Optimizing Power Consumption of Freight Railroad Bearings Using Laboratory Experimental Data

Based on projected freight truck fuel efficiency, freight railroad and equipment suppliers need to identify, evaluate and implement technologies and/or operating practices to maintain traditional railroad economic competitiveness. The railway industry uses systems that record the total energy efficiency of a train but not energy efficiency or consumption by components. Lowering the energy consumption of certain train components will result in an increase in its overall energy efficiency, which will yield cost benefits for all the stakeholders. One component of interest is the railroad bearing whose power consumption varies depending on several factors that include railcar load, train speed, condition of bearing whether it is healthy or defective, and type of defect. Being able to quantify the bearing power consumption, as a function of the variables mentioned earlier, would make it possible to obtain optimal operating condition ranges that minimize energy consumption and maximize train energy efficiency. Several theoretical studies were performed to estimate the power consumption within railroad bearings, but those studies lacked experimental validation. For almost a decade now, the University Transportation Center for Railway Safety (UTCRS) at the University of Texas Rio Grande Valley (UTRGV) has been collecting power consumption data for railroad bearings under various loads, speeds, ambient temperatures, and bearing condition. The objective of this ongoing study is to use the experimentally acquired power consumption to come up with a correlation that can be used to quantify the bearing power consumption as a function of load, speed, ambient temperature, and bearing condition. Once obtained, the model can then be used to determine optimal operating practices that maximize the railroad bearing energy efficiency. In addition, the developed model will provide insight into possible areas of improvement for the next generation of energy efficient railroad bearings. This paper will discuss ongoing work including experimental setup and findings of energy consumption of bearings as function of railcar load, train speed, condition of bearing whether it is healthy or defective, and type of defect. Findings of energy consumption are converted into approximations of diesel gallons to quantify the effect of nominal energy consumption of the bearings and show economic value and environmental impact.

Defect Prognostics Models for Spall Growth in Railroad Bearing Rolling Elements

Prevention of railroad bearing failures, which may lead to catastrophic derailments, is a central safety concern. Early detection of railway component defects, specifically bearing spalls, will improve overall system reliability by allowing proactive maintenance cycles rather than costly reactive replacement of failing components. A bearing health monitoring system will provide timely detection of flaws. However, absent a well verified model for defect propagation, detection can only be used to trigger an immediate component replacement. The development of such a model requires that the spall growth process be mapped out by accumulating associated signals generated by various size spalls. The addition of this information to an integrated health monitoring system will minimize operation disruption and maintain maximum accident prevention standards enabling timely and economical replacements of failing components. An earlier study done by the authors focused on bearing outer ring (cup) raceway defects. The developed model predicts that any cup raceway surface defect (i.e. spall) once reaching a critical size (spall area) will grow according to a linear correlation with mileage. The work presented here investigates spall growth within the inner rings (cones) of railroad bearings as a function of mileage. The data for this study were acquired from defective bearings that were run under various load and speed conditions utilizing specialized railroad bearing dynamic test rigs owned by the University Transportation Center for Railway Safety (UTCRS) at the University of Texas Rio Grande Valley (UTRGV). The experimental process is based on a testing cycle that allows continuous growth of railroad bearing defects until one of two conditions are met; either the defect is allowed to grow to a size that does not jeopardize the safe operation of the test rig, or the change in area of the spall is less than 10% of its previous size prior to the start of testing. The initial spall size is randomly distributed as it depends on the originating defect depth, size, and location on the rolling raceway. Periodic removal and disassembly of the railroad bearings was carried out for inspection and defect size measurement along with detailed documentation. Spalls were measured using optical techniques coupled with digital image analysis, as well as, with a manual coordinate measuring instrument with the resulting field of points manipulated in MatLab™. Castings were made of spalls using low-melting, zero-shrinkage bismuth-based alloys, so that a permanent record of the spall geometry and its growth history can be retained. The main result of this study is a preliminary model for spall growth, which can be coupled with bearing condition monitoring tools that will allow economical and effective scheduling of proactive maintenance cycles that aim to mitigate derailments, and reduce unnecessary train stoppages and associated costly delays on busy railways.

Radiative Heat Transfer Analysis of Railroad Bearings for Wayside Hot-Box Detector Optimization

