大数据分析的大口径光学元件检测误差  

Detection errors of large aperture optical components in big data analysis

作　　者：张栋 杨丽 ZHANG Dong;YANG Li(College of Mathematics and Statistics,Cangzhou Normal University,Cangzhou Hebei 061001,China)

机构地区：[1]沧州师范学院数学与统计学院,河北沧州061001

出　　处：《激光杂志》2022年第11期58-62,共5页Laser Journal

基　　金：2018年度河北省科技厅计划项目(No.18456114)。

摘　　要：为更全面测量大口径光学元件的误差,提出基于大数据分析大口径光学元件检测误差。采用大数据分析中的Simhash去重算法计算数据相似性,并将重复数据去除;利用数据平差方法计算去重后数据的条件平差与间接平差,依据平差值构建元件测量模型;通过测量坐标转换再次计算测量结果,利用随机方向法寻优计算拟合误差最小值,得到最合适拟合误差坐标系,实现大口径光学元件检测误差分析。经实验验证:该方法数据传输吞吐量大;大口径光学元件误差与实际误差接近,检测精度超过95%。In order to measure the errors of large-aperture optical elements more comprehensively, it is proposed to analyze the detection errors of large-aperture optical elements based on large data. Adopt Simhash deduplication algorithm in big data analysis to calculate data similarity and remove duplicate data;The conditional adjustment and indirect adjustment of the data after de-duplication are calculated by using the data adjustment method, and the component measurement model is constructed according to the adjustment values. The measurement results are calculated again through the transformation of measurement coordinates, and the minimum fitting error is optimized and calculated by the random direction method, so as to obtain the most suitable fitting error coordinate system and realize the detection error analysis of large-aperture optical elements. Experiments show that this method has high data transmission throughput;The error of large aperture optical element is close to the actual error, and the detection accuracy is more than 95%.

关 键 词：大数据分析 大口径光学元件 检测误差 随机方向法 

分 类 号：TN214[电子电信—物理电子学]