铸造2024，Vol.73Issue(4)：520-526,7.
基于AI图像分析的铸造原砂粒度粒形检测法
AI-Based Image Analysis for Particle Size and Shape Detection in Casting Sand
李贝贝 1郭树人 1曹华堂 1刘鑫旺 1董选普 1张宇辉 2钟飞升 2吴执成2
作者信息
- 1. 华中科技大学材料科学与工程学院,材料成形与模具技术全国重点实验室,湖北武汉 430074
- 2. 辽宁联信铸砂投资集团有限公司,辽宁沈阳 110000
- 折叠
摘要
Abstract
The shape and particle size distribution of casting sand are important factorsin the production and utilization of the casting sand.To address the issues of measurement efficiency and measurement errors associated with sieving methods,this study proposed a casting sand particle size and shape testing method based on artificial intelligence(AI)image analysis,which involves capturing images of the casting sand using an industrial camera and employing AI image processing techniques for instance segmentation.Subsequently,the images were subjected to feature extraction to statistically determine the particle size and shape distribution of the casting sand.The research findings indicated that the AI-based BlendMask instance segmentation model,could effectively separate agglomerated sand particles.By utilizing three feature parameters-circularity,shape factor,and rectangularity-for K-means clustering of casting sand particles,the method analyzed the particle shape characteristics accurately.Furthermore,employing the equivalent ellipse method and the area proportion equivalent mass ratio method enabled precise measurement of the particle size distribution for three types of the casting sand:baked sand,dried sand,and zircon sand,respectively,which meets the industry accuracy requirements.关键词
铸造原砂/粒度分布/粒形/图像法/实例分割/深度学习Key words
casting sand/particle size distribution/particle shape/image-based method/instance segmentation/deep learning分类
矿业与冶金引用本文复制引用
李贝贝,郭树人,曹华堂,刘鑫旺,董选普,张宇辉,钟飞升,吴执成..基于AI图像分析的铸造原砂粒度粒形检测法[J].铸造,2024,73(4):520-526,7.