The railroad industry utilizes wayside detection systems to monitor the temperature of freight railcar bearings in service. The wayside hot-box detector (HBD) is a device that sits on the side of the tracks and uses a non-contact infrared sensor to determine the temperature of the train bearings as they roll over the detector. Various factors can affect the temperature measurements of these wayside detection systems. The class of the railroad bearing and its position on the axle relative to the position of the wayside detector can affect the temperature measurement. That is, the location on the bearing cup where the wayside infrared sensor reads the temperature varies depending on the bearing class (e.g., class K, F, G, E). Furthermore, environmental factors can also affect these temperature readings. The abovementioned factors can lead to measured temperatures that are significantly different than the actual operating temperatures of the bearings. In some cases, temperature readings collected by wayside detection systems did not indicate potential problems with some bearings, which led to costly derailments. Attempts by certain railroads to optimize the use of the temperature data acquired by these wayside detection systems has led to removal of bearings that were not problematic (about 40% of bearings removed were non-verified), resulting in costly delays and inefficiencies. To this end, the study presented here aims to investigate the efficacy of the wayside detection systems in measuring the railroad bearing operating temperature in order to optimize the use of these detection systems. A specialized single bearing dynamic test rig with a configuration that closely simulates the operating conditions of railroad bearings in service was designed and built by the University Transportation Center for Railway Safety (UTCRS) research team at the University of Texas Rio Grande Valley (UTRGV) for the purpose of this study. The test rig is equipped with a system that closely mimics the wayside detection system functionality and compares the infrared sensor temperature reading to contact thermocouple and bayonet temperature sensors fixed to the outside surface of the bearing cup. This direct comparison of the temperature data will provide a better understanding of the correlation between these temperatures under various loading levels, operating speeds, and bearing conditions (i.e. healthy versus defective), which will allow for an optimization of the wayside detectors. The impact on railway safety will be realized through optimized usage of current wayside detection systems and fewer nonverified bearings removed from service, which translates into fewer costly train stoppages and delays.

Developing Empirical Models of Railroad Bearing Grease

The degradation of the grease used to lubricate railroad bearings is believed to be caused by two processes: the mechanical processes occurring within the bearing and a diffusion process. Appropriate lubrication of the bearings is critical during railroad service operation. The study presented here will focus on the development of empirical models that can accurately predict the residual useful life of railroad bearing grease. Modeling techniques to be employed include regression, regression trees and split plots. The data set used in the development of the model consists of more than 100 samples of grease that were taken from railroad bearings. The bearings have been subjected to experimental variables such as load conditions, rotational speed, temperature, and mileage all of which have been observed in a laboratory setting. The mileage parameter is consistent with the total miles that were run using the grease from which the sample has been taken. Load, speed, and temperature values fluctuate within the total service operation of the bearing; therefore, a high value, a low value, and a weighted average are taken for the aforementioned parameters. The grease samples are taken from critical locations of the bearing, the inboard raceway, the outboard raceway and the spacer ring area, meaning that there are three samples collected from each railroad bearing, each having their own set of corresponding parameters. The oxidation induction time (OIT) of the grease is an indicator of the residual life of the grease; therefore, the OIT for each sample had been acquired using a differential scanning calorimeter (DSC). OIT is dependent upon mileage, load, speed, and temperature. This study was successful in developing an empirical model which can be utilized to predict the residual life for given operational characteristics.

Energy Harvesting Potential of Terfenol-D for On-Board Bearing Health Monitoring Applications

One of the limiting factors in on-board bearing health monitoring systems is the life of the batteries used to power the system. Thus, any device that can extend the life of the battery, or entirely replace it, is a notable improvement on any currently available systems. Existing on-board monitoring systems, not optimized for low power, are designed to run on approximately 300 mW of power. Current bearing health monitoring systems have proven effective with as few as one reading every four minutes. The environment under which railroad bearings operate is a harsh one, making most forms of energy harvesting very hard to implement. Terfenol-D is a novel and sustainable solution for this problem due to its durable characteristics and strong magnetostriction. A fixture is designed using multiple magnets of ranging magnetization to properly characterize energy harvesting using Terfenol-D. The maximum available power observed during these experiments is about 77 mW under ideal conditions. The generated power is sufficient to run low-power bearing health monitoring systems.

Implementation of Wireless Temperature Sensors for Continuous Condition Monitoring of Railroad Bearings

At present there are no existing bearing health monitoring systems capable of continuous monitoring and tracking of railroad bearings on freight cars. Current wayside equipment is used to garner intermittent bearing cup temperatures, which at times could be every 65 km (∼40 mi) or more. Such devices are not designed to provide continuous condition monitoring which would enable users to assess the rate of bearing health degradation and predict when a bearing will require service. To this end, IONX, LLC, a subsidiary of Amsted Rail, Inc., has developed low power Wireless Sensor Nodes (WSNs) which can be retrofitted to existing bearing adapters. The WSNs provide continuous monitoring of bearing temperatures as well as the current ambient temperature. Since the nodes are affixed to the bearing adapter surface, a correlation is necessary to estimate the bearing cup temperature using the measured adapter surface temperature. This paper describes research conducted at The University of Texas-Pan American (UTPA) to devise a reliable mathematical model to correlate both temperatures. Additionally, these wireless nodes are currently in use on ten railroad cars that are part of an Australian fleet. The nodes have been collecting data since March 2010. The acquired data was used to devise and test a series of metrics that can automatically detect distressed bearings and predict time to maintenance. The development of bearing health monitoring metrics and their use to assess bearings in the Australian fleet is also discussed in this paper.

