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Author Abe, Y. ♦ Konishi, M. ♦ Imai, J.
Sponsorship IEEE ♦ ICIC Int. ♦ National Natural Sci. Found. of China ♦ Beijing Jiaotong Univ. ♦ Kaosiung Univ. of Appl. Sci
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2006
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Strips ♦ Recurrent neural networks ♦ Parameter estimation ♦ Three-term control ♦ Neural networks ♦ Humans ♦ Automatic control ♦ Control systems ♦ Electrical equipment industry ♦ Milling machines
Abstract In this study, NN based diagnostic system for hot strip mills with looper controller are proposed. Recurrent neural network (RNN) is employed to decide presetting of looper control gains. During elapse of time, deterioration of mechanical characteristics is induced together with that of the control system. To overcome the problem, it is required to diagnose true failure cause and to compensate it. For the purpose, the hierarchical neural network (HNN) is applied. HNN model which enables compensation to the deterioration of mill system can estimate current system parameters such as control gains and mill constants. Through numerical experiments, the effect of the proposed method is ascertained
Description Author affiliation: Graduate Sch. of Natural Sci. & Technol., Okayama Univ. (Abe, Y.; Konishi, M.; Imai, J.)
ISBN 0769526160
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2006-08-30
Publisher Place China
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 181.31 kB
Page Count 4
Starting Page 415
Ending Page 418


Source: IEEE Xplore Digital Library