摘要
综述了人工智能在钢铁材料微观组织分析的应用与研究进展、主要问题和当前研究热点。目前,微观组织试验测试结果数据全部实现数字化。图像等结果数据的智能分析呈现基于专家系统的知识应用型弱人工智能特征。工业大数据和物理数学模型日趋完善促进热轧组织性能预报强智能化发展。深度学习的应用逐步提升微观组织分析研究与实践的智能化水平。展望未来,基于大数据集构建和深度学习的强人工智能技术将广泛深入应用到本领域。
The application and research progress,main problems and current research hotspots of artificial intelligence in microstructure analysis of iron and steel are reviewed.At present,the data of test results,such as microstructure images are all digitized.The intelligent analysis of images and other result data presents the characteristics of knowledge-based application-oriented weak artificial intelligence based on expert systems.Industrial big data and physical-mathematical models are becoming more and more perfect to promote the development of intelligent prediction of hot rolling microstructure and properties.The application of deep learning gradually improves the intelligent level of microstructure analysis research and practice.Looking to the future,strong artificial intelligence technologies based on large dataset construction and deep learning will be widely and deeply applied to this field.
作者
陈鹰
CHEN Ying(Laboratory of Central Iron and Steel Research Institute,Beijing 100081,China)
出处
《中国体视学与图像分析》
2022年第1期47-54,共8页
Chinese Journal of Stereology and Image Analysis
关键词
人工智能
微观组织分析
钢铁材料
深度学习
artificial intelligence
microstructure analysis
iron and steel
deep learning
