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This paper presents a combined approach to fault diagnosis in discrete-time dynamic systems. The approach integrates classical and soft computing techniques. The typical methods based on signal models, and process models for residual generation are considered: parity equations, observers and parameter estimation. The role of integration of classical and intelligent techniques is enhanced. The performance of the proposed approach is analysed with application to a typical nonlinear feed-water system – the three-tank benchmark. The three typical fault scenarios (actuator and component faults) defined in the benchmark problem are tackle in this work.

A COMBINED APPROACH TO FAULT DIAGNOSIS IN DYNAMIC SYSTEMS - Application to the Three-Tank Benchmark