A visual analysis method for continuous casting crystallizer temperature field

Abstract

The invention relates to a visualized analysis method for the temperature field of a continuous casting crystallizer. According to the visualized analysis method, randomly visual temperature monitoring for the internal temperature field of the crystallizer is realized via a fuzzy control method of the neural network. Temperature data signals are collected by a temperature collection system in a PC, filtered, and then sent to a data analysis and knowledge inference module in a data analysis system via a communication system; the data analysis and knowledge inference module establishes a differential temperature field model according to the received data, and analyzes the collected temperature data based on the fuzzy control method of the neural network; and visualized analysis is carried out on the casting process and the temperature field of the crystallizer. The visualized analysis method provides importance means of controlling the casting production condition and improving the surface quality of steel, full-time, dynamic and visualized analysis on the temperature distribution of the crystallizer can be realized in the system, full-flow visualization in the aspect of temperature field analysis of the crystallizer is realized in a steel mill for the first time, the analysis level of the metallurgy process is greatly improved, and the method is worthy of popularization.

Description

technical field [0001] The invention relates to the field of continuous casting of iron and steel metallurgy, in particular to a method for visual analysis of the temperature field of a continuous casting crystallizer. Background technique [0002] In continuous casting production, steel breakout is a catastrophic accident. The occurrence of steel breakout will not only reduce the working efficiency of continuous casting machine, but also cause equipment failure, even casualties, and destroy the balance of production organization. In all breakout accidents, the occurrence rate of bonded breakouts is the highest, accounting for more than 70%. Therefore, reducing bonded breakouts is the key to reducing the rate of continuous casting breakouts. [0003] At present, many breakout forecasting systems can predict bonded breakouts, cracked breakouts and slab sinking, and can also be drawn into mold heat flow diagrams. However, these systems only focus on the prediction of breakout...

AI Technical Summary

Problems solved by technology

However, these systems only focus on the prediction of breakout, without taking into account the distribution of the temperature field in the entire mold, and only provide a simple two-dimensional curve of temperature changing with time, and cannot realize any visual temperature monitoring of the temperature field in the mold ; There are also some temperature field visualization systems, but due to the complexity of the operating conditions in the crystallizer, the temperature field cloud maps given by these systems are still inaccurate

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