Interface - The Journal of Wheel/Rail Interaction

WAYSIDE LOAD DETECTION

Using Wayside Load Detectors for Preventive Vehicle Maintenance (continued)

The performance criteria can be based on the distribution extremes found in the performance data or by a known and predetermined limit. A combination of both methods is used at WMATA. A threshold based on distribution extremes would typically look at the 99th or 99.9th percentile. This would be adjusted according to the actual data’s value at these points, along with the expected volume of vehicles that would be flagged by the criteria level. The volume of alerts, and therefore the criterion threshold, must not generate a list of vehicles that exceeds existing resources — either those of the shop personnel or the maintenance facility.

The primary metric monitored at WMATA is the L/V ratio. An 0.40 L/V is characterized as a high-severity hit; an 0.30 L/V is considered a medium-severity hit. A multi-hit criterion is used to eliminate random single readings at these levels and to control the volume of alerted vehicles. Medium- and high-severity alerts are triggered when a wheel records events in 6 of 10 passes over the detector.

Multi-hit criteria are based on data analysis and the results of teardowns and inspections. Experience has shown that repeated and measured poor performance is a sure indicator of vehicles requiring maintenance. Requiring multiple hits at the appropriate (possibly lowered) threshold prioritizes maintenance requirements and controls the volume of vehicles scheduled for maintenance. Further prioritization can identify the "worst of the worst" vehicles and schedule maintenance programs for them.

After initial monitoring and data analysis, five vehicles were flagged for performance issues, which included worn wheels, worn side bearings, inadequate car leveling and worn leveling valves, and worn bushings. Certain rail cars exhibited "abnormal" (sharp and high flange) wheel wear at the left side of the R-end truck axles, as shown in Figure 3. Sharp flanges are problematic in that they can interfere with the gauge-face lip on worn rail (see Figure 4), which could lead to a wheel-climb derailment (although no derailment occurred).

Following corrective actions, the vehicles' dynamic signatures were monitored to assess the success of each specific repair. Each vehicle's pre- and post-maintenance dynamic response was analyzed. Figure 5 shows one car's pre-maintenance dynamic signature in which axle 4 of the R-end truck is in violation of specified criteria. Corrective action included side bearing replacement, re-leveling and wheel re-truing. Maintenance actions were staggered to assess the dynamic signature and impact of each corrective action (see Figure 6).

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