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Tim Sliti¹, Nils F Melchert¹, Philipp Middendorf¹

¹Institute of Measurement and Automatic Control, Stiftung Gottfried Wilhelm Leibniz Universität Hannover, An der Universität 1, D-30823 Garbsen, Germany.

Sensors (Basel, Switzerland)

|February 27, 2026

概括

一个新的传感器通过光反射快速评估轮叶片表面状况,帮助维护和质量检查. 它在确定需要详细粗度分析的区域方面表现有前途,补充了传统方法.

科学领域:

材料科学材料科学材料科学
光学工程是指光学工程.
航空航天工程航空航天工程

背景情况:

部件的功能和寿命在很大程度上取决于技术表面的状况.
轮机叶片表面的粗程度显著影响航空发动机的性能.
传统的粗度测量对于大面积评估来说是耗时的.

研究的目的:

介绍基于LED和摄像头的照明传感器,用于快速,广泛地表征轮机叶片表面.
研究来自传感器的反射率参数与传统的表面粗度参数之间的关系.
评估传感器在维护,维修和大修 (MRO) 和质量保证 (QA) 背景下对表面状况分类的潜力.

主要方法:

使用开发的传感器获取多种照明图像数据.
每个像素安装一个异性双向反射分布函数 (BRDF) 模型以获得反射参数.
使用共聚焦激光扫描显微镜作为参考数据,独立测量表面粗度参数 (Sa,Sq,Sz,Ssk,Sku).
在具有对比表面条件的轮机叶片上,对BRDF参数和粗性特征之间的关系进行定性研究.

主要成果:

在BRDF参数和基于高度的粗度参数 (Sa,Sq,Sz) 之间观察到较弱的相关性.
在BRDF参数和表面分布参数 (Ssk,Sku) 之间发现了更明显的趋势.
在方向BRDF参数和表面纹理方向之间发现了良好的质量一致.

结论:

开发的照明传感器提供了一个互补的,基于反射率的方法来评估表面状况.
传感器可以有效地突出需要更详细的粗度测量区域,帮助MRO和QA流程.
未来的工作将涉及到对各种组件几何学的定量分析和应用.

关键词:

这就是BRDF.反射力反射力是什么?粗性粗性粗性的表面测量测量表面测量

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