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A novel grinding path generation method for removing the parting line of large casting

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Abstract

To tackle the issues of low efficiency and inaccurate results in the automated grinding of large castings, this paper presents a pioneering technique for generating grinding paths. The method combines the capabilities of the random sample consensus (RANSAC) and iterative closest point (ICP) algorithms. The RANSAC is used for discovering local feature point clouds, while the ICP estimates geometric deviations due to shrinkage and expansion. The expansion–contraction similarity (ECS) is pivotal to this approach, facilitating direct generation of global grinding path points from scant local ones. After comparing outcomes to two other methodologies and conducting a robot casting component experiment, the effectiveness and superiority of this technique were proved.

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Funding

This research work was supported by the National Natural Science Foundation of China (Grant Nos. 62027812, 51875391 and 52275027).

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Authors and Affiliations

  1. Northwest Institute of Mechanical and Electrical Engineering, Xianyang, 712099, China

    Meng Wang

  2. School of Mechanical Engineering, Tianjin University, Tianjin, 300350, China

    Meng Wang, Yimin Song & Panfeng Wang

Authors
  1. Meng Wang
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  2. Yimin Song
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  3. Panfeng Wang
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Contributions

All authors contributed to the conception and design of the study. Experimental design, material preparation, data collection, and analysis were performed by Meng Wang and Yimin Song. The first draft of the manuscript was written by Meng Wang, and all authors commented on earlier versions of the manuscript. All authors read and approved the final version of the manuscript.

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Correspondence to Meng Wang.

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Wang, M., Song, Y. & Wang, P. A novel grinding path generation method for removing the parting line of large casting. Int J Adv Manuf Technol 131, 201–209 (2024). https://doi.org/10.1007/s00170-024-13121-w

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  • DOI: https://doi.org/10.1007/s00170-024-13121-w

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