Fault diagnosis based on graphical tools for multi-energy processes

Abstract

To guarantee the safe operation of systems, it is necessary to use systematic techniques to detect and isolate faults for the purpose of diagnosis. The Fault Detection and Isolation (FDI) of nonlinear systems with coupling multiple energies became a difficult task. This why, we propose in this paper, the exploitation of the behavioral and structural properties of graphs (Bond Graph and Signed Directed Graph) combining with a Principal Component Analysis method (PCA). Therein, a coupled Bond Graph model is used for modeling methodology. A Signed Directed Graph (SDG) is then deduced. Fault detection is later carried out by graph coloring. The localization of the actual fault is performed based on a nonlinear PCA (NLPCA) and back/forward propagations on the SDG.The proposed approach is tested on the thermofluid case study and some simulations are provided.