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Anomaly diagnostics and fault classification with prognostics is an active research topic, and real-time detection of anomalies and their classification has remained a critical challenge to be overcome. We developed an innovative, model-driven anomaly diagnostic and fault characterization system for electromechanical actuator (EMA) systems to mitigate catastrophic failures. The efficacy of the Model-based...
The current state of the art in electronic prognostic health management systems does not fully support detection, collection, and remediation of real-time faults. As a result, knowledge has not been captured from an actual platform failure mechanism. Thus, point-of-failure feedback cannot be applied by system designers or operators to improve lifecycle weak links in replacement platforms, or to strengthen...
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