Interface - The Journal of Wheel/Rail Interaction

WAYSIDE LOAD DETECTION

Using Wayside Load Detectors for Preventive Vehicle Maintenance (continued)

Fleet Assessment and Impact of New Vehicles
Data collected on WMATA's existing vehicles provided important information on overall fleet performance. Testing showed that:

• The oldest series (type 1) vehicles experience higher mean and medium single-wheel L/V ratios.

• Overhauled (type 2 and type 3) vehicles experience lower mean and medium single-wheel L/V ratios, regardless of the truck design.

• Trucks on the 1000 and 5000 series vehicles generate lower mean and medium single-wheel L/V ratios than trucks on the 2000 through 4000 series (types 2, 3, and 4) vehicles.

• Vehicle types 4 and 5 generate the highest maximum singe-wheel L/V ratios. Vehicle type 4’s high maximum singe-wheel L/V ratio is due to a midlife overhaul, while the type 5’s high maximum single-wheel L/V ratio is due to high mileage between wheel truing intervals (worn wheels) and car leveling issues.

The dynamic signature of each vehicle series, including the new 6000 series, is being monitored to obtain better insight into the performance of each vehicle type and the condition of the fleet, overall. Beginning with WMATA’s 6000 series rail car procurement, specifications were modified to reduce lateral forces and thereby minimize the potential for flange-climb derailments. Lateral load data was collected on the existing fleet and sorted by vehicle series. L/V ratios (single wheel and high and low rail) were calculated for various percentiles using statistical analysis.

Preventive versus Scheduled Maintenance
WMATA employs a time-based preventative maintenance schedule. Vehicles undergo inspections on a daily, monthly, semi-annual and annual basis. Trucks are scheduled to be overhauled at five-year intervals. Since annual mileage accumulated by these vehicles continues to increase, WMATA is developing a mileage-based equivalent to augment the five-year plan.

Still, scheduled maintenance and repairs are only part of the solution. Technology provides a more effective tool to predict failures and plan maintenance. Preventive or proactive condition-based maintenance can help WMATA and other transit systems operate at peak capacity by reducing component failures, minimizing out-of-service time, and reducing stress on the infrastructure. Identifying and correcting vehicle-related problems before they become critical can enhance safety, improve operating efficiency, decrease service disruptions and reduce overall (vehicle and track) maintenance costs.

During the testing and calibration phase, the WRLD successfully detected poorly performing vehicles. Poor performance was always associated with component wear and the need for maintenance. Preventive maintenance allowed vehicles to perform according to their design characteristics.

WRLD data has shown that the frequency with which a vehicle passes a detector, the vehicle's direction of travel and orientation (which end is leading) affect the number of alerts it will generate. Tests showed that vehicles that exhibited somewhat high L/V ratios in one direction "disappeared" for weeks at a time when operated in a different direction or orientation. WRLD data has also shown that abnormal conditions typically do not exist in isolation. For example, the typical bad actor produced high L/V values on the lead wheel of the lead axle. Sometimes, however, a less severe L/V ratio was found with a large negative or a moderately positive L/V on the mate wheel. This usually indicates some form of warp or radial misalignment of the truck.

In any case, wayside health-monitoring systems provide a reliable way to measure vehicle performance and predict maintenance requirements. Access to real-time data allowed engineers at WMATA to assess vehicle dynamic behavior during acceptance testing. Dynamic signatures were characterized. Poorly performing vehicles and potential "troublemakers" were identified. With this, the potential for wheel-climb derailments was minimized, and overall safety was improved. The potential to migrate from corrective to preventive vehicle maintenance was clearly identified.

B. McGuire is Quality Assurance Officer in the Quality Assurance Department of System Safety and Risk Management, Washington Metropolitan Area Transit Authority; R. Sarunac is Lead Mechanical Engineer in the Washington, D.C., office of Booz Allen Hamilton; R. B. Wiley is Principal Investigator at the Transportation Technology Center, Inc.; P. Klauser is a Vehicle Dynamics – Engineering Consultant.

The authors would like to acknowledge the support and assistance of J. Pringle, T. Consavage, D. Ogunrinde, D. H. Smith and D. George of WMATA, and C. Stuart of Booz Allen Hamilton. Special thanks to A. Coe and M. Hiller of WMATA for providing field assistance and close collaboration in writing this article.

References
5000 Series Rapid Transit Car Technical Specification, WMATA, June 1999.

6000 Series Rapid Transit Car Technical Specification, WMATA, July 2002.

AAR, “Rail Car Train/Track Dynamic Testing,” Report No. P-93-109, March 1993.

Klauser, P., “Curving Performance of WMATA Cars,” February 2005.

Sarunac, R., and Klauser, P., “Effect of Secondary Suspension Air Spring Imbalance on Wheel Climb Derailment Potential,” APTA, Pittsburgh, June 2005.

TTCI, “WMATA Wheel-Rail Interface Study,” October 2005.

Zeta-Tech Associates, “Derailment of Transit Vehicles in Special Trackwork,” Final Report, TCRP, July 1996.

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