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

机译:基于混沌和神经元理论的振动炉渣检测系统

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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 home and aboard 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 shroud 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, and 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.
机译:在钢水铸造过程中,必须检测出流渣,以提高钢材质量和连铸效率。在对国内外排渣检测技术进行了深入研究,数据分析和数据汇总之后,本文通过混沌和神经元方法,分析了护罩操作臂的振动信号,提出了一种钢铸态排渣检测系统。深入研究了钢水振动信号的采集,处理以及炉渣特征参数的识别方法,阐述了神经网络在铸态识别中应用的基本原理。简要介绍了矿渣检测系统的框架和功能设计。在湘钢厂进行的结果测试证明了该渣检测系统的有效性,该钢渣检测系统可以满足实时需求,提高钢水的纯净度和连铸效率,为钢厂带来明显的效益。

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