivotal position in the iron and steel industry. The rough set theory and the CBR (case based reasoning, CBR) were combined in the research and implementation for the quality assurance of continuous casting billet to improve the efficiency and accuracy in determining the processing parameters. According to the continuous casting case, the object-oriented method was applied to express the continuous casting cases. The weights of the attributes were calculated by the algorithm which was based on the rough set theory and the retrieval mechanism for the continuous casting cases was designed. Some cases were adopted to test the retrieval mechanism, by analyzing the results, the law of the influence of the retrieval attributes on determining the processing parameters was revealed. A comprehensive evaluation model was established by using the attribute recognition theory. According to the features of the defects, different methods were adopted to describe the quality condition of the continuous casting billet. By using the system, the knowledge was not only inherited but also applied to adjust the processing parameters through the case based reasoning method as to assure the quality of the continuous casting and improve the intelligent level of the continuous casting.

Citation Download Citation

Wenbin Su and Zhufeng Lei "Rough case-based reasoning system for continues casting", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106962F (13 April 2018); https://doi.org/10.1117/12.2309438

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