The Adaptive Remaining Useful Life Estimator (ARULE) is a sophisticated predictive analytics tool designed to forecast key indicators such as Remaining Useful Life (RUL), State of Health (SoH), and Prognostic Horizon (PH) in complex systems. ARULE is versatile, handling electrical, mechanical, and electro-mechanical fatigue damage through its advanced condition-based monitoring and data analysis techniques. Utilizing a proprietary approach involving Extended Kalman Filtering, the system processes condition-based feature data to offer early warnings on potential failures.
ARULE's interactive graphical user interface (GUI) allows users to upload and process data streams for target systems, enhancing the overall maintenance and health management strategies. The software platform supports defining user-specific parameters for efficient data analysis, delivering prognostic estimates that guide the maintenance of systems based on actual conditions rather than arbitrary timelines.
This tool is an integral part of Ridgetop's Sentinel Suite, bolstering the predictive capabilities of Sentinel Power, Motion, and IT modules. By applying ARULE, industries can maintain operational systems more effectively, reducing downtime and optimizing performance across applications like power supply systems, battery management, and industrial automation.
