Our client, based in the USA, needed support with condition based maintenance on their freight railroad operation.
Read about the issues we worked to solve, how our technology helped and the results.
At a Glance
We supply points condition monitoring to a Class I freight railroad operator in Eastern USA.
The continual, agile development of our Centrix data platform has ensured that the operator has been able to automate detection of issues on Points machines.
The application of automated alarm threshold settings, as well as tagging traces with their suspected fault cause has allowed the operator to implement condition based maintenance. There have been significant financial savings and improved staff safety.
USA railroad infrastructure
Railroad infrastructure in the USA is used by a significant level of heavy freight trains. It is often located at geographically remote locations. This makes regular maintenance inspections expensive and challenging, despite them being very necessary.
Common points failures
The most common source of failure within the signalling and rail systems are points failures.
Required user knowledge
Using remote condition monitoring of points systems meant that issues could be identified prior to them having a significant impact on the railroads. However, the setting of alert levels, and the interpretation of alert meanings, required user knowledge and time.
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.