Сибирский федеральный университет

Тип публикации: статья из журнала

Год издания: 2020

Идентификатор DOI: 10.1007/978-3-030-63319-6_33

Ключевые слова: knowledge base, model analysis, simulation modeling, spacecraft onboard equipment, testing

Аннотация: In this article we present graphical tools for models’ analysis using expert knowledge for solving functional tasks. We have studied special models of technical systems’ work logics simulation used in spacecraft onboard equipment production. We also took a close look at the modern approaches to intellectual models’ assessment and verification. We suggest our own method of model assessment on the basis of technical systems’ testing. The unicity of our method is that it allows not only to compare the quantitative characteristics of the equipment, but also to study logical sequences of the model’s actions. In the method, model’s structural elements (blocks) describing technical devices, switching interfaces and junctions defining the ways of information interaction – have been formalized. We provide an example of the onboard equipment’s command-and-software control model’s architecture. We suggest an algorithm for creating the control points and criteria of model analysis. We present graphical tools allowing to build functional dependencies of model’s elements visually and in an interactive mode. We provide tools for test monitoring. The results of tests are saved in a data storage and are used for automated comparison with simulation tests in the chosen control points. We suggest the criteria for interpretation of the results of data comparison. Our method substitutes a complicated manual process of knowledge base studying with the tools of automated digital support. This method is highly potential for scaling for analysis of big models.

Журнал: Advances in Intelligent Systems and Computing (см. в книгах)

Выпуск журнала: Т. 1295

Номера страниц: 368-376

ISSN журнала: 21945357

• Isaeva O. (Institute of Computational Modelling SB RAS)
• Nozhenkova L. (Institute of Computational Modelling SB RAS)
• Kulyasov N. (Institute of Computational Modelling SB RAS)
• Isaev S. (Institute of Computational Modelling SB RAS)

• Ядро РИНЦ (eLIBRARY.RU)