In this paper we apply a diagnosis methodology illustrated in Fig. 9, which combines fault detection, fault hypothesis generation, prediction, and monitoring. Observations that deviate are processed using the temporal causal graph to generate fault hypotheses and predict future behavior for each fault. These predictions are then monitored against new observations to refine the set of possible faults. Details of these algorithms appear in [10, 11].
Figure 9: The diagnosis process.