Condition Based Maintenance in the USA
Our client, based in the USA, needed support with condition based maintenance on their freight railroad operation.
How our Products Helped
Our Centrix data platform was developed with usability in mind. We ensure that operators can gain the best possible benefit from their remote condition monitoring kit.
Continual agile development ensures that our Centrix platform continually evolves to meet clients needs. In this case, automating the alert configuration, as well as tagging alerts with suspected failure causes, meant that operators can make the best use of the system.
Locking performance, or “sticky locks,” are the most frequently observed issue. This is followed by motor commutation issues (e.g. worn motor brushes).
There were occasions when points motors stalled partway through a movement, but recovered so they could finish the movement and make detection. These faults were unlikely to be detected manually by signallers - the only indication would be a slightly extended swing time.
However, automated analysis in Centrix has ensured that this early warning is flagged for attention.
Results and Future Plans
The below image shows condition based monitoring data in action.
The red dots are automatically generated alarms, caused by unusual points motor behaviour. In this instance, this was due to a build up of ice on the systems.
The green dots are automatically generated tags. These identify maintenance being undertaken on the points location.
Further investigation of this site identified a sticky lock. This required maintenance attention to prevent further degradation, as well as ensuring there wasn't a negative impact on the railroads effectively running.
With access to data like this, our client was able to see the following results:
Improved understanding of asset performance:
Automated alert tagging enables operatora to identifywhat changes in Points machine performance are. This includes whether they have stalled, are stuck or are re-swung points.
Reliable alerts leading to accurate data:
These alerts are based on historic trends in performance at individual points machines. Trace splitting ensures that the peak inrush of current when a motor initiates does not affect these alerts.
Reduction in manual inspections:
With these automated monitoring tools in place, the need for routine manual inspections has been greatly reduced. This has saved both money and time. Situational awareness has also been increased via instant notification of events of interest.
