Development of Prognostic Techniques for Surface Defect Growth in Railroad Bearing Rolling Elements

Prevention of bearing failures which may lead to catastrophic derailment is a major safety concern for the railroad industry. Advances in bearing condition monitoring hold the promise of early detection of bearing defects, which will improve system reliability by permitting early replacement of failing components. However, to minimize disruption to operations while providing the maximum level of accident prevention that early detection affords, it will be necessary to understand the defect growth process and try to quantify the growth speed to permit economical, non-disruptive replacement of failing components rather than relying on immediate removal upon detection. The study presented here investigates the correlation between the rate of surface defect (i.e. spall) growth per mile of full-load operation and the size of the defects. The data used for this study was acquired from defective bearings that were run under various load and speed conditions utilizing specialized railroad bearing dynamic test rigs operated by the University Transportation Center for Railway Safety (UTCRS) at the University of Texas Rio Grande Valley (UTRGV). Periodic removal and disassembly of the railroad bearings was carried out for inspection and defect size measurement and documentation. Castings were made of spalls using low-melting, zero shrinkage Bismuth-based alloys so that a permanent record of the full spall geometry could be retained. Spalls were measured using optical techniques coupled with digital image analysis and also with a manual coordinate measuring instrument with the resulting field of points manipulated in MatLab™ and Solidworks™. The spall growth rate in area per mile of full-load operation was determined and, when plotted versus spall area, clear trends emerge. Initial spall size is randomly distributed as it depends on originating defect depth, size, and location on the rolling raceway. The growth of surface spalls is characterized by two growth regimes with an initial slower growth rate which then accelerates when spalls reach a critical size. Scatter is significant but upper and lower bounds for spall growth rates are proposed and the critical dimension for transition to rapid spall growth is estimated. The main result of this study is a preliminary model for spall growth which can be coupled to bearing condition monitoring tools to permit economical scheduling of bearing replacement after the initial detection of spalls

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

Prognostics Models for Railroad Tapered Roller Bearings with Spall Defects on Inner or Outer Rings

Rolling contact fatigue (RCF) is one of the major causes of failure in railroad bearings used in freight service. Subsurface inclusions resulting from impurities in the steel used to fabricate the bearings initiate subsurface fatigue cracks, which propagate upwards and cause spalling of the rolling surfaces. These spalls start small and propagate as continued operation induces additional crack formation and spalling. Studies have shown that the bearing temperature is not a good indicator of spall initiation. In many instances, the temperature of the bearing increases markedly only when the spall has spread across major portions of the raceway. In contrast, vibration signatures can be used to accurately detect spall initiation within a bearing and can track spall deterioration. No monitoring technique can indicate the growth rate of a spall or determine residual useful life. Hence, the main objective of this study is to develop reliable prognostic models for spall growth within railroad bearings that are based on actual service life testing rather than theoretical simulations. The data used to devise the models presented here were acquired from laboratory and field testing that started in 2010. Growth models are provided for spalls initiating on the bearing inner (cone) and outer (cup) rings. Coupling these prognostic models with a previously developed vibration-based bearing condition monitoring algorithm will provide the rail industry with an efficient tool that can be used to plan proactive maintenance schedules that will mitigate unnecessary and costly train stoppages and delays and will prevent catastrophic derailments

Development of Prognostics Techniques for Surface Defect Growth in Railroad Bearing Rolling Elements

One of the major causes of failure in railroad bearings used in freight service is rolling contact fatigue (RCF). RCF is due to subsurface inclusions which are a result from impurities in the steel that is used to fabricate the bearings. Once the bearings initiate subsurface fatigue cracks, they will then propagate upward and initiate spalling of the rolling surfaces. These spalls will begin small and continuously propagate with operation as this induces additional crack forming and spalling. Studies have indicated that bearing temperature is not a good indicator of spall initiation. In many cases, the temperature of the bearing increases markedly once the spall has propagated across major portions of the raceway. However, vibration signatures can be used to detect spall initiation and can track spall deterioration. No monitoring system technique can indicate the growth rate of a spall nor can it determine the bearing residual useful life. Therefore, the principle objective of this study is to develop reliable prognostic models for spall growth within railroad bearings that are based on actual service life testing rather than theoretical simulations. The data used to develop the models presented in this study have been acquired from laboratory and field testing that initiated in 2010. The growth models in this study are for spalls that initiated on the bearing inner (cone) and outer (cup) rings. Coupling these prognostic models with a vibration-based bearing condition-monitoring algorithm previously developed, will provide the rail industry with an efficient tool that can be used to propose proactive maintenance schedules that will reduce unnecessary and costly train stoppages and delays and will prevent catastrophic derailments

Calculation and finite element analysis of the temperature field for high-speed rail bearing based on vibrational characteristics

