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

Exploiting Particle Swarm Optimization in Multiple Faults Fuzzy Detection