Hot-rolled strip steel plate convexity prediction method based on deep learning

Abstract

The invention discloses a hot-rolled strip steel plate convexity prediction method based on deep learning, and the method comprises the following steps: S1, collecting and recording strip steel production data, and carrying out the preprocessing, including missing value deletion, abnormal value deletion and normalization, of the collected data; S2, according to the strip steel production data, removing redundant and irrelevant attributes in the collected data through an attribute selection method based on a Morita index, and screening a minimum number of attributes capable of representing plate convexity changes to form an input variable set of a forecasting model; and S3, establishing a strip steel outlet plate convexity prediction model based on the deep and wide convolutional neural network based on the input variable set so as to obtain the hot rolled strip steel outlet plate convexity. According to the method, high-order features and invariant features of the data are extracted byusing the convolutional layer in the convolutional neural network, the local correlation between the variables is learned, and the global feature learning ability of the deep neural network is combined, so that the plate convexity prediction precision is remarkably improved.

Description

technical field [0001] The invention relates to a method for predicting the crown of a hot-rolled strip steel plate based on deep learning, which belongs to the field of metallurgy. Background technique [0002] The iron and steel industry is a pillar industry for national production and social development. Among iron and steel products, strip steel is known as general-purpose steel. It is an important basic material for high-end products and is widely used in construction, transportation, national defense and other fields. With the continuous improvement of the manufacturing industry, the demand for high-precision plates and strips has increased sharply, and the requirements for the dimensional accuracy of plates and strips have become more stringent. As an intermediate step in strip rolling, hot rolling has a significant impact on the product quality of downstream processes such as cold rolling. Therefore, it is of great significance to achieve precise control of hot-rolle...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a method for predicting the crown of hot-rolled strip steel plate based on deep learning, which can effectively solve the problems in the prior art, especially using traditional machine learning and deep learning models for prediction, the model The problem of low forecasting accuracy and generalization ability

Images