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A two-stage vision-based method for measuring the key parameters of ball screws
Affiliation:Department of Mechanical Engineering, Marri Laxman Reddy Institute of Technology and Management, Hyderabad 500 043, India;Koszalin University of Technology, 75-620 Koszalin, 15-17 Raclawicka Str., Poland;School of Mechanical Engineering & Automation, Northeastern University, Shenyang, Liaoning 110819, PR China;Department of Industrial Engineering (DIIn) – University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, SA, Italy
Abstract:Ball screws are crucial for improving the reliability and interchangeability of transmission mechanical systems; however, existing contact measurement methods that utilise stylus contact are not efficient, which precludes their use for rapid in-situ geometry evaluation. This paper presents a vision-based two-stage method for rapid measurement of key parameters (raceway arc radii and centre distance) of ball screws. The edge contour information is extracted from the acquired image using the dual-tree complex wavelet transform and non-maximal suppression. In the matching stage, a shape-matching algorithm is used for detecting approximate geometrical centres of raceway arcs. The refinement stage, on the other hand, is implemented for acquiring precise dimensional results. Furthermore, the method of averaging multiple measurements is performed to suppress random noise. A comparative experiment is presented to validate the robustness of the proposed method. Based on experimental results, the calculated mean absolute errors in the measurement of the two raceway arc radii and the centre distance are found to be 0.0082 mm, 0.0079 mm and 0.0055 mm, respectively. This study therefore paves the way for key parameter measurement without removing ball screws.
Keywords:Ball screw  Dual-tree complex wavelet transform  Machine vision  Non-maximum suppression  Shape matching
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