2023-06-10 00:00:00
(09/06/2023)
This predictive module is based on the application of algorithms to predict buckling and the consequences associated with the deformation of the tracks or structural failures as a consequence of factors such as temperature, among others. For the development of this tool, meteorological data, track geometry and a maintenance history are combined to identify risk points and critical moments in which the risk of buckling exceeds the pre-calculated limits within a period of time. time horizon of seven or ten days.
With the weather forecasts the temperature of the rail is estimated, which is considered one of the crucial factors in the origin of the buckling. Based on the relationship between temperature and the structural behavior of the road, the algorithm analyzes data in real time and generates detailed predictions. These forecasts provide infrastructure operators with the ability to take preventative and maintenance actions at the right places and times. In this way possible incidents are avoided, the efficiency of the system is improved and the availability of the exploitation of the roads will be increased.
Benefits
The objective of the implementation of this predictive module is to introduce new tools for more efficient and precise maintenance of the infrastructure. Among the benefits it provides are the improvement of security, the optimization of resources, the planning of speed limitations and the provision of information to take corrective and preventive measures.
predictive module
This project is an extension of the contract signed between ETS and Main Rail, both parties, for the implementation of a platform that manages the maintenance of the infrastructure and the analysis of track monitoring data from the Basque operator. It is a predictive module that was validated in the summer of 2022 in a first implementation in the Majorca rail network.
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