Abstract

Sensor-rich systems typically employ extensive signal processing techniques for fault detection and isolation tasks. Sensor-poor systems, on the other hand, require system models and analytical redundancy techniques to make diagonstic inferences. The increasing availability of inexpensive, batch-fabricated micro-controllers and MEMS sensors enables deployment of a multituted of sensors and microprocessors for control and diagnosing complex systems with hybrid discrete/continous behaviors and to reduce the computational requirements by focusing the signal processing algorithms. We demonstrate the approach on problems in reprographic copier path diagnosis.

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