Reliable Roll Force Prediction in Cold Mill Using Multiple Neural Networks  

Oleh:

Cho, Sungzoon ; Cho, Yongjung ; Yoon, Sungchul

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 8 no. 4 (1997), page 874-882.
Topik: Prediction; roll force; prediction; cold mill; multiple; neural networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

The cold rolling mill process in steel works uses stands of rolls to flatten a strip to a desired thickness. The accurate prediction of roll force is essential for product quality. Currently, a suboptimal mathematical model is used. We trained two multilayer perceptrons, one to directly predict the roll force and the other to compute a corrective coefficient to be multiplied to the prediction made by the mathematical model. Both networks were shown to improve the accuracy by 30 - 50 %. Combining the two networks and the mathematical model results in systems with an improved reliability.

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