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ID 48874
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Methods of Diagnosis and Intervention for Agent of Hot Rolling Operation Support
Author
Konishi, Masami
Nakano, Koichi
Abstract
In the last two decades, it becomes possible to automate operations of various steel plants especially in rolling mills. As the results, stabilization of productivity and improvement of product quality have been attained. On the while, in these years, many skilled engineers and operators who actively promoted economical growth of steel industries will retire due to their age limits. Thus, the inheritance of the high level technology and know-how has becomes a serious problem. To overcome the problem, it is necessary to extract knowledge of the skilled persons and make technical textbook reducing tacit knowledge. In this paper, rules are extracted from the operation data of hot strip rolling applicable to the operation diagnosis and intervention during operation. To attain the object, agent based simulator of hot strip rolling has been developed to prepare various rolling data for extraction of diagnosis and intervention rules in rolling operations. As for the selection of normal and abnormal data, SVM algorithm is tested before rules extraction. Rules are written in Fuzzy logic forms and its parameters are optimized by GA algorithm. These technologies are involved in the operation support agent system of hot strip rolling mills together with RNN for automatic gain tuning of mill controller.
Keywords
diagnosis
agent system
human intervention
hot strip rolling
rule extraction
genetic algorithm
support vector machine
Published Date
2011-06-01
Publication Title
鉄と鋼
Publication Title Alternative
Tetsu-to-Hagané
Volume
volume97
Issue
issue6
Publisher
社団法人 日本鉄鋼協会
Start Page
326
End Page
333
ISSN
0021-1575
Content Type
Journal Article
Official Url
http://dx.doi.org/10.2355/tetsutohagane.97.326
language
日本語
Copyright Holders
Copyright © 2011 社団法人 日本鉄鋼協会
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publisher
Refereed
True
DOI