A Novel Approach to Dynamic Fault Tree Analysis for Complex Redundant Systems with Partial Capacity Degradation

Dynamic fault trees (DFTs) have been used successfully to evaluate both the reliability and failure management of complex, redundant systems. Although existing static and DFTs are effective in determining overall failure probabilities and reliability, and even optimizing redundant resources, they do not have the ability to effectively characterize and optimize partially degraded components. This paper presents two new DFT gates, namely the Capacity Gate and the Preference Gate, which utilize dynamically updated capacity degradation profiles, failure probability distribution (PDF) profiles, and remaining useful life (RUL) predictions as inputs to the fault tree model and generate an optimized set of outputs, based on user preferences, that can be fully integrated with existing static and DFT gates. Using reaction wheel (RW) data from the Rosetta space mission, an experiment was conducted in which three fault trees were implemented and analyzed for effectiveness. These include a static fault tree (SFT), a DFT using existing gates, and a DFT using the new Capacity and Preference gates. This experiment validated that the new DFT gates can significantly extend mission lifetime and improve system reliability more than either a DFT or SFT that use existing fault tree gates.