基于裂特征的支持矢量机的混凝土裂自动识别系统
Rui Wang1, Rui-Qi Chen1, Xin-Xin Guo2
1College of Engineering, Sichuan Normal University, Chengdu, 610068, China.
Scientific reports
|August 29, 2024
概括
本研究介绍了使用支矢量机 (SVM) 和图像处理的有效混凝土裂检测系统. 拟议的方法在识别裂方面达到97.14%的准确性,增强了结构健康监测.
科学领域:
- 土木工程 土木工程是指土木工程.
- 计算机视觉 计算机视觉
- 材料科学 材料科学 材料科学
背景情况:
- 混凝土裂是基础设施中普遍存在的问题,需要可靠的自动化检查方法.
- 机器视觉系统为混凝土裂检测和识别提供先进的解决方案.
- 有效的裂识别对于结构健康评估和维护至关重要.
研究的目的:
- 开发和验证用于混凝土裂检测和识别的自动化系统.
- 提高在混凝土表面破裂识别的准确性和效率.
- 建立一个强大的框架来区分裂和其他表面异常.
主要方法:
- 使用Pewitt运算符和Otsu值算法的组合图像细分.
- 数学形态学的应用,以改进裂区的识别.
- 功能提取包括紧性,占用率和长宽比.
- 支持矢量机 (SVM) 具有辐射基础功能,用于裂分类.
主要成果:
- 拟议的细分算法有效地产生了完整的裂区域,干扰减少.
- 预先区分成功删除了99%的杂质区域,确保了样品质量.
- 对于混凝土裂,SVM模型实现了97.14%的高识别精度.
结论:
- 开发的机器视觉系统在混凝土裂检测方面表现出高效率和实用性.
- 集成先进的图像处理技术和SVM分类为结构监控提供了可靠的解决方案.
- 提出的方法满足了对混凝土表面自动检查的实际要求.
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