Knowledge-based hierarchical modeling evaluation method for skeleton models

Sichao Liu; Jingzhou Dai; Ling Tian; Shaoke Nan; Qian Chen

doi:10.1117/12.3014789

4 March 2024 Knowledge-based hierarchical modeling evaluation method for skeleton models

Sichao Liu, Jingzhou Dai, Ling Tian, Shaoke Nan, Qian Chen

Proceedings Volume 12981, Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023); 1298121 (2024) https://doi.org/10.1117/12.3014789
Event: 9th International Symposium on Sensors, Mechatronics, and Automation (ISSMAS 2023), 2023, Nanjing, China

Abstract

The information of a skeleton model mainly includes spatial information and critical interface data. It is an important tool for constraining detailed design in the early stages of the design process. The design of complex products follows a top-down decomposition and refinement process, followed by bottom-up iterative validation. It involves a high level of knowledge intensity and uncertainty. Automating the hierarchical modeling and evaluation of skeleton models has become a fundamental problem to be solved in top-down design. This paper analyses the characteristics of skeleton models, and defines the component correlations in skeleton models based on the design knowledge representation in conceptual design. A hierarchical modeling and evaluation method for multi-level skeleton models based on the transitive closure is proposed. Finally, the effectiveness of the method is validated through the skeleton modeling and evaluation of the fairing on a rocket.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Sichao Liu, Jingzhou Dai, Ling Tian, Shaoke Nan, and Qian Chen "Knowledge-based hierarchical modeling evaluation method for skeleton models", Proc. SPIE 12981, Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023), 1298121 (4 March 2024); https://doi.org/10.1117/12.3014789

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