Non-Contacting Seal for Rail Freight Applications

Due to increasing energy costs and emissions restrictions, many industries are paying closer attention to the energy required to keep their equipment operating. Parasitic losses in power such as those due to the drag produced by contacting lip seals that are found in a variety of rotating equipment can significantly add to the total operating costs of that equipment. In mobile industries (railroad, heavy truck, and automotive), these losses can significantly affect the amount of fuel consumed and emissions produced. Power losses due to seal drag are also accompanied with frictional heat and wear which can degrade components and lead to maintenance costs to service or replace these components. To address these issues for the railroad industry, Timken has developed a non-contacting seal for use in railroad bearings. A review is given of the design and development of a non-contacting labyrinth seal for railroad bearing applications. The seal has been qualified by the Association of American Railroads (AAR) for use in North America freight car service and is currently the only non-contacting seal in operation for this market. The unique design of the labyrinth pathway allows for zero seal drag with exceptional grease retention and contaminant exclusion capabilities as compared to contacting elastomer lip seals that are typical for this industry. Experimental test performance of this seal will be compared to other seals that are currently used in this industry. Operating torque reductions of 10–30 in-lb per seal achieved through this technology can lead to fuel savings on the order of hundreds of thousands of gallons per year corresponding to the elimination of thousands of tons of emissions due to the reduced fuel usage in the U.S. alone. These savings can be passed directly to railroads and freight car owners as well as the general population with lower operating costs, increased reliability, longer service life, and reduced emissions.

Thermal Analysis of Railroad Bearings: Effect of Wheel Heating

Catastrophic bearing failure is a major concern for the railroad industry because it can lead to costly train stoppages and even derailments. Excessive heat buildup within the bearing is one of the main factors that can warn of impending failure. A question is often raised regarding the transfer of heat from a wheel during braking and whether this can lead to false setouts. Therefore, this work was motivated by the need to understand and quantify the heat transfer paths to the tapered roller bearing within the railroad wheel assembly when wheel heating occurs. A series of experiments and finite element (FE) analyses were conducted in order to identify the different heat transfer mechanisms, with emphasis on radiation. The experimental setup consisted of a train axle with two wheels and bearings pressed onto their respective journals. One of the wheels was heated using an electric tape placed around the outside of the rim. A total of 32 thermocouples scattered throughout the heated wheel, the axle, and the bearing circumference measured the temperature distribution within the assembly. In order to quantify the heat radiated to the bearing, a second set of experiments was developed; these included, in addition to the axle and the wheel pair, a parabolic reflector that blocked body-to-body radiation to the bearing. The appropriate boundary conditions including ambient temperature, emissivity, and convection coefficient estimates were measured or calculated from the aforementioned experiments. The FE thermal analysis of the wheel assembly was performed using the ALGOR™ software. Experimental temperature data along the radius of the heated wheel, the bearing circumference, and at selected locations on the axle were compared to the results of the FE model to verify its accuracy. The results indicate that the effect of thermal radiation from a hot wheel on the cup temperature of the adjacent bearing is minimal when the wheel tread temperature is at 135°C (275°F), and does not exceed 17°C (31°F) when the wheel tread is at 315°C (600°F).

Revenue Service Demonstration of On-Board Condition Monitoring System

The Office of Research and Development of the Federal Railroad Administration (FRA) is sponsoring a project to develop and demonstrate an on-board condition monitoring system for freight trains. The objective of the system is to improve railroad safety and efficiency through continuous monitoring of mechanical components in order to detect defects before they cause breakdowns and accidents. The project, which commenced in June 1999, is part of the Rolling Stock Program Element in FRA’s Five-Year Strategic Plan for Railroad Research, Development and Demonstrations [1]. Science Applications International Corporation (SAIC) and Wilcoxon Research (WR) designed and developed a prototype system in 2000. The prototype system was tested during the period Nov. 2000–Nov. 2001 on a vehicle provided by the Research and Tests Department at Norfolk Southern Corporation. A Revenue Service Demonstration is scheduled to commence in October 2003. The monitoring system will be installed on five coal hopper cars and tested in revenue service. Southern Company Service is providing the test cars. The train will operate on a Norfolk Southern line between a coalmine near Berry, AL and an electric power plant, located 35 miles southeast of Birmingham. The demonstration is scheduled to run for six months. The demonstration will showcase some of the latest technologies in wireless communications and railroad bearings. A tri-mode cell telephone will be used for data telemetry between the on-board monitoring system and a web-accessible database. The Timken Company has developed two innovative systems that will be deployed in the demonstration — a permanent magnet generator mounted inside a Class F railroad bearing and bearing health monitoring system featuring temperature and vibration sensors, a tachometer, a micro-controller and an RF transmitter mounted inside a Class F bearing.