Asset Health Management for Substations and
Expensive Grid Equipment
Adaptix self-learning algorithms constantly monitors and analyzes assets at the transmission and substation level. Adaptix has been shown to reduce maintenance costs by 20% while cutting the number of outages by 95%.
Multivariate time series analysis
Adaptix uniquely analyses and correlates virtually all available data – oil pressure, temperature, levels and
acoustic sensors – on the transformer in combination with load data meters and environmental variables.
Multi-mode anomaly detection, Failure identification and
Deploy and combine self-learning, supervised or semi-supervised machine learning tools to historically analyse assets’ behaviour, identify underlying patterns, reveal anomalies and predict failures and remaining useful life (RUL).
Similar situations can yield different outcomes. Adaptix comes with a powerful multi-scenario prediction engine to help the engineer assess all possible scenarios and select the optimal solution.