Method for recognizing signal mode of cold-rolled strip

Abstract

Provided is a method for recognizing a signal mode of a cold-rolled strip. The method comprises the following steps that the plate shape measurement values, measured by a plate shape instrument on line, of all measurement sections in the width direction of the cold-rolled strip are acquired, and the plate shape values of all the measurement sections are obtained; original data output by the plate shape instrument are input into a n-layer neural network and used as a feature extraction layer, and the network is made to extract the feature automatically through training for eliminating the trace of artificial use; and plate shape recognition is conducted through the improved quantum neural network based on a genetic algorithm. According to the method, the improved quantum neural network of a multi-layer excitation function optimized through the genetic algorithm is applied to a plate shape mode recognition technology, the training efficiency of the network is improved remarkably, and the problems that the precision and the real-time performance are not ideal, the network structure is complex, the training time is long, and the stability and robustness are poor by means of a traditional plate shape recognition method are solved effectively.

Description

technical field [0001] The invention belongs to the field of cold-rolled strips and relates to a method for identifying signal patterns of cold-rolled strips. Background technique [0002] In the production process of cold-rolled strips, the pattern recognition of cold-rolled strip shape is an important part of the cold-rolled strip shape control system. In this link, the recognition accuracy of the flatness defect state is crucial to the subsequent flatness control effect. role. The stress signal data in the plate on the production site is collected by the shape meter for identification, and the type of the current shape defect state is judged, and fed back to the shape control mechanism, and the defect degree of the shape is reduced by controlling the adjustment of the actuator, and finally To make the output of the shape meet the production standard of the process, it is necessary to seek and study the identification method of the high-precision shape defect mode. [00...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to provide a method for signal pattern recognition of cold-rolled strips, which can effectively solve the problems of insufficient accuracy and real-time performance encountered in traditional flatness pattern recognition methods, complex identification model structure and too long network training time , poor stability and other technical problems can provide a reliable control basis for the control system and provide a strong guarantee for improving the quality of cold-rolled strip shape control

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