A Focused, Context-Sensitive Approach to Monitoring

Abstract

We address two issues which arise in the task of detecting anomalous behavior in complex systems with numerous sensor channels: how to adjust alarm thresholds dynamically, within the changing operating context of the system, and how to utilize sensors selectively, so that nominal operation can be verified reliably without processing a prohibitive amount of sensor data. Our approach involves simulation of a causal model of the system, which provides information on expected sensor values, and on dependencies between predicted events, useful in assessing the relative importance of events so that sensor resources can be allocated effectively. 1. The Monitoring Problem Timely detection of anomalous behavior is essential for the continuous safe operation and longevity of aerospace systems. The pilot of a jet aircraft must be aware of any conditions which may affect thrust during the critical moments of takeoff. The thermal environment onboard Space Station Freedom must be carefully controlled to provide uninterrupted life support for the crew. The Mars Rover must react quickly to an unpredictable environment or the mission may come to an abrupt conclusion. Monitoring a physical system involves a number of problem-solving tasks. Dvorak, in his survey of work on expert systems for monitoring and control [Dvorak 87], lists among these tasks recognizing abnormal conditions, combining sensory information into a picture of the global state of a system, isolating faults, predicting both normal and faulted behavior, and maintaining safe operation in the presence of faults. In addition, decisions