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We present a general architecture for the monitoring and diagnosis of largescale sensor-based systems with real time diagnostic constraints. Thisarchitecture is multileveled, combining a single monitoring level based onstatistical methods with two model based diagnostic levels. At each level,sources of uncertainty are identified, and integrated methodologies foruncertainty management are developed. The general architecture was applied tothe monitoring and diagnosis of a specific nuclear physics detector at LawrenceBerkeley National Laboratory that contained approximately 5000 components andproduced over 500 channels of output data. The general architecture isscalable, and work is ongoing to apply it to detector systems one and twoorders of magnitude more complex.

Management of Uncertainty in the Multi-Level Monitoring and Diagnosis of the Time of Flight Scintillation Array