Termination point prediction method and system for converter steelmaking

Abstract

The embodiment of the present invention discloses a termination point prediction method and a system for converter steelmaking. The method includes the following steps: collecting current production parameter information in converter steelmaking and current flame information at the mouth of a converter as independent variables; creating a neural network, and training the created neural network with a training sample made up of the independent variables; and predicting the termination point of converter steelmaking by the neural network obtained after the training according to the independent variables, so as to obtain a termination point time prediction result, a carbon content prediction result and a molten steel temperature prediction result. Therefore, with the technical scheme provided by the embodiment of the present invention, by obtaining the production information of the converter and the flame information at the mouth of the converter in real time, the steelmaking terminationpoint time, the molten steel temperature and the carbon content can be analyzed precisely online in real time, so as to precisely control the process to improve the automation and the production efficiency of converter steelmaking and lower the cost.

Description

technical field [0001] The invention relates to the field of automatic control of steelmaking, and more specifically, to a method and system for predicting the end point of converter steelmaking. Background technique [0002] Steelmaking end point control in converter steelmaking is one of the key technologies in converter steelmaking, and the steel production of converter steelmaking accounts for more than 80% of the total steel production. In large and medium-sized key iron and steel enterprises, the output of converter steel occupies a dominant position, so improving the production capacity and control level of converter steelmaking has always been valued by people. Converter steelmaking is a very complicated metallurgical reaction process with many influencing factors. In order to realize the automatic control of the converter smelting process, many detection technologies have been developed at home and abroad. The commonly used methods mainly include artificial experie...

AI Technical Summary

Problems solved by technology

[0003] In actual production and theoretical research, it is found that artificial experience controls the end point of steelmaking, which is closely related to the experience and working status of on-site workers. It has low end point hit rate, high labor intensity for workers, high spattering rate, and poor production stability. Problem: With the static terminal control system, the hit rate still cannot meet the requirements of automatic steelmaking, and the control process cannot be tracked and corrected in real time; although the furnace gas analyzer and sub-lance are better than the manual experience control and static control methods. Better end-point prediction accuracy, but due to the high cost, difficult maintenance, and large size of these equipment, they are only used in some large steel mills; the measurement time of chemical analysis method is far from meeting the requirements of smelting process control Real-time requirements, and there is a splash accident during sampling;

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