Predictive Machine Learning Maintenance of VRLA Batteries based Uninterruptible Power Supply Systems

This thesis evaluates standard statistical and machine learning models for early fault detection for Valve Regulated Lead-Acid (VRLA) batteries in uninterruptible power supply (UPS) units. Unexpected battery failures in emergency support systems throughout CERN can endanger working personnel. Thus the minimization of downtime of such battery...