Another Tool for Predictive Maintenance

28 July 2009

Another function has been added to the already impressive array of rail inspection instrumentation developed by the progressive rail flaw detection systems (RFD) developer, CATER.

CATER (The Centre for Advanced Transport Engineering and Research) is based in Perth, Western Australia, and has a strong international reputation for providing tools to identify rail flaw trending.

The powerful post-processing analysis tool, rail intelligent permanent way analysis viewer (RIPWave), now incorporates GPS coordinates embedded in the collected data. The recorded information is graphically represented on a network map with positions of "artefacts of interest" accurately shown in their particular locations.

RIPWave already highlights the type of flaw, the size of flaw and position of potential flaws identified by the ultrasonic information. By adding this new functionality to the post-processing software, the spread of locations can be shown graphically.

In addition to the location, the severity and types of flaw are represented in different colours for ease of review. The operator/reviewer can then assess the flaw type, severity and spread of locations to make maintenance decisions based on need. Clusters of particular flaws can be targeted by maintenance field crews. This process is a more efficient way to reduce unnecessary maintenance time and money that could be spent in addressing more serious flaws in the rail environment.

Reports can be generated using Google Earth overlays which represent a general report of flaw location. Specialised electronic rail network maps can be used to give a more specific report of where particular flaw trending may be occurring. Both of these mapping methods generate an overview of rail flaw trending necessary for accurate predictions leading to a focused maintenance regime.

Condition monitoring is a major topic currently emphasised in asset management. The rail inspection industry is often required to provide methods of monitoring the condition of the rail environment in addition to simple flaw identification. With enough detailed information and using suitable post-processing tools, a network can identify trends related to its particular network. Targeted re-railing decisions, accurate flaw response and improved grinding programmes are some of the improved outcomes from genuine condition monitoring.

By targeted maintenance, fewer resources are wasted leading to improved rail continuity and safety. CATER expect a strong response from rail networks requiring predictive maintenance through enhanced recording of flaw identification and location. RIPWave is now more powerful to reduce rail network operating costs.

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