基于MCM的二维水平分布式光度传感器的不确定性评估,用于照度测量任务
Jianguo Sun1, Yueyao Wang1, Yinbao Cheng1
1College of Metrology Measurement and Instrument, China Jiliang University, Hangzhou 310018, China.
Sensors (Basel, Switzerland)
|August 14, 2025
概括
这项研究提出了一个新的框架,用于评估用于LED充电灯的分布式光度传感器的测量不确定性. 它发现蒙特卡洛方法提供了比GUM方法更准确的不确定性评估.
科学领域:
- 光学和光子学 在光学和光子学.
- 计量学 计量学 计量学
- 光学工程是指光学工程.
背景情况:
- 精确的照度测量对于LED充灯质量控制和光学设计至关重要.
- 分布式光度传感器提供优势,但在不确定性评估方面面临挑战.
- 现有的方法可能无法完全捕捉这些先进测量系统的复杂性.
研究的目的:
- 提出和验证用于使用二维水平分布式光度传感器测量光度参数的不确定性评估框架.
- 为了比较"测量不确定性表达指南" (GUM) 和蒙特卡洛方法 (MCM) 在这种情况下进行不确定性合成.
- 通过改进不确定性评估,提高光学计量系统的可靠性.
主要方法:
- 为二维水平分布式光度传感器系统开发一个不确定性分析模型.
- 实施和比较两个不确定性合成方法:GUM和MCM.
- 设计和执行照度测量实验以验证拟议的框架.
主要成果:
- 测量数据的概率分布被发现遵循梯形分布.
- 使用GUM方法计算的扩展不确定性比使用MCM获得的不确定性高21.1%.
- 拟议的框架有效地解决了这种类型传感器的不确定性评估挑战.
结论:
- 与GUM方法相比,蒙特卡洛方法为分布式光度传感器提供了更准确的不确定性评估.
- 这些发现对于评估高精度光学仪器的不确定性非常有价值.
- 这项研究对提高光学计量系统的可靠性作出了重大贡献.
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