【24h】

Mathematical Modelling of Capacitance Sensor for Blast Furnace Burden Identification

机译:高炉负荷识别电容传感器的数学建模

获取原文
获取原文并翻译 | 示例

摘要

The primary blast furnace burden are coke and ore. The visualization of furnace burden has been an attractive task and a very difficult task due to the furnace being a high temperature, high pressure 'black box'. Owing to the significant difference between coke and ore in permittivity, Electrical capacitance tomography (ECT) can be applied to the furnace burden visualization. Since the furnace burden distribution is quite different from the material distribution imaged by any existing ECT system, the micro-capacitor series-parallel model is used in this paper to analyze the relationship between the capacitance sensor output and the blast furnace burden distribution. The main problem in designing capacitance sensor array is also discussed in this paper.
机译:高炉的主要负担是焦炭和矿石。由于炉子是高温,高压的“黑匣子”,因此炉子负荷的可视化一直是一项有吸引力的任务,并且是一项非常艰巨的任务。由于焦炭和矿石之间介电常数的显着差异,可以将电容层析成像(ECT)应用于熔炉负荷可视化。由于熔炉负荷分布与现有ECT系统成像的材料分布有很大不同,因此本文使用微电容器串并联模型分析电容传感器输出与高炉负荷分布之间的关系。本文还讨论了电容传感器阵列设计中的主要问题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号