Future military avionics systems will be depending more on built-intest (bit) for fault detection and isolation to meet stringent reliability, maintainability, and supportability goals. Recent experience indicates that bit is not meeting specification requirements in field operations, exhibits a high false alarm rate, has low reliability, and is unable to isolate failures to a single module. As a result, good unit removal rate has been high, reducing system availability and Increasing maintenance costs. Daina proposes to investigate the feasibility of an innovative, hierarchicallys structured, modular, and adaptive bit design concept compatible with s the next-generation avionics architecture. The use of statistical system state and parameter estimation techniques will be evaluated to determine their suitability for decreasing the false alarm rate. The proposed approach will be unique in that it will use external environment data, on-line reliability models, signal fusion, and artificial intelligence techniques to improve fault diagnosis. Successful completion of the phase I effort will provide foundation for the phase ii prototype development to further refine the selected bit implementation concepts.
