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Integrated Intelligence Control Based on Fuzzy and AI for Reheating Furnace

机译:基于模糊和人工智能的加热炉集成智能控制

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摘要

An integrated intelligence control method based on fuzzy and artificial intelligence (AI) is proposed aiming at combustion control of reheating furnace in steel rolling mill. Both fuzzy and AI strategies are used to solve problems of the bigger overshoot and the slower response in conventional hearth temperature control when gas pressure and heat value are frequently and acutely varied. The fuel-air ratio optimization and flux tracking modules based on AI respectively decrease fuel consumption and prolong the lifetime of actuators. The proposed method is implemented on an intelligence controller and distributed controllers, and the field test on two reheating furnaces in Lianyuan Iron and Steel Group Co. Ltd., Loudi, Hunan, China confirms that hearth temperature standard deviation, fuel consumption, and high temperature oxidation of billet are respectively decreased by 50%, 12%, and 10% over the current manual method. The proposed method delivers superior performance for reheating furnace in steel industry, but also it can be applied for other type furnaces in steel industry and in other industries, where further performance improvement might be achieved by adding a self-organizing capability to the fuzzy logic and AI control.
机译:针对轧钢厂加热炉的燃烧控制,提出了一种基于模糊和人工智能的集成智能控制方法。当气体压力和热值频繁且剧烈变化时,模糊和AI策略都可用来解决传统炉膛温度控制中过大和响应慢的问题。基于AI的空燃比优化和磁通跟踪模块分别减少了燃油消耗并延长了执行器的使用寿命。该方法在智能控制器和分布式控制器上实现,并在湖南省娄底市联元钢铁集团有限公司的两台加热炉上进行了现场测试,证实了炉膛温度标准偏差,燃油消耗和高温与当前的手工方法相比,钢坯的氧化分别降低了50%,12%和10%。所提出的方法为钢铁工业中的加热炉提供了优越的性能,但是它也可以应用于钢铁工业和其他工业中的其他类型的炉子,通过在模糊逻辑中增加自组织能力可以进一步提高性能。 AI控制。

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