Interface - The Journal of Wheel/Rail Interaction

WAYSIDE LOAD DETECTION

Using Wayside Load Detectors for Preventive Vehicle Maintenance - Part 1 of 2 (continued)

WMATA's WRLD Project

WMATA, working with a team of engineers from Booz Allen Hamilton, TTCI and the WMATA engineering staff, installed a WRLD at one of its yards to assess vehicle performance and identify poorly performing rail cars. WMATA’s primary objective was to install and modify a WRLD in order to characterize the existing fleet by establishing a database of wheel/rail forces. WMATA also wanted to monitor wheel/rail forces on vehicles that have experienced low-speed flange-climb derailments (and thereby decrease the probability of such incidents), establish a baseline of wheel/rail forces for the newest series rail cars, and compare measured wheel/rail forces with modeling and simulation results. A secondary objective was to pinpoint specific defects based upon vehicle dynamic signatures.

Real-time data collection allowed immediate access to the curving performance of individual rail cars; data was used to assess vehicle dynamic behavior during acceptance testing. Data stored in a database at the WRLD site were accessed via an Internet InteRRIS® link. This data was evaluated for generating performance alarms of poorly performing rail cars — an important project milestone, since gaining maintenance personnel’s confidence in the WRLD’s abilities was one of the major objectives. The system is also used to evaluate specific vehicle types and overall fleet performance.

WMATA's WRLD determines truck performance by measuring lateral loads, vertical loads and angles of attack (along with lateral to vertical (L/V) load ratios, speed, average car weight and total train weight) as vehicles and trains pass the detector. The WRLD is used to identify and schedule preventive maintenance for poorly performing vehicles. In longer term, early detection of potential “troublemakers” could allow WMATA to transition from scheduled to preventive maintenance.

Prior to installing the WRLD, a (VAMPIRE®) simulation was run to predict the angles of attack, lateral and vertical forces, and single wheel L/V ratios that were anticipated at the measurement site. The conditions considered were vertical load, vehicle speed, track roughness, wheel/rail friction, wheel and rail profiles, nominal track gauge, inflated or deflated air springs, air spring pressure imbalance, side bearing coefficient, truck radial misalignment and wheel diameter mismatch. Generally, these factors were considered individually, rather than in combination.

The modeled vehicle was an empty car with a weight of approximately 80,000 pounds. The car length was roughly 75 feet, and the truck center distance was just over 50 feet. The trucks were a two-axle (all powered), two-part frame design with cast side frames and bolster, rubber primary suspension and air spring secondary suspension. The measurement site was a 1,614-foot radius (3.5-degree) curve without superelevation.

Results were based on “nominal case” condition — i.e., empty car weight (AW0), vehicle speed of 15 mph, coefficient of friction (tread and flange) of 0.35, wheel flange angle of 69 degrees, worn rail, standard gauge, perfect track, no air spring imbalance, no wheel mismatch and side bearing coefficient of friction of 0.12. The following parameters were analyzed to determine their impact on performance:

— Vehicle Load. The vehicle load at the current (yard lead) measurement site is unlikely to vary significantly from AW0 (ready-to-run). The effect of greater vehicle load is to increase the axle steering moment. Therefore, a higher vehicle load (AW3 vs. AW0) tends to reduce the single wheel (leading axle, high rail) L/V ratio. This is the result of vehicle interior arrangement (weight imbalance). Because the vehicle speed is above the curve balance speed, the vertical load will shift toward the high rail.

— Vehicle Speed. The vehicle speed for yard track is unlikely to be a completely controllable variable, since the vehicle may pass the measurement site at a range of speeds. For a 1,614-foot radius curve and a speed range of 5 mph to 35 mph, the effect on single wheel (high rail) L/V ratio was found to be insignificant.

— Track Roughness. The impact of track roughness is one of the most influential parameters on vehicle performance. The majority of the simulations that were performed considered a constant radius curve with perfect geometry (i.e., no deviations in curve gauge, crosslevel, alignment or profile from ideal values).

— Wheel to Rail Friction. The wheel/rail friction coefficient is the first critical influence on vehicle curving performance. The simulations involved two friction values: the first for contact between the wheel tread and rail crown, the second for contact between the wheel flange and rail gauge face. Both coefficients were equal with values varying from 0.2 to 0.5. Lubrication reduced the wheel flange coefficient of friction to 0.15; the wheel tread coefficient of friction was either 0.35 or 0.5. Weather conditions and rail contamination are generally outside of operator control; however, wheel or rail lubrication provides a means to provide a controlled friction environment. The angle of attack decreases significantly as wheel/rail friction increases. Also, lubrication tends to increase angle of attack and lateral forces, and reduce axle steering forces. This means that values collected on a rainy day may not be directly comparable to those obtained after an extended period of hot and dry weather.

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