基于线型激光的连铸板坯表面裂纹在线检测技术  

On-line detection technique of surface cracks for continuous casting slabs based on linear lasers

作　　者：徐科[1] 杨朝霖[1] 周鹏[1] 杨成[1] 李希纲[1] 

机构地区：[1]北京科技大学高效轧制国家工程研究中心,北京100083

出　　处：《北京科技大学学报》2009年第12期1620-1624,共5页Journal of University of Science and Technology Beijing

基　　金："十一五"国家科技支撑计划资助项目(No.2006BAE03A06);国家自然科学基金资助项目(No.60705017);北京市科技新星计划资助项目(No.2007B027)

摘　　要：采用光学检测法对高温铸坯进行表面裂纹在线检测,将高亮度绿色激光线光源照射到铸坯表面,利用激光的单色性在摄像机镜头前加装窄带滤色镜去除高温铸坯表面辐射光的影响,从而提高图像的对比度.通过非抽样小波对铸坯表面图像进行分解,计算分解后得到的低频分量和原始图像的尺度共生矩阵,以及高频分量的灰度共生矩阵,作为图像的纹理特征,并输入基于AdaBoosting算法的分类器进行分类.利用该方法对表面裂纹、水痕、渣痕、氧化铁皮和振痕等五种缺陷和伪缺陷样本进行识别,表面裂纹的识别率达86.75%,总体识别率达87.16%.An optical detection technique was applied to on-line detection of surface defects for continuous casting slabs with high temperature. Green linear lasers with high luminance were projected on the slab surface. According to laser monochromaticity, a narrowband color filter was added to lens to prevent slab radiation coming into CCD cameras, and the image contrast was improved. Non- sampling wavelet decomposition was applied to surface images of the slabs, and the scale co-occurrence matrixes of low-pass compo- nents and original images were calculated as textural features of images, as well as the scale coccurrence matrixes of high-pass components. A classifier based on AdsBoosting algorithms was developed for classification of defects with textural features. The technique was tested with samples of surface cracks, water marks, slag marks, scales and vibration marks, and the results show that the classification rate of surface cracks is 86.75 % and the classification rate of all the samples is 87.16 %.

关 键 词：连铸板坯 表面裂纹 在线检测 共生矩阵 

分 类 号：TP216[自动化与计算机技术—检测技术与自动化装置]