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模糊逻辑方法用于模拟工业炉中的加热和规模形成
Jaroslaw Krzywanski1, Jaroslaw Boryca2, Dariusz Urbaniak3
1Department of Advanced Computational Methods, Faculty of Science and Technology, Jan Dlugosz University in Czestochowa, 13/15 Armii Krajowej Ave., 42-200 Czestochowa, Poland.
Materials (Basel, Switzerland)
|November 9, 2024
概括
这项研究使用模糊逻辑在工业炉中模拟钢材加热和形. 开发的模型准确地预测了最终的表面温度和尺寸厚度,有助于减少能源消耗.
科学领域:
- 材料科学 材料科学 材料科学
- 工艺工程是过程工程.
- 计算智能是一种计算智能.
背景情况:
- 钢铁加热对于电荷形成至关重要,但非常耗能.
- 尽量减少形是减少钢铁加工过程中热量的关键.
- 工业再加热炉对于热厂的运行至关重要.
研究的目的:
- 开发一种基于模糊逻辑的模型,用于预测工业再加热炉中的加热和尺度形成.
- 为了最大限度地减少钢充电加热过程中的多余能源消耗.
- 为预测最终表面温度和尺度厚度提供一个工具.
主要方法:
- 应用模糊逻辑来建模加热和尺度形成的复杂相互作用.
- 使用初始充电温度,加热时间,过剩空气系数和初始尺度厚度的实验数据作为模型输入.
- 模型的验证使用来自热厂部门行走光束炉的数据.
主要成果:
- 成功开发了一个基于模糊逻辑的加热和尺度形成 (HSF) 模型.
- 该模型准确地预测了钢充电的最终表面温度.
- 该模型有效地预测了加热过程中形成的尺度层的最终厚度.
- 通过与测量结果进行比较,确认了模型的准确性.
结论:
- 模糊逻辑提供了一种可接受的方法,用于模拟工业炉中的加热和尺度形成.
- 开发的HSF模型可以帮助优化加热过程,以减少能源消耗.
- 可以准确预测温度和尺度厚度,从而支持高效的钢铁生产.
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