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The Inspection module allows the detection and tracking of point defects on railway infrastructure by using data collected by recording and imaging wagons or lidars. Point defects are anomalies or localized degradation on the components of railway infrastructure, such as rails, sleepers, turnouts, bridges, tunnels, etc.


The spatial aspect

Cross-referencing spatial data collected by recording wagons, image capture systems, lidar or digital twins allows for a complete view of the environment surrounding railway infrastructure and to accurately identify point defects. Indeed, the combination of spatial data and infrastructure-related data allows for the detection of anomalies and degradation that could be related to spatial factors such as topography, geometry, vegetation or weather conditions. This approach also optimizes analysis and planning processes by combining data from different sources to assess the risks and criticality of point defects.

Multivariate aspect

By combining multivariate data, Inspection can study multiple variables simultaneously to better understand the interactions between these variables and identify anomalies and degradations that could be related to complex interactions. This approach allows for the detection of point defects with greater precision and a reduction in false positives.

The winning combination

By combining multivariate data with spatial and infrastructure-related data, Inspection can also evaluate the risks and criticality of punctual defects by taking into account complex interactions between the different variables. This approach optimizes maintenance planning processes by focusing on the most critical defects and prioritizing repair work based on risk.

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