VibeFly

VibeFly is a web + edge desktop app for condition monitoring and predictive maintenance of flywheel energy storage systems. It ingests high-frequency vibration, temperature, RPM, vacuum pressure, and power electronics telemetry from existing PLC/SCADA historians, then flags early warning patterns like bearing wear, rotor imbalance, vacuum leaks, and abnormal spin-down curves. The MVP focuses on practical reliability workflows: health scoring per unit, event timelines, and maintenance recommendations tied to evidence (trend plots and thresholds). It also generates concise incident reports for operators and OEM support, reducing back-and-forth and downtime. This is an AI + traditional app: AI is used for anomaly detection and remaining-useful-life estimates, but the product remains usable with simple rules/thresholds when data quality is poor. It’s built for industrial realities: noisy sensors, intermittent connectivity, and strict change-control environments.