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光腔衰荡法数据截取对时间常数测量精度的影响分析

张金玉 金尚忠 张彪 吴磊 俞兵 袁良 黎高平

张金玉, 金尚忠, 张彪, 吴磊, 俞兵, 袁良, 黎高平. 光腔衰荡法数据截取对时间常数测量精度的影响分析[J]. 应用光学, 2023, 44(1): 153-158. doi: 10.5768/JAO202344.0103006
引用本文: 张金玉, 金尚忠, 张彪, 吴磊, 俞兵, 袁良, 黎高平. 光腔衰荡法数据截取对时间常数测量精度的影响分析[J]. 应用光学, 2023, 44(1): 153-158. doi: 10.5768/JAO202344.0103006
ZHANG Jinyu, JIN Shangzhong, ZHANG Biao, WU Lei, YU Bing, YUAN Liang, LI Gaoping. Influence of cavity ring-down data interception on time constant measurement accuracy[J]. Journal of Applied Optics, 2023, 44(1): 153-158. doi: 10.5768/JAO202344.0103006
Citation: ZHANG Jinyu, JIN Shangzhong, ZHANG Biao, WU Lei, YU Bing, YUAN Liang, LI Gaoping. Influence of cavity ring-down data interception on time constant measurement accuracy[J]. Journal of Applied Optics, 2023, 44(1): 153-158. doi: 10.5768/JAO202344.0103006

光腔衰荡法数据截取对时间常数测量精度的影响分析

doi: 10.5768/JAO202344.0103006
基金项目: 浙江省科技计划项目(2020C03095);技术基础科研项目(JSJL2020208A003);测试仪器项目(2006ZCGG0103-2)
详细信息
    作者简介:

    张金玉(1994—),男,硕士研究生,主要从事光学计量测试研究工作。E-mail:1731135828@qq.com

  • 中图分类号: TN248

Influence of cavity ring-down data interception on time constant measurement accuracy

  • 摘要: 光腔衰荡方法是目前测量光学元件超高反射率(反射率>99.9%)的唯一方法。介绍了一种对光腔衰荡法中激光信号强度与时间关系的优化提取方法。设计了基于光腔衰荡法的光学元件超高反射比的测试系统,通过对采集的光腔衰荡曲线数据进行分段指数拟合,将光腔衰荡曲线数据分为5段,对每段指数拟合结果对应的R2 (R-square)和RMSE(root mean squared error)值进行对比分析,计算每段指数拟合的衰荡时间。实验结果表明:截取光腔衰荡曲线数据40%~60%部分拟合得到的结果最接近真实值,求得对应的腔镜的反射率为99.988 977%。最后通过与腔镜的自身反射率进行比较,表明该种数据拟合方法能有效地测量腔镜的反射率,并能减小实验数据本身带来的误差。
  • 图  1  初始光腔测量系统框图

    Fig.  1  Block diagram of initial optical cavity measurement system

    图  2  测试光腔测量系统框图

    Fig.  2  Block diagram of test optical cavity measurement system

    图  3  折叠腔示意图

    Fig.  3  Schematic diagram of folding cavity

    图  4  实验装置系统连接示意图

    Fig.  4  System connection diagram of experimental device

    图  5  第23组一次指数函数拟合曲线图

    Fig.  5  Fitting curve of primary exponential function of group 23

    图  6  第23组二次指数函数拟合曲线图

    Fig.  6  Fitting curve of quadratic exponential function of group 23

    图  7  第1组数据拟合曲线图

    Fig.  7  Fitting curve of data of group 1

    图  8  第2组数据拟合曲线图

    Fig.  8  Fitting curve of data of group 2

    图  9  第3组数据拟合曲线图

    Fig.  9  Fitting curve of data of group 3

    图  10  第4组数据拟合曲线图

    Fig.  10  Fitting curve of data of group 4

    图  11  第5组数据拟合曲线图

    Fig.  11  Fitting curve of data of group 5

    表  1  6组实验数据的处理值

    Table  1  Processing values of six groups of experimental data

    试验组数第3组第8组第13组第18组第23组第28组
    ${ {R} }^{2}$0.994 60.994 30.994 20.994 10.994 30.994 3
    $ {\rm{RMSE}} $4.9224.9524.9134.9504.8204.851
    下载: 导出CSV

    表  2  第23组指数函数拟合统计值

    Table  2  Fitting statistics of exponential function of group 23

    拟合函数次数一次指数拟合二次指数拟合
    ${ {R} }^{2}$0.994 30.999 0
    $ {\rm{RMSE}} $4.8201.999
    下载: 导出CSV

    表  3  5段数据求得的参数值

    Table  3  Parameter values obtained from five segments of data

    数据1~500501~1 0001 001~1 5001 501~2 0002 001~2 500
    $\tau $16.949 1519.801 9830.238 88770.821 53228.519 56
    $R$0.999 8030.999 831 70.999 889 770.999 952 90.999 985 4
    ${ {R} }^{2}$0.994 80.980 90.906 80.633 10.164 5
    $ {\rm{RMSE}} $4.8122.0211.0590.609 20.444 6
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-03-28
  • 修回日期:  2022-04-28
  • 网络出版日期:  2022-08-05
  • 刊出日期:  2023-01-17

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