A Detection and Identification Method Based on Machine Vision for Bearing Surface Defects

被引:12
作者
Gu, Zhengyan [1 ]
Liu, Xiaohui [2 ]
Wei, Lisheng [3 ]
机构
[1] Anhui Polytech Univ, Sch Elect Engn, Wuhu, Peoples R China
[2] Shanghai Oushuo Intelligent Packaging Technol Co, Shanghai, Peoples R China
[3] Anhui Key Lab Elect Drive & Control, Wuhu, Peoples R China
来源
2021 INTERNATIONAL CONFERENCE ON COMPUTER, CONTROL AND ROBOTICS (ICCCR 2021) | 2021年
关键词
machine vision; canny algorithm; support vector machine; bearing surface defects;
D O I
10.1109/ICCCR49711.2021.9349370
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In view of the disadvantages of manual testing of bearing surface defects in the bearing production process, an automatic detection and identification method of bearing surface defects based on machine vision is proposed. Firstly, the source image is pre-processed by gamma correction algorithm, and the Canny algorithm is improved by adaptive selection of the Canny algorithm based on iterative threshold segmentation method and Ostu algorithm to improve the integrity and precision of the segmentation of bearing surface defects. The experimental results show that the method can be accurately detected of bearing surface defects, and the defect recognition rate has reached 93.33%.
引用
收藏
页码:128 / 132
页数:5
相关论文
共 16 条
  • [1] Chen Hao, 2018, J INSTRUM, V39, P198
  • [2] Chen J. G., 2018, MODULAR MACHINE TOOL, P82
  • [3] Support vector machine classification and validation of cancer tissue samples using microarray expression data
    Furey, TS
    Cristianini, N
    Duffy, N
    Bednarski, DW
    Schummer, M
    Haussler, D
    [J]. BIOINFORMATICS, 2000, 16 (10) : 906 - 914
  • [4] Gao N., 2018, COMPUTER DIGITAL ENG, V46, P2347
  • [5] Mobile Application Detection of Road Damage using Canny Algorithm
    Gunawan, G.
    Nuriyanto, Heri
    Sriadhi, S.
    Fauzi, Achmad
    Usman, Ari
    Fadlina, F.
    Dafitri, Haida
    Simarmata, Janner
    Siahaan, Andysah Putera Utama
    Rahim, Robbi
    [J]. 1ST INTERNATIONAL CONFERENCE ON GREEN AND SUSTAINABLE COMPUTING (ICOGES) 2017, 2018, 1019
  • [6] [郭慧 Guo Hui], 2018, [东华大学学报. 自然科学版, Journal of Donghua University. Natural Science Edition], V44, P635
  • [7] [何俊 HE Jun], 2009, [计算机工程与科学, Computer Engineering and Science], V31, P58
  • [8] Liu Lixia, 2019, Computer Engineering and Applications, V55, P54, DOI 10.3778/j.issn.1002-8331.1811-0180
  • [9] Luo T B, 2018, MECH ELECT ENG, V35, P148
  • [10] Okwuashi Onuwa, 2020, PATTERN RECOGN, P103