Diagnosing an Analog Feedback System Using Model-based Reasoning

Automated troubleshooting using design information has been the goal of substantial research in recent years. A number of model-based approaches have been proposed, but have typically been applied to examples limited in size and/or complexity. Systems containing feedback loops are panicularly troublesome. In this work, the approach developed by de Kleer/Williams has been extended to diagnose steady state faults in an analog feedback system. A prototype system is described which automatically diagnoses a target system given only information on the connectivity and component transfer functions. The prototype detects inconsistencies among measurements, calculates single and multiple fault hypotheses and their probabilities, and suggests the best next measurement.