Rolling Force Models of Cold Tandem Rolling Mill Based on Genetic Neural Networks

ZHANG Dazhi; CHENG Bingxiang; LI Mouwei; SUN Yikang; GUAN Kezhi

doi:10.13374/j.issn1001-053x.2000.04.058

Volume 22 Issue 4

Aug. 2021

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Article Navigation > Chinese Journal of Engineering > 2000 > 22(4): 384-388

ZHANG Dazhi, CHENG Bingxiang, LI Mouwei, SUN Yikang, GUAN Kezhi. Rolling Force Models of Cold Tandem Rolling Mill Based on Genetic Neural Networks[J]. Chinese Journal of Engineering, 2000, 22(4): 384-388. doi: 10.13374/j.issn1001-053x.2000.04.058

Citation:

ZHANG Dazhi, CHENG Bingxiang, LI Mouwei, SUN Yikang, GUAN Kezhi. Rolling Force Models of Cold Tandem Rolling Mill Based on Genetic Neural Networks[J]. Chinese Journal of Engineering, 2000, 22(4): 384-388. doi: 10.13374/j.issn1001-053x.2000.04.058

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Rolling Force Models of Cold Tandem Rolling Mill Based on Genetic Neural Networks

doi: 10.13374/j.issn1001-053x.2000.04.058

1. National Engineering Research Center for Advanced Rolling Technology, UST Beijing, Beijing 100083, China;
2. Information Engineering School, UST Beijing;
3. Mechanical Engineerin School, UST Beiji

Received Date: 1999-11-18
Available Online: 2021-08-27

Abstract

Abstract

Some defects of the traditional rolling force models of cold tandem rolling mill were found out, and new rolling force models based on genetic neural networks were set up. The comparison results of the measured rolling force of cold tandem rolling mill with the calculated value from the traditional models and also with the calculated value from the new rolling force models based on genetic neural netWothe show thatthe calculating precision of the new models is better than that of the traditional models.
- genetic algorithms,
- BP algorithms,
- neural networks,
- rolling force models