  In this paper an on-line multiple faults detection approach is first of all
proposed. For efficiency, an optimal design of membership functions is
required. Thus, the proposed approach is improved using Particle Swarm
Optimization (PSO) technique. The inputs of the proposed approaches are
residuals representing the numerical evaluation of Analytical Redundancy
Relations. These residuals are generated due to the use of bond graph modeling.
The results of the fuzzy detection modules are displayed as a colored causal
graph. A comparison between the results obtained by using PSO and those given
by the use of Genetic Algorithms (GA) is finally made. The experiments focus on
a simulation of the three-tank hydraulic system, a benchmark in the diagnosis
domain.
