Abstract
Abstract The focus of this paper is the development of attributed graph representations of industrial processes. In this case energy attributes are used since it serves a data reduction purpose and allows for the consideration of multi-domain systems. Pattern recognition approaches towards FDI are considered advantageous due to their visual interpretation qualities. It is therefore envisaged that these attributed graphs can be used in a new innovative graph matching methodology to be able to detect and isolate faults. A two-tank thermo-fluid system is considered in this paper as a case study. An attributed graph containing exergy and energy flows is derived and from this graph node signature matrices are extracted that represent normal and fault conditions. Fault signatures are compared to the normal signature by deriving a cost matrix using a Heterogenous Eucledian-Overlap Metric (HEOM). Eigenvalues of the cost matrices are analysed in a qualitative way as a first stage of fault detection.
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