Cold-rolling mathematical model-based power consumption prediction method for combined pickling-cold rolling unit

Abstract

The invention provides a cold-rolling mathematical model-based power consumption prediction method for a combined pickling-cold rolling unit and belongs to the technical field of steel rolling. The method comprises five parts, namely torque prediction, rolling mill power consumption prediction, coiler power consumption prediction, other common auxiliary equipment power consumption prediction and model self-learning, and comprises the following specific processes of (1) calculating rolling torque, tension torque and loss torque of various racks on the basis of a cold-rolling mathematical model;(2) calculating power consumption of various racks according to the calculated torque parameters; (3) calculating power consumption of a coiler according to the coiling turns of the coiler and corresponding radiuses; (4) predicting power consumption of common auxiliary equipment of strip steel through counting historical data; and (5) correcting adaptation coefficients of the model according to the measured data and improving the prediction accuracy of the model. Through the method provided by the invention, the power consumption of each strip steel in the whole production of the combined pickling-cold rolling unit in a rolling plan can be predicted in advance, and the method is of great significance to peak shifting production and cost reduction of iron and steel enterprises.

Description

technical field [0001] The invention relates to the technical field of steel rolling, in particular to a method for predicting electric energy consumption of a combined acid rolling unit based on a cold rolling mathematical model. Background technique [0002] As we all know, cold-rolled products are closer to consumers and are widely used in household appliances, automobiles, electronics and other fields. Therefore, the quality of cold-rolled products is related to the life and death of an enterprise. However, with the continuous advancement of technology in various steel mills, the competition among peers has become increasingly fierce, and the profit margin has gradually declined. Therefore, the control of production costs has gradually been raised to an equally important position. In the production line of combined acid-rolling unit, energy consumption is the main part of production cost. The price of industrial electricity varies with different peak periods of electrici...

AI Technical Summary

Problems solved by technology

Patent 1 (Rolling schedule optimization method aimed at controlling power consumption per ton of steel in the cold tandem rolling process, 201510725285.X) uses an iterative algorithm to find the reduction rate and tension of the rolling mill that minimize energy consumption. This patent has the following deficiencies: 1 ) only considered the power consumption of the rolling mill; 2) did not predict the power consumption, and could not guide the site to flexibly adjust the production plan; 3) assumed that the exit speed of the final stand remained unchanged during the strip rolling process, and the rolling mill speed up and down in actual production , the high speed may be 30 times that of the low speed; 4) The model has not been self-learning, and the accuracy and adaptability of the model cannot be guaranteed

[0004] Judging from the currently available data, no method has been found that can accurately predict the power consumption of rolling mills

Images