Cold rolling flatness quality judgment method based on fuzzy algorithm

Abstract

The invention relates to a cold rolling flatness quality judgment method based on a fuzzy algorithm. The cold rolling flatness quality judgment method includes the following steps: secondary function fitting is carried out on single measurement residual data of a plate shape gauge, a monomial coefficient and a quadratic coefficient of a fitting function are determined, and characteristic values of middle waves and edge waves are demarcated; secondary function fitting is carried out on the one fourth position of the single measurement residual data of the plate shape gauge, a quadratic coefficient is determined, and a plate shape characteristic value of the one fourth position is demarcated; adjacent difference comparison most value obtaining processing is carried out on all channel values of the plate shape gauge, and a local plate shape characteristic value is determined; a strip steel overall length comprehensive plate shape characteristic matrix is calculated through fuzzy algorithm processing; through a weighting algorithm, plate shape quality grades are determined. By means of the cold rolling flatness quality judgment method, under the condition that complex wave shapes are considered, accurate judgment on the flatness of a cold rolling plate can be carried out, and the judgment level of the cold rolling flatness can be improved.

Description

Technical field: [0001] The invention relates to metallurgical automation and rolling technology, in particular to a method for judging the flatness quality of cold rolling based on a fuzzy algorithm. Background technique: [0002] With the rapid development of modern industrial technology, especially the continuous expansion of my country's automobile manufacturing, electromechanical equipment, high-precision instruments, and national defense industries, the demand for high-quality strip steel is increasing year by year. Because of its good mechanical properties and process properties, cold-rolled strips have always occupied an important market share and are widely used in various fields. Flatness, as an important measure to determine the quality of the strip, is a key indicator that steel manufacturers and market users pay attention to. However, due to many adverse factors affecting flatness, the wave-shaped generation parts can appear along the width direction of the stri...

AI Technical Summary

Problems solved by technology

Judging from the data that can be retrieved so far, no cold-rolled flatness evaluation method has been found that comprehensively considers the primary flatness, secondary flatness, high-order flatness, and local flatness, bright bands, ribbing and other influencing factors.

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