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Blast furnace abnormal furnace condition prediction manner

机译:高炉异常炉况预测方式

摘要

PROBLEM TO BE SOLVED: To properly predict abnormal furnace conditions by detecting blasting pressure of pressure in the furnace, frequency analyzing time series pattern and monitoring the neighborhood of a specific frequency. ;SOLUTION: In a blast furnace 10, a sensor 15 for detecting the blasting pressure and a sensor 16 for detecting the pressure in a shaft part are fitted, respectively and data detected with these sensors 15, 16 are periodically collected and stored in a data collecting part 25. In a time series frequency analyzing part 26, the time series frequency analysis of the data in the past fixed period is executed from the newest values of the collected and stored pressure data. In the case of executing this analysis with a Fourier transformation, the change with time of the frequency components in the sensor data can be obts. by executing the Fourier transformation related to each time in the time series data. The analyzed result is displayed on an observing monitor 27. At this time, the tendency to the aggration of the furnace condition is predicted in advance by observing to power near the prescribed frequency (e.g. 2.8×10-3Hz; the frequency component accompanying the charge of raw material).;COPYRIGHT: (C)1998,JPO
机译:解决的问题:通过检测炉内压力的爆破压力,频率分析时间序列模式并监视特定频率的附近区域来正确预测炉子的异常状况。 ;解决方案:在高炉10中,分别装有用于检测鼓风压力的传感器15和用于检测竖井部分压力的传感器16,并定期收集用这些传感器15、16检测到的数据并将其存储在数据中收集部分25。在时间序列频率分析部分26中,根据收集和存储的压力数据的最新值执行过去固定时间段内数据的时间序列频率分析。在通过傅立叶变换执行此分析的情况下,传感器数据中频率分量的时间变化可能会很明显。通过执行与时间序列数据中的每个时间相关的傅立叶变换。分析结果显示在观察监视器27上。这时,通过观察接近规定频率(例如2.8×10 -3 Hz;随原材料一起使用的频率分量).;版权所有:(C)1998,JPO

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