Causal approaches and fuzzy logic in FDI of Bond Graph uncertain parameters systems

Abstract

In this paper, two isolation methods issued from FDI and AI approaches are compared. These methods are interested with bond graph (BG) modeled uncertain parameters systems. Residuals are generated from the Diagnostic Bond Graph (DBG). Detection is based on fuzzy logic approach and its different parameters are determined off-line. By exploiting the causal properties of the BG model, two isolation methods are proposed: Fault Signature Matrix (FSM) and causal paths covering of the causal graph. A simulation example is provided to show the performances of the proposed methods.