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  4. Vol 6, Issue 5, 2022

Study of Semantic Similarity Evaluation Methods for Combined Assembly Models

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DOI: 10.23977/acss.2022.060508 | Downloads: 15 | Views: 704

Author(s)

Xufan Wang 1, Hu Qiao 1, Sibo Hu 1, Liang You 1, Zhijie Wang 1

Affiliation(s)

1 School of Mechatronic Engineering, Xi'an Technological University, Xi'an, Shaanxi, 710021, China

Corresponding Author

Hu Qiao

ABSTRACT

In order to better realize the effective reuse of manufacturing information of 3D CAD models for manufacturing domain, a semantic-based research of combined assembly model retrieval method is proposed. Firstly, the labelled CAD model is transformed into a structured CAD model with the assembly features as the semantic object; then the attribute information for evaluating the similarity between two manufacturing features is extracted to construct a multi-attribute fused manufacturing feature similarity weighted evaluation model, which is used to construct a complete bipartite graph with manufacturing features as nodes; the optimal matching algorithm is used to calculate the optimal Finally, the optimal matching algorithm is used to calculate the similarity of the assembly model, which is used as the basis for evaluating the similarity of the model. The results show that the method can better achieve semantic-based combined assembly model retrieval, and can effectively support the reuse of manufacturing information of 3D CAD models in manufacturing oriented fields.

KEYWORDS

Combined assembly model retrieval, Assembly features, Similarity assessment

CITE THIS PAPER

Xufan Wang, Hu Qiao, Sibo Hu, Liang You, Zhijie Wang, Study of Semantic Similarity Evaluation Methods for Combined Assembly Models. Advances in Computer, Signals and Systems (2022) Vol. 6: 52-62. DOI: http://dx.doi.org/10.23977/acss.2022.060508.

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