Continuous casting slab quality prediction method based on extreme learning machine

Abstract

The invention provides a continuous casting slab quality prediction method based on an extreme learning machine, and belongs to the technical field of ferrous metallurgy. The method comprises the following steps: firstly, collecting data related to actual production of the continuous casting billet, finding out influence factors influencing the quality of the continuous casting billet, then preprocessing selected sample data, determining the number of input nodes and the number of output nodes counted by an extreme learning machine according to the data, and finally calculating the quality of the continuous casting billet. And inputting the training data set into an extreme learning machine to complete training of the extreme learning machine, and finally inputting residual sample data to complete defect grade classification of the quality of the continuous casting billet. The method is high in training speed, high in prediction precision and good in adaptability, compared with a continuous casting slab quality prediction model based on a statistical method, an expert system, a BP neural network and the like, the prediction precision and the operation speed are obviously improved, and then the quality of the continuous casting slab can be timely and accurately judged.

Description

[0001] This application is a divisional application of a patent application entitled "A Method for Predicting the Quality of Continuous Casting Slabs Based on Extreme Learning Machine". The original application date is February 5, 2018, and the application number is 201810109564.7. technical field [0002] The invention relates to the technical field of iron and steel metallurgy, in particular to a continuous casting slab quality prediction method based on an extreme learning machine. Background technique [0003] In recent decades, with the rapid development of iron and steel enterprises, the technology of hot charging, hot delivery and direct rolling of continuous casting slabs has made continuous steel casting the most active research field in iron and steel enterprises. The development of this technology not only greatly reduces the The production cost and equipment input are reduced, and the competitiveness of the product is improved. However, the current continuous cas...

AI Technical Summary

Problems solved by technology

However, the model based on this method consumes a lot of time in the training process, is easy to fall into the local optimal value, and needs to set a large number of network training parameters during the training process, and the prediction accuracy is low, so it is difficult to quickly and timely evaluate the quality of continuous casting slabs in iron and steel enterprises. Accurate judgment is not conducive to the efficient production of high-quality steel in iron and steel enterprises

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