Research on Benchmark Ruler Measurement Method based on Cluster Analysis

被引:0
|
作者
Hu, Xiaolei [1 ,2 ]
Zhang, Feng [1 ,2 ]
Ren, Yu [1 ,2 ]
Tang, Yajie [1 ,2 ]
Fu, Yunxia [1 ,2 ]
机构
[1] Shanghai Inst Measurement & Testing Technol, 1500 Zhang Heng Rd, Shanghai 201203, Peoples R China
[2] Shanghai Key Lab Online Testing & Control Technol, Shanghai 201203, Peoples R China
来源
关键词
measurement traceability; reference scale; laser tracking interferometric; length measurement; layout; Combination optimization;
D O I
10.1117/12.2683892
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In order to improve the accuracy of the traditional laser tracking interferometric length measurement method and make the traceability of the datum ruler more reliable, a datum ruler measurement optimization method under multi-attitude is proposed in the paper. The method firstly constructs a multi-attitude datum ruler layout on the basis of traditional laser tracking interferometric length measurement, and collects the measurement information in different datum ruler directions under the layout by a laser tracker, and then adopts the weight-based optimization strategy to optimize the combination of measurement data, and then outputs the measurement results and carries out the analysis of the error source and the evaluation of the uncertainty, and finally conducts experimental analysis on the datum ruler with an accuracy of 1000mm based on the optimization scheme. Finally, based on this optimization scheme, an experimental analysis is carried out on the 1000mm datum ruler, and compared with the CMM method with higher accuracy, the En value is 0.1, which verifies the reasonableness of the uncertainty assessment, and it is found through experimental comparisons that the reference lengths output from the measurement optimization scheme with multiple postures are more reliable than those with single postures. The optimization method provides a new calibration scheme for achieving the traceability of the measurement value of high-precision large-size reference ruler, which has good practicality and certain guiding significance.
引用
收藏
页数:10
相关论文
共 50 条
  • [41] Measurement Error Detection for Calibration Standards Based on Cluster Analysis
    Zhou, Jiefeng
    Zhang, Ling
    Chen, Ziyang
    Li, Er-Ping
    2024 54TH EUROPEAN MICROWAVE CONFERENCE, EUMC 2024, 2024, : 948 - 951
  • [42] Research on Digital Image based Displacement Measurement Method
    Hong, Niansong
    TRENDS IN CIVIL ENGINEERING, PTS 1-4, 2012, 446-449 : 3399 - 3404
  • [43] The Research of a Stress Measurement Method Based on the Amorphous Alloy
    Shi Yanping
    Chen Jiping
    ISTM/2009: 8TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-6, 2009, : 2226 - 2229
  • [44] Research of object microimpurtity measurement based on Stroboflash method
    Zou Ji
    Wang Lirong
    Zhang Chao
    Bai Duanyuan
    ISTM/2007: 7TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-7, CONFERENCE PROCEEDINGS, 2007, : 4180 - 4183
  • [45] Research of Welding Deformation Measurement Based on Visual Method
    Huang, Jiankang
    Lu, Lihui
    Wu, Xiaoliang
    Shi, Yu
    Fan, Ding
    MANUFACTURING ENGINEERING AND AUTOMATION I, PTS 1-3, 2011, 139-141 : 2093 - +
  • [46] Analysis and evaluation method for linpack benchmark
    Du, Yun-Fei
    Yang, Can-Qun
    Wang, Feng
    Yi, Hui-Zhan
    Dongbei Daxue Xuebao/Journal of Northeastern University, 2014, 35 : 102 - 107
  • [47] Research on Liquid Flow Measurement Method Based on Heat Transfer Method
    Qin, Hongwei
    Dang, Ruirong
    Dang, Bo
    WATER, 2023, 15 (06)
  • [48] Research on water content measurement method based on heat transfer method
    Qin, Hongwei
    Dang, Bo
    Dang, Ruirong
    Liu, Guoquan
    HELIYON, 2024, 10 (11)
  • [49] Research of neural network algorithm based on factor analysis and cluster analysis
    Shifei Ding
    Weikuan Jia
    Chunyang Su
    Liwen Zhang
    Lili Liu
    Neural Computing and Applications, 2011, 20 : 297 - 302
  • [50] Research of neural network algorithm based on factor analysis and cluster analysis
    Ding, Shifei
    Jia, Weikuan
    Su, Chunyang
    Zhang, Liwen
    Liu, Lili
    NEURAL COMPUTING & APPLICATIONS, 2011, 20 (02): : 297 - 302