Volume 15 Issue 3
May  2022
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LI Mao-yue, LIU Ze-long, ZHAO Wei-xiang, XIAO Gui-feng. Blade reflection suppression technology based on surface structured light on-machine detection[J]. Chinese Optics, 2022, 15(3): 464-475. doi: 10.37188/CO.2021-0194
Citation: LI Mao-yue, LIU Ze-long, ZHAO Wei-xiang, XIAO Gui-feng. Blade reflection suppression technology based on surface structured light on-machine detection[J]. Chinese Optics, 2022, 15(3): 464-475. doi: 10.37188/CO.2021-0194

Blade reflection suppression technology based on surface structured light on-machine detection

Funds:  Supported by National Natural Science Foundation of China (No. 51975169) ;the Fundamental Research Fundation for Universities of Heilongjiang Province (No. 2019-KYYWF-0204)
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  • Corresponding author: lmy0500@163.com
  • Received Date: 08 Nov 2021
  • Rev Recd Date: 07 Dec 2021
  • Accepted Date: 21 Jan 2022
  • Available Online: 26 Jan 2022
  • Publish Date: 20 May 2022
  • In the process of structured light detection, the thin-walled blade is easy to produce a strong reflection due to its low surface roughness, which affects the solution of the principal value of the fringe phase. As a result, it cannot accurately reconstruct the three-dimensional point cloud. In this paper, the blade in the machining process is taken as the research object, and an image enhancement process based on the Retinex algorithm is proposed to restore the information of the stripes in the position with the highest reflectivity. Firstly, the reflective characteristics of thin-walled blades are analyzed. The gray range and ideal gray value of the optimal exposure are calibrated experimentally. The camera response curve model of the aperture rotation angle and the image’s average gray level is determined, and the gray level interval of the optimal exposure is used as the detection condition by adjusting the aperture and exposure time. Secondly, the fringe image is processed based on the Retinex algorithm. The improved bilateral filter replaces the commonly used Gaussian filter, which effectively retains the edge information of the fringe while removing its illumination. Finally, monocular structured light detection is carried out on the thin-walled blade. The experimental results show that, for the fringe image processed by this proposed algorithm, the number of stripes detected by the Canny operator is the largest, the average growth rate of image information entropy is 18.21%, and the phase principal value error of the solution is the smallest. Through the deviation analysis with the standard point cloud detected by the handheld laser scanner, the positive and negative deviations of the point cloud are reduced to 0.0589 mm and −0.0590 mm, which are reduced by 44.6% and 44.1% compared with the deviation of the origin cloud, respectively, and the surface quality is significantly improved. The image enhancement algorithm proposed effectively suppresses the reflection of the metal surface in the process of surface structured light detection.

     

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