一个符合代码的计算机视觉框架,用于对钢筋和预压混凝土桥梁进行视觉检查
Giuseppe Santarsiero1, Valentina Picciano1, Nicola Ventricelli1
1Department of Engineering, University of Basilicata, 85100 Potenza, Italy.
Sensors (Basel, Switzerland)
|February 27, 2026
概括
本研究介绍了VIADUCT软件,使用人工智能和计算机视觉来检测混凝土桥梁中的各种缺陷. 该工具通过提高缺陷识别准确性和基础设施安全效率来增强传统检查.
科学领域:
- 土木工程 土木工程是指土木工程.
- 计算机科学 计算机科学
- 人工智能的人工智能
背景情况:
- 传统的桥梁检查是劳动密集型和主观的.
- 为了高效的基础设施维护,需要自动检测缺陷.
- 现有的桥梁检查人工智能工具具有有限的缺陷识别能力.
研究的目的:
- 开发一个人工智能驱动的软件工具VIADUCT,用于检测钢筋和预应力混凝土桥的各种缺陷.
- 提高桥梁结构退化评估的准确性和效率.
- 通过自动识别恶化模式来支持检查员.
主要方法:
- 使用了YOLOv8n对象检测模型,该模型基于1045张桥梁检查图像进行训练.
- 实现了多模式的注意力机制,包括语义细分 (SAM,U-Net) 和缩.
- 为VIADUCT软件开发了一个图形用户界面 (GUI).
主要成果:
- 越道工具在检测各种桥梁缺陷方面展示了有希望的功能.
- 注意力机制有效地将对象检测模型集中在相关的桥梁区域上.
- 在缺陷检测方面取得了显著的精度,尽管训练数据集有限.
结论:
- 人工智能,特别是深度学习和计算机视觉,可以显著帮助评估混凝土桥梁的结构健康.
- 该VIADUCT软件为自动化桥梁检查提供了一个可扩展的解决方案.
- 未来的代可以整合新的对象检测模型以提高性能.
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