Slag Detection System Based on Vibration using Chaos and Nerve Cell Theory

摘要

At the process of molten steel casting, outflow slag must be detected to improve the quality of steel product and continuous casting efficiency. After lots of investigation of the internal and external slag detection technology, data analysis and data summarization,the dissertation brings forward the slag detection system of the casting state of steel by analyzing the vibration signal of nozzle operation arm using chaos and nerve cell method.The collection and process of molten steel vibration signal and the method of slag characteristic parameter identification has been researched deeply, basic principles of the application of neural network in casting state recognition are expounded. And the frame and function design of slag detection system are all briefly introduced. The results testing in Xiang Steelworks proved the effectiveness of the slag detection system, which can satisfy the demand for real-time, improve pure measure of molten steel and continuous casting efficiency and create benefit for the steelworks evidently.