通过机器视觉与工人肉眼的类比，设计了一种基于视频图像的连铸大包下渣检测系统，利用该系统进行了连铸大包下渣特征提取方法的研究。构建了系统平台，通过软硬件进行视频图像信号的采集与处理，实现对连铸大包下渣过程的实时在线监控，无长水口保护套时进行钢流边缘的下渣特征提取与分析，有长水口保护套时进行液面平均灰度变化、结构相似度、统计特性的多参数以及三特征综合分析的下渣特征提取与分析。工业现场试验表明：该系统具有易于安装维护、自动化程度高、使用寿命长、成本低、非接触式检测、有一定的下渣检测成功率等优点，可有效地减少下渣量，提高钢水收得率，降低中间包的存渣厚度，有较高的使用价值。
A continuous casting ladle slag detection system in which an image recognized technology was used to detect the slag was designed by comparing machine vision with workers eye. The system was used for researching on continuous casting ladle slag feature extraction method. System platform was built and completed video image signal sampling and processing by software and hardware to realize the real-time online monitoring of continuous casting ladle slag process. As for having no long outlet protection sleeve, it presented slag feature extraction based on steel flow edge detection; as for the other situation, it presented slag feature extraction based on the average change in gray about the fluid level, structural similarity, statistical properties and combined analysis for three features. Industrial field experiments proved： this detecting system is easy to installation and maintenance, has high degree of automation, long service life, low cost, non-contact detection and a certain success rate of slag detection. It can effectively reduce slag amount, improve the yield of molten steel, reduce the thickness of the tundish slag deposits and has a high practical value .
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