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
Time-to-failure forecasting

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).

Multi-scenario forecasting

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.