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An ontology-based approach for decentralized monitoring and diagnostics

机译:基于本体的分散式监控和诊断方法

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Modern decentralized industrial applications demand the design of application-independent solutions for monitoring and diagnostics systems (MDSs) that exhibit a high degree of flexibility and re-utilization. To achieve this, we propose an ontology-based approach that adheres to the Meta Object Facility (MOF) paradigm for engineering and maintenance of MDSs. The key of our approach is to built a decentralized system architecture implemented on a semantic technology stack. Our architecture allows for storing plant engineering expert knowledge and the monitoring and diagnosis rules in formalized OWL models. The plant models can then be processed by the rules to compute monitoring states and diagnose causes of faults. This paper specifically focuses on a system implementation in alignment to requirements of the industrial domain. Based on these requirements, alternative knowledge-based tools and techniques are compared to evaluate the effectiveness of our approach.
机译:现代分散式工业应用程序要求针对监控和诊断系统(MDS)设计与应用程序无关的解决方案,这些解决方案具有高度的灵活性和可重复利用性。为实现此目的,我们提出了一种基于本体的方法,该方法遵循用于MDS的工程设计和维护的元对象工具(MOF)范例。我们方法的关键是构建在语义技术堆栈上实现的去中心化系统架构。我们的体系结构允许将工厂工程专家知识以及监视和诊断规则存储在正式的OWL模型中。然后可以通过规则处理工厂模型,以计算监视状态并诊断故障原因。本文专门针对符合工业领域要求的系统实现。根据这些要求,比较了基于知识的替代工具和技术,以评估我们方法的有效性。

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