Qualitative Event-based Diagnosis with Possible Conflicts: Case Study on the Third International Diagnostic Competition

We describe two model-based diagnosis algorithms entered into the Third International Diagnostic Competition. We focus on the first diagnostic problem of the industrial track of the competition in which a diagnosis algorithm must detect, isolate, and identify faults in an electrical power distribution testbed in order to provide correct abort recommendations. Both diagnosis algorithms are based on a qualitative event-based fault isolation framework augmented with modelbased fault identification. Although based on a common framework, the fundamental difference between the two algorithms is that one is based on a global model for residual generation, fault isolation, and fault identification, whereas the other uses a set of minimal submodels computed using Possible Conflicts. We describe, compare, and contrast the two algorithms in terms of practical implementation and their diagnosis results.