基于多尺度纹理融合分析的复合材料研磨质量评估研究
Yangjun Wang1, Zilu Liu2, Li Ling2
1School of Mechanical and Electrical Engineering, Soochow University, Suzhou 215000, China.
Materials (Basel, Switzerland)
|August 14, 2025
概括
本研究介绍了一种先进的机器视觉算法,用于复合材料表面研磨质量评估. 这种新的方法提高了缺陷检测的准确性和效率,减少了手动检查的需求.
科学领域:
- 材料科学 材料科学 材料科学
- 计算机视觉 计算机视觉
- 制造业 工程 制造工程
背景情况:
- 手动检查复合材料表面是低效和昂贵的.
- 自动化质量评估对于现代制造业至关重要.
研究的目的:
- 开发一种机器视觉算法,用于精确地评估复合材料的表面研磨质量.
- 克服传统检查方法的局限性.
主要方法:
- 提出了一个多尺度纹理融合分析算法,集成亮度和纹理特征.
- 开发了一个修改后的雷利参数,用于未抛光区域的预分段.
- 增强了Otsu算法与全球灰度平均值和标准偏差用于缺陷检测.
- 实施了适应性的多尺度纹理分析框架.
主要成果:
- 在表面研磨质量评估中实现了96%的识别准确度.
- 在自动缺陷检测中证明了>95%的可靠性.
- 成功检测到镜面反射缺陷和纹理均性的变化.
结论:
- 拟议的算法为自动化表面研磨质量评估提供了强大而高效的解决方案.
- 这种机器视觉方法显著改善了手动检查方法.
- 亮度和多尺度纹理分析的融合是算法的高性能关键.
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