高炉料面检测中的多源数据融合  

Multi-source data fusion in detection of blast furnace burden surface

作　　者：苗亮亮[1,2] 陈先中[1] 侯庆文[1] 白真龙[1] 王正鹏[1] 

机构地区：[1]北京科技大学自动化和电子工程学院钢铁流程先进控制教育部重点实验室,北京100083 [2]北京佰能电气技术有限公司,北京100096

出　　处：《光学精密工程》2014年第9期2407-2415,共9页Optics and Precision Engineering

基　　金：国家自然科学基金资助项目(No.61333002)

摘　　要：针对高炉料面检测中多传感器数据难以直接应用的问题,提出了同时融合高度和温度数据,结合布料机理对非检测点进行估计来实现料面检测的方法。首先,对高炉异类传感器得到的多源数据进行时间和空间配准;然后,根据高炉高度与温度的机理关系,提出环域配准融合思想,用高炉料面温度求出对应的高度;最后,结合料面的物理性质,将理论料形与多源数据进行贝叶斯融合得到高炉料面图像。以某钢铁企业2 500m3高炉现有检测设备为基础进行了现场实验,实验结果表明,与料形估算法相比,本文检测方法的测量精度提高了5.4%,料面分辨率提高了0.43。该方法使得高炉料面形状检测更加精准,为高炉节能减排操作提供了必要的指导。In consideration of the difficulty of directly using the multi-sensor detecting data in detection of the burden surface of a blast furnace（BF）, a novel approach is put forward. The method fuses height data and temperature data and makes use of material mechanism to estimate the non-detecting points to obtain the burden surface. First, multi-sourced data obtained by dissimilar sensors are dealt with in both the time dimension and the spatial dimension. Then, a specific means of loop domain registration is proposed to derive the height of burden surface from the temperature of burden surface. Finally, by combing with the physical properties of surface shape and using Bayes fusion for the theoretical shape and multi-sourced data, the image of burden surface shape of BF is acquired. The experiments indicate that the measurement accuracy has improved by 5.4%, and the resolution of BF has improved by 0.43 as compared with that the traditional burden surface shape estimating method. The method provides necessary guidance for energy saving operation of blast furnaces.

关 键 词：料面检测 多源数据融合 环域配准 贝叶斯融合 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术] TF03[自动化与计算机技术—计算机科学与技术]