基于模型的系统工程中支持模型集成的面向服务方法

R. Chen, Guoxin Wang, Shouxuan Wu, Jinzhi Lu, Yan Yan
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引用次数: 0

摘要

当使用基于模型的系统工程(MBSE)开发复杂系统时,使用不同语法和语义的模型通常在异构环境中实现,这会导致难以实现跨整个生命周期的数据集成。具体来说,需要在不同建模工具的模型之间进行无缝交换,以支持系统生命周期活动,例如需求分析、功能分析、验证和确认。本文说明了一种面向服务的方法来支持基于模型的系统工程的模型集成,特别是在体系结构设计和系统验证之间。首先,提出了一套基于生命周期协作开放服务(Open Service of Lifecycle Collaboration, OSLC)的体系结构模型和仿真模型之间的语义映射规则,以支持技术资源(模型、数据、api)的形式化。然后开发OSLC适配器来将模型、数据和api转换为基于web的服务。服务由特定建模工具中的服务发现插件部署,用于模型信息交换。以六自由度机器人(RobotR3)系统的KARMA体系结构模型和Modelica仿真模型为例说明了该方法的可行性。我们从定性和定量两方面评价了该方法的有效性和效率。结果表明,该方法在模型和数据集成方面是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Service-oriented Approach Supporting Model Integration in Model-based Systems Engineering
When using Model-Based Systems Engineering (MBSE) to develop complex systems, models using different syntax and semantics are typically implemented in a heterogeneous environment which leads to difficulties to realize data integrations across the entire lifecycle. Specifically, seamless exchanges between models of different modeling tools are needed to support system lifecycle activities such as requirement analysis, function analysis, verification and validation. This article illustrates a service-oriented approach to support model integration for model-based systems engineering, especially between architecture design and system verification. First, a set of semantic mapping rules between architecture models and simulation models based on Open Service of Lifecycle Collaboration (OSLC) are proposed to support the formalization of technical resources (models, data, APIs). Then OSLC adapters are developed to transform models, data and APIs into web-based services. The services are deployed by a service discovering plug-in within a specific modeling tool for model information exchange. The approach is illustrated by a case study on KARMA architecture model and Modelica simulation model for a six-degree-of-freedom robot (RobotR3) system. We evaluate the availability and efficiency of this method from both qualitative and quantitative perspectives. The results show that our approach is effective in model and data integration.
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