Applying BP Neural Network Model to Forecast the Largest Coiling Torque of down Coilers

Abstract:

Down coiler is an important equipment of hot rolling mill. The coiling torque is changing constantly in the process of strip steel coiling, and the largest coiling torque depends on several factors, such as the material and specification of coiling strip, the coiling temperature and the process parameters and so on. Only when the largest coiling torque is less than the carrying capacity could the coiler work in security. A topology relationship of the largest coiling torque among the materials, the specification of the strip and the coiling temperature is established. Based on the BP(backward propagation of errors) artificial neural network, a predicted formula model of the largest coiling torque in coiling high strength strip is built, which provides a theoretical basis for the development and utilization of the largest working potential of the down coiler. Keywords: Down Coiler; BP Neural Network; Coiling Torque; Forecast

• Periodical: Advanced Materials Research (Volume 936)
• Pages: 1614-1619
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.936.1614
• Online since: June 2014
• Authors: Ke Zhao, Zhi Gang Wang*, Chang Ming Liu
• Keywords: BP Neural Network (BPNN), Coiling Torque, Down Coiler, Forecast

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