The Adaptive Remaining Useful Life Estimator (ARULE) is a sophisticated prognostic tool designed to deliver key predictions such as Remaining Useful Life (RUL), State-of-Health (SoH), and Prognostic Horizon (PH) of complex systems. Supporting predictive maintenance, the software processes a range of condition-based feature data to preemptively warn maintenance personnel about potential system failures.
ARULE incorporates advanced analytics, employing methods related to Extended Kalman Filtering (EKF) for accurate predictions, and is versatile enough to be applied across electrical, mechanical, and electromechanical domains. The software generates RUL, SoH, and PH estimates based on observed sensor data, ensuring timely maintenance and a reduction in unforeseen downtimes.
Featured within Ridgetop's Sentinel Suite, ARULE functions as a core component in various applications, providing insight into performance and health management of power supply, battery management, gearbox systems, and more. Its interactive graphical user interface makes it accessible for users across industries, allowing for comprehensive condition-based system evaluations.
