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Light source optimization for automatic visual inspection of piston surface defects

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Abstract

This paper focused on the light source optimization for visual inspection of piston surface defects. A novel structured lighting system was developed to overcome the difficulties in the well-qualified imaging of tiny and random defects on the cylindrical smooth surface of components such as pistons. A polarized light-filtering based method was proposed to enhance the defect image contrast, enlarge the detection range, and suppress the noise of flawless area. It was both experimentally proven and theoretically proven effective by mathematical modeling of light intensity loss during light propagation. To analyze the influence of the pose and position of light sources on defect imaging quality, the system model for camera, light source, and workpiece was established, and the structure parameters of the lighting system were optimized to improve the brightness uniformity over the entire inspection region and lighting efficiency. Moreover, a soft lighting method was introduced as a subsidiary means of removing the surface noise at two ends of a piston. This method was found to be more effective compared with conventional software filtering algorithm. Finally, a case was examined. The defects on the automotive brake master piston surface were captured using the optimized light source system. A random sampling experiment with 600 specimens revealed that the false-positive rate was about 2.3%, and with no leak detection. The findings have been applied in the production, and it is expected to be referred in inspecting defects on other smooth cylindrical surfaces.

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Authors and Affiliations

  1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    L. M. Xu, Z. H. Jiang & Y. Chen

  2. Faw-Volkswagen Automotive Co., Ltd., Changchun, 130011, China

    Z. Q. Yang

Authors
  1. L. M. Xu
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  2. Z. Q. Yang
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  3. Z. H. Jiang
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  4. Y. Chen
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Correspondence to L. M. Xu.

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Xu, L.M., Yang, Z.Q., Jiang, Z.H. et al. Light source optimization for automatic visual inspection of piston surface defects. Int J Adv Manuf Technol 91, 2245–2256 (2017). https://doi.org/10.1007/s00170-016-9937-x

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  • DOI: https://doi.org/10.1007/s00170-016-9937-x

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