An architecture for the development of real-time fault diagnosis systems using model-based reasoning

Abstract

This article presents an architecture for implementing real-time telemetry-based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for off-line entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run-time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed off-line by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.