Abstract

In this paper, a new causal graph-based fault detection and isolation framework is developed. The Signed Directed Graph (SDG), as a graphical model for capturing process topology and connectivity to show the causal relationships between process variables, has been widely used in modeling and fault diagnosis of multi-energies systems. An SDG is usually built based on mathematical equations of process or based on process knowledge as described by piping and instrumentation diagrams, this is a complex and experience-dependent task. This paper introduces a methodology to built the SDG directly from Bond Graph. For the fault detection and isolation purpose, the generic model is able to deduce systematically qualitative fault signatures matrix from the qualitative redundancy relations. Whenever an abnormality was not isolated, a principal component analysis and a back/forward propagation through paths on the SDG model are combined so as to ameliorate the fault isolability.To highlight the efficiency and the performance of the developed algorithm, the multi-energy process case study is provided.

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