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材料测试技术是研究材料结构、成分与性能之间关系的关键手段，也是确保材料研发和应用安全的重要基础。近年来，人工智能（artificial intelligence,AI）技术的进步，特别是深度学习(deep learning,DL)、机器学习(machine learning,ML)和计算机视觉的发展，为材料测试技术带来了新的变革和发展机遇。该文首先介绍了人工智能在现代材料测试中的核心应用场景，然后结合具体案例剖析AI在微观结构表征、X射线衍射（X-ray diffraction,XRD）图谱智能物相分析及光谱类表征中的技术实现路径，为材料测试领域的智能化转型提供理论参考与实践借鉴。最后探讨了人工智能驱动下材料测试技术未来的发展方向。
Abstract：Material testing technology is a key means to study the relationships between material structure,composition, and performance, and also serves as an important foundation for ensuring the safety of material research, development, and application. In recent years, the advancement of artificial intelligence(AI)technology, especially the development of deep learning(DL), machine learning(ML), and computer vision,has brought new changes and development opportunities to material testing technology. This paper first introduces the core application scenarios of AI in modern material testing, then analyzes the technical implementation pathways of AI in microstructural characterization, intelligent phase analysis of X-ray diffraction(XRD) patterns, and spectral characterization by combining specific cases, providing theoretical references and practical references for the intelligent transformation of the material testing field. Finally, it discusses the future development directions of material testing technology driven by artificial intelligence.
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基本信息:
DOI：10.11857/j.issn.1674-5124.2025100065
中图分类号:TB302;TP18
引用信息:
[1]夏芳芳,翟天佑.人工智能在材料测试中的应用及其案例分析[J].中国测试,2026,52(03):1-7+79.DOI:10.11857/j.issn.1674-5124.2025100065.
2025-10-21
2025-12-03
2026-03-31
2026-03-31