Dynamic Data-Driven Prognostics and Condition Monitoring of On-board Electronics

Degradation and failure prognostics in electronic systems is a growing requirement for both military and civilian sectors of 21st century. US Army's FCS will extensively use complex electronic systems. To enhance functionality, survivality, and mission success probability of FCS platforms while limiting the logistic footprint, efficient prognostic health management is essential. Qualtech Systems, Inc. in collaboration with Center for Advanced Life Cycle Engineering of University of Maryland proposes to develop a data-driven prognostics solution for on board electronic systems of FCS platform. The effort targets to develop algorithms to detect degradation signature, measure its severity and track its progression trend. An integral part of the effort is directed towards identification of sources of degradations and forecasted faults. Multi-disciplinary analytic techniques including signal processing, time series analysis, multi-variate statistics, neural networks, probabilistic decision fusion, graph theoretic and information theoretic algorithms are envisaged for attaining a reliable prognostic solution. Preliminary research and development will be performed targeting a selected on-board electronic system of an FCS platform. Testbench validation of the developed technology followed by deployment on target platform will be performed in subsequent phases of the work. The resultant prognostic solution will be generic having applicability across various military and commercial platforms.