Tags of micro-power active RFID system are usually supllied by cells battery, the power consumption is a crucial factor. The currently applied operating mode is of timing wake-up. In this paper, presented the method o...Tags of micro-power active RFID system are usually supllied by cells battery, the power consumption is a crucial factor. The currently applied operating mode is of timing wake-up. In this paper, presented the method of LF wake-up technology , discussed how to use it to solve the low-power problem of active RFID tag. Put forward the crucial electrocircuit and working program flow. Practices show that this solution is capable of solving the problem of low-power of active RFID.展开更多
以我国某钢厂120 t LF精炼炉为研究对象,通过建立由冶炼机理模型和XGBoost模型相结合的混合模型,预测LF精炼过程中的钢水成分并进行实际应用。结果表明,模型预测终点碳、硅、锰、铝等元素均处于内控范围内,并平均减少了每炉钢取样工序0....以我国某钢厂120 t LF精炼炉为研究对象,通过建立由冶炼机理模型和XGBoost模型相结合的混合模型,预测LF精炼过程中的钢水成分并进行实际应用。结果表明,模型预测终点碳、硅、锰、铝等元素均处于内控范围内,并平均减少了每炉钢取样工序0.8次,提高了生产效率。展开更多
针对LF精炼炉钢液温度控制过度依赖人工经验的问题,马钢长材事业部以120 t LF精炼炉为研究对象,基于能量平衡原理,计算分析LF精炼过程中输入电能、合金化、炉渣热效应、钢包内衬散热、渣面辐射、吹氩搅拌和烟气热损失等热量对钢液温度...针对LF精炼炉钢液温度控制过度依赖人工经验的问题,马钢长材事业部以120 t LF精炼炉为研究对象,基于能量平衡原理,计算分析LF精炼过程中输入电能、合金化、炉渣热效应、钢包内衬散热、渣面辐射、吹氩搅拌和烟气热损失等热量对钢液温度的影响,建立LF精炼钢液温度的预测模型。经过跟踪实际生产试验、测温校正并优化模型,使模型取得了良好的应用效果。模型预测温度与实际测量值偏差绝对值≤5℃的比例为97.73%,偏差绝对值≤6℃的比例为100%。展开更多
针对LF精炼操作对人工经验过度依赖的问题,马鞍山钢铁有限公司长材事业部基于冶金机理,在120 t LF上开发了温度模型、合金模型、吹氩模型和造渣模型,建立以钢水温度、成分、炉渣三者相互统一的控制模型,利用大数据技术和自学习功能对控...针对LF精炼操作对人工经验过度依赖的问题,马鞍山钢铁有限公司长材事业部基于冶金机理,在120 t LF上开发了温度模型、合金模型、吹氩模型和造渣模型,建立以钢水温度、成分、炉渣三者相互统一的控制模型,利用大数据技术和自学习功能对控制模型进行优化,实现了各模型协同集成和LF智能控制,取得了良好的应用效果,LF自动控制比例达到80%,终点目标温度±5℃命中率达95%以上,终点成分窄范围命中率(w(Si)±0.02%、w(Mn)±0.02%、w(S)±0.001%、w(Al s)±0.005%)达97%以上,降低LF精炼电耗约4 kWh/t、减少精炼处理时间约5 min,提高了生产效率和钢水质量,对炼钢工序降本增效起到了重要作用。展开更多
文摘Tags of micro-power active RFID system are usually supllied by cells battery, the power consumption is a crucial factor. The currently applied operating mode is of timing wake-up. In this paper, presented the method of LF wake-up technology , discussed how to use it to solve the low-power problem of active RFID tag. Put forward the crucial electrocircuit and working program flow. Practices show that this solution is capable of solving the problem of low-power of active RFID.
文摘针对LF精炼炉钢液温度控制过度依赖人工经验的问题,马钢长材事业部以120 t LF精炼炉为研究对象,基于能量平衡原理,计算分析LF精炼过程中输入电能、合金化、炉渣热效应、钢包内衬散热、渣面辐射、吹氩搅拌和烟气热损失等热量对钢液温度的影响,建立LF精炼钢液温度的预测模型。经过跟踪实际生产试验、测温校正并优化模型,使模型取得了良好的应用效果。模型预测温度与实际测量值偏差绝对值≤5℃的比例为97.73%,偏差绝对值≤6℃的比例为100%。
