The paper focuses on a methodological study oriented towards the development of diagnostic tools for on-field operating solid oxide fuel cell (SOFC) systems. This work is motivated by the increasing demand for diagnostic techniques aimed at both increasing durability and fully exploiting SOFC benefits throughout system lifetime. Nowadays many SOFC diagnostic applications are available in lab-controlled environment, but few studies are proposed for on-field use. Main contribution of this work is thus the development of suited methodologies for detection and isolation of typical SOFC system faults. Fault tree analysis (FTA) is proposed as a tool for the isolation process. For each specific component, the most significant faults are correlated, via a top-down approach, to the corresponding symptom(s). The knowledge gained through the FTA is exploited to understand the mutual interactions among all devices within the entire SOFC system. Such an approach resulted in the definition of a fault signature matrix that conveniently links system-level symptoms to specific component faults. Such an approach is therefore suitable to perform fault detection and isolation (FDI) of an SOFC system as a whole.

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