Intelligent setting method for on-line target strip shape of cold rolling strip

Abstract

The invention discloses an intelligent setting method for the on-line target strip shape of a cold rolling strip. The intelligent setting method comprises the following steps that a strip shape curve is divided into an original strip shape detection curve, a technology error strip shape compensation curve and a target strip shape curve, wherein the original strip shape detection curve and the technology error strip shape compensation curve are overlaid to form an effective actually-measured strip shape curve which is called the effective strip shape curve for short, and the target strip shape curve only needs to consider a strip shape control target for the follow-up process requirement; an on-line strip shape target curve is built on the basis of a quartic Legendre polynomial, the self-balanced constraint condition requirement (that is, the transverse integration in the width direction of the strip is zero) of the residual stress deviation of the rolled strip in the width direction of the strip is met, the target is clear, and the function is explicit; and a target strip shape standard curve library is built on the basis of an intelligent algorithm, the optimal parameter of the on-line target strip shape is obtained, and the control precision of the strip shape is ensured.

Description

technical field [0001] The present invention relates to the field of automatic measurement of rolling strip machinery and equipment, in particular to an intelligent setting method for on-line target shape of cold-rolled strip, the method is suitable for cold-rolled strip, aluminum strip, copper strip and other strip products Shape control target. Background technique [0002] With the rapid development of rolling theory and steel rolling technology, the strip tends to be wider and thinner. Therefore, the flatness problem is becoming more and more prominent and complex, and the research on flatness control theory and regulation technology is constantly updated and improved. . The key to flatness closed-loop control lies in the real-time detection of high-sensitivity online flatness signals, the target flatness curve considering actual working conditions, and a stable and reliable high-precision flatness control model. The original flatness signal is the basis and premise, an...

AI Technical Summary

Problems solved by technology

Obviously, these two methods will cause a series of problems in the actual application process, and it is easy to cause the strip with good online shape to show different degrees of shape defects after off-line unloading

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