alexa Surface Micro Defect Detection of Tapered Rollers Based on Laser Diffraction
ISSN: 2090-4886

International Journal of Sensor Networks and Data Communications
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Research Article

Surface Micro Defect Detection of Tapered Rollers Based on Laser Diffraction

Li Cao1, Shuncong Zhong1,2*, Qiukun Zhang1 and Xinbin Fu3

1Laboratory of Optics, Terahertz and Non-destructive Testing & Evaluation, School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China

2Fujian Key Laboratory of Medical Instrument and Pharmaceutical Technology, Fuzhou 350108, P.R. China

3Xiamen Special Equipment Inspection Institute, Xiamen 361000, P. R. China

*Corresponding Author:
Shuncong Zhong
Laboratory of Optics
Terahertz and Non-destructive Testing & Evaluation
School of Mechanical Engineering and Automation
Fuzhou University, Fuzhou 350108, China
Tel: +86 591 87893
E-mail: [email protected]

Received date: September 28, 2015; Accepted date: November 16, 2015; Published date: November 20, 2015

Citation: Cao L, Zhong S, Zhang Q, Fu X (2015) Surface Micro Defect Detection of Tapered Rollers Based on Laser Diffraction. Sensor Netw Data Commun 4:129. doi: 10.4172/2090-4886.1000129

Copyright: © 2015 Cao L, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



A method based on laser diffraction was reported to improve the defect recognition accuracy of surface micro defect detection of tapered rollers. According to Fraunhofer diffraction theory, the fluctuations of the width of a tiny slit can be transformed to obvious changes of diffraction fringes, which can be employed to measure the micro surface defect of tapered rollers. These optical diffraction fringes were captured by a CCD camera, and subsequently were transmitted to a developed image processing system. The system includes image de-noising based on anisotropic diffusion, automatic extraction of fringe center lines by the derivative-sign binary image method, and analysis of the extracted fringe center lines for automatic defect detection. The experimental results demonstrated that the proposed method could magnify defect effect and therefore improve the accuracy of defect detection, making it attractive for industrial applications on tapered roller defect detection.


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