A feature quantification method based on binary tree oriented for constructional frameset of heterogeneous models

Nana Shen; Chun Zhao; Wenzheng Liu; Yue Liu; Hao Yang

doi:10.1117/12.2652469

10 November 2022 A feature quantification method based on binary tree oriented for constructional frameset of heterogeneous models

Nana Shen, Chun Zhao, Wenzheng Liu, Yue Liu, Hao Yang

Author Affiliations +

Proceedings Volume 12331, International Conference on Mechanisms and Robotics (ICMAR 2022); 123310G (2022) https://doi.org/10.1117/12.2652469
Event: International Conference on Mechanisms and Robotics (ICMAR 2022), 2022, Zhuhai, China

Abstract

To meet the more demanding requirements of the modeling and simulation technology in various fields, more diverse modeling languages and methods are emerging, which in turn makes it more challenging to integrate and reuse heterogeneous models for field applications. Therefore, it is necessary to extract a constructional frameset of heterogeneous models based on a unified modeling language. This paper presents a method of constructional frameset extraction and feature quantization to address the issues of matching, classification, and composition of multi-domain heterogeneous models. Firstly, heterogeneous models are converted into unified models, which are described by X language. Then, the structural features of each X model are extracted to be incorporated into a predefined template. Then the template can be quantified in the form of a binary tree. The sequence obtained by inorder transversal of the binary tree can be a quantified feature of the template. All the model templates make up the constructional frameset of multi-domain heterogeneous models. The results show that the proposed method can abstract the features of multi-domain heterogeneous models and support a constructional frameset library to rapid modeling, integration, and reuse.

Citation Download Citation

Nana Shen, Chun Zhao, Wenzheng Liu, Yue Liu, and Hao Yang "A feature quantification method based on binary tree oriented for constructional frameset of heterogeneous models", Proc. SPIE 12331, International Conference on Mechanisms and Robotics (ICMAR 2022), 123310G (10 November 2022); https://doi.org/10.1117/12.2652469

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