Page 32 - 360.revista de Alta Velocidad - Nº 5

Coca, Marcos

The removal of a significant number of maintenance interventions at first-level visits comes
true, especially those associated with integrity and wear checking, thus improving the fleet
availability by reducing the immobilization periods.
At infrastructure level, one another case-study comes from predictive algorithms already
developed for RFI Point Machines after analyzing more than 100,000 maneuvers in 20 devices,
allowing the identification and validation of suitable Health Indicators. Detection patterns
of lack of lubricant, presence of obstacles and non-compliant deformations were identified,
making possible to update the maintenance strategy.

There could come also changes in the maintenance processes when a new device is integrated
to complement and sometimes provide more accurate information to the maintenance activity.
Specific monitoring devices allow remote data collection from equipment maintenance ports,
often providing wider and more precise information than the one retrieved from the train
control system.
Maintenance data currently collected from AVE S100 Motor Blocks are being managed to
develop and validate models for traction degraded operation, so that automatic alerts could
be configured and the root cause for possible failures could be more rapidly investigated,
improving troubleshooting and providing means to enhance the fleet availability.

30 360.revista de alta velocidad