Visual modeling of surface structure geometric features of mechanical parts based on boundary data mining and wireless computing

Feng Wu () and Jie Yao
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Feng Wu: Hunan Mechanical and Electrical Polytechnic
Jie Yao: Hunan Mechanical and Electrical Polytechnic

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 4, No 32, 1964-1975

Abstract: Abstract Visual modeling of surface structure geometric features of mechanical parts based on boundary data mining and wireless computing is essentially discussed in this manuscript. This paper establishes a method for reducing the degree of the uncertainty of the rough set boundary elements with the integration of the communication models. The method selects the appropriate coverage formation rule from the minimum coverage generated by the attribute reduction according to the statistical rule of the boundary element. In our model, the novelty can be listed as follows. (1) The cluster boundary can be obtained by detecting data objects with such features in the data set. (2) The multi-scale information of the surface of the part is optimized and input into the CAD system to obtain the multi-scale shape information, including the surface point cloud type, mesh model, surface model and solid model information of the parts at each scale, and the information is also transmitted to each other. The results of the simulation can prove the core effectiveness of the methodology. We simulate the proposed model under different scenarios and the comparison analysis has proven the efficiency and the robustness of the model. It is proven that the modelling efficiency has been 21.2% percent higher than the traditional model.

Keywords: Visual modeling; Geometric characteristics; Surface structure; Data mining; Wireless computing (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s13198-021-01611-z

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