3-D measurement and evaluation of surface texture produced by scraping process

被引:13
|
作者
Fan, Kuang-Chao [1 ]
Torng, Jingsyan [2 ]
Jywe, Wenyuh [3 ]
Chou, Rui-Chen [1 ]
Ye, Jyun-Kuan [1 ]
机构
[1] Natl Taiwan Univ, Dept Mech Engn, Taipei, Taiwan
[2] Nanya Inst Technol, Dept Mech Engn, Chungli, Taiwan
[3] Natl Formosa Univ, Dept Automat Engn, Huwei, Taiwan
关键词
Scraped surface; Surface quality parameter; Image measurement system; Laser focus probe system; 3-D topography; OPTICAL ACCELEROMETER; SYSTEM; PROBE;
D O I
10.1016/j.measurement.2011.11.006
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The scraping process involves traditional manual work and is an important technique for producing flat bearing surfaces with lubricating grooves on a sliding surface. In order to meet the requirements of precision engineering, the scraped surface should have an equally distributed pattern with a required number of high points per unit area while retaining good flatness. In the machine tool manufacturer's workshop, however, the quality inspection of scraped surfaces still depends on human eyes. In this study, a 2-D evaluation system is first developed using image processing so that the peak points per area of square inch (PPI) and the percentage of points (POP) can be quantified as parameters. A vision-assisted laser focus probe system is then developed to measure the 3-D form of the scraped profiles. The laser probe is made of a DVD pickup head based on the astigmatic principle. Driven by an XY stage, the entire scraped profile can rapidly be scanned. The quality of the scraped surface can thus be interpreted in a more scientific manner. Based on the measured 3-D data, new evaluation methods are proposed for five parameters, namely the PPI, POP, height of points (HOP) or depth of surroundings (DOS), flatness, and oil retention volume. Experiments show that the 3-D system is consistent with the 2-D system. It not only reveals more surface quality parameters but also uncovers more characteristic surface phenomena than the 2-D image system. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:384 / 392
页数:9
相关论文
共 50 条
  • [41] 3-D surface fitting
    UCO, Lick Observatory, United States
    Sci. Comput., 2007, 10 (09):
  • [42] 3-D surface integration in structured light 3-D scanning
    Long, Xi
    Zhong, Yuexian
    Li, Renju
    You, Zhifu
    Qinghua Daxue Xuebao/Journal of Tsinghua University, 2002, 42 (04): : 477 - 480
  • [43] Development of an Optical Surface Characterization Sensor for Simultaneously Measuring Both 3-D Surface Texture and Mechanical Properties
    Shen, Yantao
    Wang, Yongxiong
    Zaklit, Josette
    2010 IEEE SENSORS, 2010, : 1892 - 1895
  • [44] Spectral analysis for automatic 3-D texture generation
    Ghazanfarpour, D.
    Dischler, J.M.
    Computers & Graphics (Pergamon), 1995, 19 (03):
  • [45] Coding of dynamic texture for mapping on 3-D scenes
    DeKnuydt, B
    Desmet, S
    Van Eycken, L
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 1999, 9 (02) : 210 - 217
  • [46] 3-D measurement of 2-D jet by 3-D 3-C SPIV
    Ninomiya, Nao
    Tanaka, Yukihisa
    Sotome, Satoshi
    Eda, Masahide
    Watanabe, Atsushi
    JOURNAL OF VISUALIZATION, 2019, 22 (02) : 305 - 312
  • [47] 3-D measurement of 2-D jet by 3-D 3-C SPIV
    Nao Ninomiya
    Yukihisa Tanaka
    Satoshi Sotome
    Masahide Eda
    Atsushi Watanabe
    Journal of Visualization, 2019, 22 : 305 - 312
  • [48] Texture-based 3-D brain imaging
    Saladi, S
    Pinnamaneni, P
    Meyer, J
    2ND ANNUAL IEEE INTERNATIONAL SYMPOSIUM ON BIOINFORMATICS AND BIOENGINEERING, PROCEEDINGS, 2001, : 136 - 143
  • [49] Objective breast symmetry evaluation using 3-D surface imaging
    Eder, Maximilian
    v. Waldenfels, Fee
    Swobodnik, Alexandra
    Kloeppel, Markus
    Pape, Ann-Kathrin
    Schuster, Tibor
    Raith, Stefan
    Kitzler, Elena
    Papadopulos, Nikolaos A.
    Machens, Hans-Guenther
    Kovacs, Laszlo
    BREAST, 2012, 21 (02): : 152 - 158
  • [50] 3-D surface quality evaluation based on graphics processing unit
    Cao, Yanlong
    Xu, Peng
    Jin, Lu
    Yang, Jiangxin
    Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural Machinery, 2012, 43 (03): : 219 - 222