烧结矿FeO含量智能检测仪的开发  

Development of the intelligent detector of FeO content in sinter

作　　者：姜宏洲[1] 张学东[1] 张宏勋[1] 李万新[2] 周雷[2] 

机构地区：[1]东北大学信息工程学院,沈阳110006 [2]本溪钢铁公司

出　　处：《冶金自动化》1999年第6期13-16,共4页Metallurgical Industry Automation

摘　　要：检测仪应用图像处理与神经网络技术， 依照烧结看火工对烧结矿ＦｅＯ 含量的判断方法， 用ＣＣＤ 摄像机采集烧结机尾断面图像，对所采集的图像进行实时处理，并提取特征，再由根据烧结看火工的经验知识训练的ＢＰ神经网络对图像样本分类识别，最后给出相应的ＦｅＯ 含量等级。Techniques of image processing and neural networks applied to the intelligent detector of FeO content in sinter is proposed. One CCD camera is used in the detector to collect the cross section image of the discharge end of the strand. The image is processed in real time, the features of the image are extracted and then a neural network trained by the experience of watchers fire is employed to determine the content degree of FeO in the sinter at the moment of sampling.

关 键 词：烧结矿 图像处理 神经网络 氧化亚铁 智能检测仪 

分 类 号：TF046.6[冶金工程—冶金物理化学] TF325.1