Flatness error measurement method based on line structured light vision

被引:0
|
作者
Liu S.-Y. [1 ]
Hou Y.-Q. [2 ]
Kou Y. [1 ]
Ren Z. [2 ]
Hu Z.-Y. [3 ,4 ]
Zhao X.-W. [2 ]
Ge Y.-P. [1 ]
机构
[1] School of Mechanical and Aerospace Engineering, Jilin University, Changchun
[2] School of Mechanical Engineering, Changchun University, Changchun
[3] School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou
[4] Production and Education Integration Development Center, Changchun Automobile Industry College, Changchun
关键词
flatness; line structured light vision; machine vision; tolerance measurement;
D O I
10.13229/j.cnki.jdxbgxb.20220050
中图分类号
学科分类号
摘要
Flatness is an important shape deviation. A flatness error measurement method was proposed based on line structured light vision technology for flatness measurement in the field of mechanical component manufacturing and processing. Firstly,the images of light strips were collected,and the spatial coordinates of the scanning points were obtained by the corresponding light plane equation for each position. Secondly,the evaluation methods for flatness errors in national standards was analyzed and a measurement algorithm for flatness errors was established based on geometric constraints. Finally,through the proposed method,the evaluation base plane and flatness errors were calculated using the spatial coordinates of the scanning points. In the experiment,the positioning surfaces of the insert molds are selected as the measured planes,and the measurement results obtained by visual measurement are compared with those obtained by the contact measurement method. The measurement error is less than 20 μm. The experimental results show that the measurement method proposed is feasible and improves the measurement efficiency of flatness error. © 2023 Editorial Board of Jilin University. All rights reserved.
引用
收藏
页码:3358 / 3366
页数:8
相关论文
共 18 条
  • [1] (2016)
  • [2] Li Ying, The design of photoelectric level gauge and the study of flatness error measurement method, (2019)
  • [3] Qiao Liang, Ran Qing, Gong Ke-an, Evaluation of uncertainty in measurement results of indication error of laser planar phase-shifting interferometer, Industrial Metrology, 30, 1, pp. 66-67, (2020)
  • [4] Wang Han-bin, Uncertainty evaluation for the CMM flatness measurement, Metrology & Measurement Technique, 46, 3, pp. 98-99, (2019)
  • [5] Shan Zhong-de, Zhang Fei, Nie Jun-gang, Et al., Study on the detection method and measurement system of head flatness error on non-contact detection, Journal of M echanical Engineering, 52, 20, pp. 1-7, (2016)
  • [6] Tan Qing-chang, Kou Ying, Miao Jian-wei, Et al., A model of diameter measurement based on the machine vision, Symmetry, 13, 2, (2021)
  • [7] Liu Rui-yuan, Wang Ze-yuan, Liu Xiao-min, Et al., Research on Visual Inspection of Appearance Defects of Automotive Precision Parts, 41, 3, pp. 192-196, (2020)
  • [8] Mikko Makela, Marja Rissanen, Herbert Sixta, Machine vision estimates the polyester content in recyclable waste textiles, Resources Conservation and Recycling, 161, (2020)
  • [9] (2005)
  • [10] Liu Bin, Wang Peng, Zeng Yong, Et al., Measuring method for micro-diameter based on structured-light vision technology[J], Chinese Optics Letters, 8, 7, pp. 666-669, (2010)