An Intelligent Fault Detection and Isolation Architecture for Antenna Arrays

This article describes a general architecture for fault modeling, diagnosis, and isolation of the DSN antenna array based on computationally intelligent techniques (neural networks and fuzzy logic). It encompasses a suite of intelligent test and diagnosis algorithms in software. By continuously monitoring the health of the highly complex and nonlinear array observables, the automated diagnosis software will be able to identify and isolate the most likely causes of system failure in cases of faulty operation. Furthermore, it will be able to recommend a series of corresponding corrective actions and effectively act as an automated real-time and interactive system supervisor. In so doing, it will enhance the array capability by reducing the operational workload, increasing science information availability, reducing the overall cost of operation by reducing system downtimes, improving risk management, and making mission planning much more reliable. Operation of this architecture is illustrated using examples from observables available from the 34-meter arraying task.