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Robot automation grinding process for nuclear reactor coolant pump based on reverse engineering

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Abstract

The nuclear reactor coolant pump (NRCP) is the heart of the nuclear power plant. This paper focuses on robot automation grinding processing for NRCP, which includes scanning, point cloud processing, grinding trajectory generation, and quality evaluation system based on reverse engineering. In this work, firstly, the point cloud of NRCP is obtained by robotic scanner system of hand-eye calibration. Secondly, the research proposes a novel method for point cloud simplification, denoising, and boundary extraction base on k neighborhood octree structure. More important, the efficient trajectory generation of grinding relies on transforming point cloud into adaptive triangular mesh. Lastly, quality evaluation system can calculate the deviation between point cloud and qualified workpiece. And the further path is generated according to the deviation. Experiments show that the accuracy of “246” hand-eye calibration method is less than 0.02 mm. The method of point cloud processing has obvious efficiency advantages over other researchers’ algorithms. The final results indicate that the error of grinding is less than 3 mm and efficiency can be improved by 2.5 times compared with manual grinding.

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Funding

The authors are grateful for the support provided by National Natural Science Foundation of China (grant # 51775542) and National Natural Science Foundation of China (grants # 51605475).

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Authors and Affiliations

  1. Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, 110016, China

    Hongyao Zhang, Lun Li & Jibin Zhao

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Hongyao Zhang

Authors
  1. Hongyao Zhang
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  2. Lun Li
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  3. Jibin Zhao
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Correspondence to Hongyao Zhang.

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Zhang, H., Li, L. & Zhao, J. Robot automation grinding process for nuclear reactor coolant pump based on reverse engineering. Int J Adv Manuf Technol 102, 879–891 (2019). https://doi.org/10.1007/s00170-018-03230-8

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  • DOI: https://doi.org/10.1007/s00170-018-03230-8

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