Abstract

Coiling temperature of hot rolled strip is one of the important parameters which affect performances of hot rolled strip. The control of coiling temperature is highly nonlinear and time-varying. Based on the laminar cooling control system of a hot rolling plant, a coiling temperature prediction model based on BP neural network was established. Many factors which affect coiling temperature control were taken into account, and the BP neural network was trained by actual production data. The simulation was carried out, which indicates that coiling temperature can be predicted precisely, and the BP neural network model has the prospect of online application.

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