Structural Problem Reduction for Set-based Fault Diagnosis

Complex technical systems, e. g. chemical plants, are prone to equipment failures. To ensure the safe operation of such systems, the occurrence of a fault has to be reliably detected. Set-based validation and identification methods are well suited for this problem as they are flexible with respect to modeling uncertainties and as they can provide guaranteed results. One of the main challenges of set-based approaches is, however, the complexity of underlying computations. Simplifying the problem formulation via a suitable approximation of the model is one way to reduce the computational effort. However, to retain the ability to diagnose faults, the underlying structure of the model has to be taken into account. We present a method to reduce the problem formulation based on causal reasoning and lifting technique that orders the system states according to the effects of occurring faults. We present an approach to derive such a reduction and illustrate its application considering two 5-tank configurations.