Our diagnostic approach to reliable insights
At KONUX, we do not simply provide data, but we take a diagnostic approach to understanding the health of an asset, such as trackbed. KONUX Switch, our S&C Predictive Maintenance System continuously captures data via IIoT devices, monitors the health of key switch components and analyses the patterns of asset conditions to anticipate failures. Sudden changes in the condition of an asset trigger a Smart Alert – a set of notifications that inform users when important events are detected in the system while factoring in relevant information such as S&C configuration, weather conditions, train speed, and traffic composition. Smart Alerts, however, are not triggered by simple threshold exceedances or change points in isolation but are algorithmically corrected for external dynamic effects, such as frost. For instance, if a sudden change is detected when the ballast is frozen due to low temperatures, our algorithms determine if a frost period is the likely reason for the change in data. We know that these data variations do not suggest immediate or permanent issues with trackbed health, but rather are a consequence of something like the temporary stiffening of the trackbed due to freezing weather conditions. By omitting an alert, we are saving inspection teams valuable time in the field and reducing unnecessary safety risk. Understanding the context and reason behind this anomalous data behaviour is essential to us being able to send only relevant alerts that can be acted on with trust. This is how we are able to ensure over 90% accuracy of our prediction.
The example below shows how our system has identified and flagged a frost period when the trackbed was frozen and we saw sudden changes in our data readings. Additionally, it shows that due to the temporary trackbed behaviour changes, prediction is suspended until the frost period has passed to not provide misleading readings or alerts. Frozen trackbed can have a temporary impact on our readings but importantly, is not related to the long-term health of the asset.