Adaptive Remaining Useful Life Estimator (ARULE) is a sophisticated tool designed for predictive analytics in complex systems. It accurately estimates prognostic quantities such as Remaining Useful Life (RUL), State-of-Health (SoH), and Prognostic Horizon (PH) by processing condition-based feature data. This allows maintenance teams to preemptively schedule repairs, reducing the risk of operational failures. ARULE leverages advanced prediction methods linked to Extended Kalman Filtering, making it versatile across electrical, mechanical, and electro-mechanical systems.
ARULE's intuitive graphical user interface (GUI) supports Condition-based Maintenance (CBM), Prognostic Health Management (PHM), and Integrated Vehicle Health Management (IVHM) applications. Users can easily upload and process condition-based data (CBD) to generate essential prognostics, which help in evidence-based system replacements. This approach streamlines maintenance, reduces costs, and promotes system reliability.
This estimator is part of the broader Sentinel Suite solution from Ridgetop Group, which integrates seamlessly with other components like sensors and application software. ARULE's utility is wide-ranging, applicable in power supply systems, battery management, industrial automation, and more, making it a cornerstone of effective health management strategies.
