Offline self-learning system for strip shape control efficiency coefficient of cold-rolling mill

Abstract

The invention relates to an offline self-learning system for a strip shape control efficiency coefficient of a cold-rolling mill. The offline self-learning system comprises an offline self-learning parameter setting module, a cold-rolling mill input-output process data reading module, a process data sequential processing module, a data-driven strip shape control function mechanism modeling module, a cold-rolling mill strip shape control efficiency coefficient computing module and a computed result evaluating and processing module which are sequentially connected, and the modules are used for preliminarily screening and sequentially processing data according to tension groups before rolling in the input-output process of the cold-rolling mill, building a data-driven strip shape control function mechanism model and an objective optimization function, and computing the cold-rolling mill strip shape control efficiency coefficient for minimizing the objective optimization function. The offline self-learning system provides an effective way which can be used for offline self-learning of the high-precision cold-rolling mill strip shape control efficiency coefficient, thereby solving the technical problems that strip shape control precision of a cold-rolled steel strip product is low, and even production accidents of strip breakage stop are caused in traditional cold-rolled steel strip production.

Description

technical field [0001] The invention relates to the field of cold-rolled steel strips, in particular to an off-line self-learning system for cold-rolling mill strip shape control efficiency coefficients. Background technique [0002] With the rapid development of the domestic equipment manufacturing industry, users of cold-rolled strip steel have higher and higher requirements for the shape quality of products, especially in high-end automobiles, IT industry and household appliances and other industries. Improving the shape quality of products has become one of the important ways for cold-rolled strip enterprises to improve economic benefits and core competitiveness. Cold-rolled strip shape control technology is a highly complex key technology that integrates multidisciplinary knowledge, involving professional knowledge of multiple disciplines such as process, equipment, hydraulic pressure, electrical control, and computer. Optimal design of functional modules. The cold-ro...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide an off-line self-learning system for the efficiency coefficient of cold rolling mill strip shape regulation, which can significantly improve the accuracy of the cold rolling mill strip shape regulation efficacy coefficient, and at the same time can well solve the problem of traditional cold rolling mill In strip steel production, due to the large deviation between the calculated value and the actual value of the flatness control efficiency coefficient of the cold rolling mill, applying the low-precision efficiency coefficient to the closed-loop flatness control system will cause the flatness control accuracy of cold-rolled strip products to Not high, or even the technical problem of belt breakage and shutdown production accidents

Images