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A robotic polishing parameter optimization method considering time-varying wear

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Abstract

In the automatic polishing process, the wear of polishing tools and the change of polishing parameters will affect the Preston coefficient, which makes it difficult to establish an accurate material removal model to achieve stable and excellent polishing quality. In this paper, a robotic polishing parameter optimization method considering time-varying wear is proposed to address these issues. First, combining the rich information in the theoretical modeling method with the data-driven regression method, a material removal regression model incorporating prior knowledge is proposed, which greatly reduces the large amount of experimental data required by the original regression model. The proposed model is able to track the wear variation of the sandpaper as well as the effect of polishing parameters. Then, based on the proposed prediction model, the genetic algorithm is used to optimize the polishing parameters in order to achieve better machining quality and less energy consumption. Finally, the experimental verification is carried out on the hybrid robot polishing test bench. The results show that the proposed material removal regression model incorporating prior knowledge has higher prediction accuracy and less required experimental data than existing models. The proposed robot polishing parameter optimization method can effectively compensate for tool wear and ensure the consistency of material removal during polishing while reducing energy consumption.

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Data availability

The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

Some or all models, or code generated or used during the study, are available from the corresponding author by request.

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Funding

This work was financially supported by the National Science and Technology Major Project (2017ZX04021001-004).

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Authors and Affiliations

  1. Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, 300354, China

    Qianjian Zheng, Juliang Xiao, Chao Wang, Haitao Liu & Tian Huang

Authors
  1. Qianjian Zheng
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  2. Juliang Xiao
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  3. Chao Wang
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  4. Haitao Liu
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  5. Tian Huang
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Contributions

QZ came up with the original idea, designed the research, collected the data, and wrote the manuscript. The improvement of the article was completed under the guidance of JX. WC provides support for relevant experimental materials, techniques, and venues. HL made significant contributions to the analysis process. TH provided theoretical assistance. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Juliang Xiao.

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Zheng, Q., Xiao, J., Wang, C. et al. A robotic polishing parameter optimization method considering time-varying wear. Int J Adv Manuf Technol 121, 6723–6738 (2022). https://doi.org/10.1007/s00170-022-09788-8

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  • DOI: https://doi.org/10.1007/s00170-022-09788-8

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