Knowledge-based Runtime Failure Detection for Industrial Automation Systems

[e-mail] 2010.

工业技术;计算机科学

Martin Melik-Merkumians ; Thomas Moser ; Alexander Schatten ; Alois Zoitl ; Stefan Biffl

Others  :  http://ceur-ws.org/Vol-641/paper_06.pdf
PID  :  42369

来源: CEUR

【 摘 要 】

Engineers of complex industrial automation systems need engineering knowledge from both design-time and runtime engineering models to make the system more robust against normally hard to identify runtime failures. Design models usually do not exist in a machine-understandable format suitable for automated failure detection at run-time. Thus domain and software experts are needed to integrate the fragmented views from these models. In this paper we propose an ontology-based engineering knowledge base to provide relevant design-time and runtime engineering knowledge in machine-understandable form to be able to better identify and respond to failures. We illustrate and evaluate the approach with models and data from a real-world case study in the area of industrial automation systems. Major result was that the integrated design-time and runtime engineering knowledge enables the effective detection of runtime failures that are only detectable by combining runtime and design-time information.