Thomas J. Laffey, Scott M. Weitzenkamp, Jackson Y. Read, Simon A. Kao, James L. Schmidt
This paper describes a multi-tasking architecture for performing real-time monitoring and analysis using knowledge-based problem solving techniques. To handle asynchronous inputs and perform in real-time, the system consists of three or more distributed processes which run concurrently and communicate via a message passing scheme. The Data Management Process acquires, compresses, and routes the incoming sensor data to other processes. The Inference Process consists of a high performance inference engine that performs a real-time analysis on the state and health of the physical system. The I/O Process receives sensor data from the Data Management Process and status messages and recommendations from the Inference Process, updates its graphical displays in real time, and acts as the interface to the console operator. The distributed architecture has been interfaced to an actual spacecraft (NASA' s Bubble Space Telescope) and is able to process the incoming telemetry in "real-time" (i.e., several hundred data changes per second).