The complicated temperature environment of the high-speed rail bearing will generate the thermal stress and thermal deformation, which will change the vibrational characteristics of the bearing. If the vibration is serious, it will result in bearing failure and destructive accidents. Thus, the steady temperature field and the relationship between temperature field and the critical speed of the bearing were researched based on the vibrational characteristics in the paper. According to the specific work conditions and structure characteristics of the double row tapered roller bearing assembly, the heat transfer model of high-speed rail bearing was developed. The heat source and the external heat dissipation of the bearing were calculated, the reasonable boundary conditions of lubrication were set, and then the finite element model was established in ANSYS. According to four different distribution methods of heat source, the temperature field of the inner ring, outer ring and rollers were simulated and analyzed. Comparing the four different results, a reasonable distribution method of the heat source was put forward. Finally the effects of steady temperature field on critical speed of high-speed rail bearing were discussed. The simulation results showed that the bearing temperature distribution was basically consistent with the actual working conditions. The steady temperature field has stronger effect on vibration mode of low-order critical speed then high-order critical speed of bearing. The results of this study provide a basis of vibration characteristics for the use and optimal design of high-speed rail bearing

The Effect of Heat Generation in the Railroad Bearing Thermoplastic Elastomer Suspension Element on the Thermal Behavior of Railroad Bearing Assembly

Understanding the internal heat generation of the railroad bearing elastomer suspension element during operation is essential to predict its dynamic response and structural integrity, as well as to predict the thermal behavior of the complete railroad bearing assembly including the bearing adapter. The latter is essential for sensor selection and placement within the adapter (e.g., typical temperature sensors have operating ranges of up to 125°C or 257°F). The internal heat generation is a function of the loss modulus, strain, and frequency. Based on experimental studies, estimations of internally generated heat within the thermoplastic elastomer pad were obtained. The calculations show that the pad internal heat generation is impacted by temperature and frequency. However, during service operation, exposure of the suspension pad to loading frequencies above 10 Hz is less likely to occur. Therefore, internal heat generation values that have a significant impact on the suspension pad steady-state temperature are less likely to be reached. An experimentally validated finite element thermal model that can be used to obtain temperature distribution maps of complete bearing assemblies in service operation conditions is presented. This thesis summarizes the work done to investigate the effect of the internal heat generation in the thermoplastic elastomer suspension element on the thermal behavior of the railroad bearing assembly

Empirical Model of Bearing Temperature Saturation at Asahan II Hydro-Turbine-Generator

Bearing temperature saturation is a common phenomenon observed during no-load run and full-load tests of Asahan II hydro-turbine-generators. Despite complex heat transfer mechanism involved behind it, simple model can be constructed to predict bearing temperature change with time. Confidence on the general form of such model is rather high because it is validated using abundant data collected during the past 35 years. Further investigations are also made to compare temperature saturations at different load, rotational speed, and performance of cooling coil

An Experimentally Validated Finite Element Model of Thermal Transient Response of a Railroad Bearing Adapter

Wayside hot box detectors (HBDs) are devices used to determine the health of railcar components such as bearings, axles, and brakes by monitoring the radiated temperature form these components. HBDs have been instrumental in reducing rail derailments in the decade, but the number of non-verified bearing removals has increased significantly. To combat these limitations, researchers have opted to use wireless onboard sensor devices directly mounted on the bearing adapter. The wireless onboard health monitoring system developed by the University Transportation Center for Railway Safety (UTCRS) utilizes temperature and vibration sensors to detect the condition of rolling stock. However, because the sensor is affixed to the bearing adapter, a transient thermal analysis was performed to determine the lumped capacitance behavior and the corresponding thermal lag of a railroad bearing adapter. To fully understand the heat transfer distribution, a finite element model (FEM) was developed to observe the thermal dissipation among the components. To validate the results, experimental data and the finite element simulation were compared against each other. These results can be used to identify the optimal anchor points for the temperature sensors on the bearing adapter and increase the proficiency of wireless onboard sensor devices in detecting defective components

The Role of Thermally-Induced Geometrical Changes in Temperature Trending of Railroad Tapered Roller Bearings

The understanding of the phenomenon of temperature trending of railroad tapered roller bearings is of paramount importance to the railroad industry. The problem that this poses to the industry is that it leads to false alarms triggered by wayside detectors, which forces the premature removal of defect-free bearings. This thesis provides more insight into this phenomenon and answers questions regarding the importance of key tapered roller bearing components geometry and geometrical changes during temperature trending events. In this study, dynamic experiments conducted in the laboratory have represented the primary method of testing bearing temperature trending. The experimental results are brought together with theoretical calculations of rates of heat generation and finite element investigations in an attempt to map out the temperature and geometrical changes that occur within bearing components during a temperature trending event

Estimating the Outer Ring Defect Size and Remaining Service Life of Freight Railcar Bearings Using Vibration Signatures

The railroad industry currently utilizes two wayside detection systems to monitor the health of freight railcar bearings in service: The Trackside Acoustic Detection System (TADS™) and the wayside Hot-Box Detector (HBD). TADS™ uses wayside microphones to detect and alert the conductor of high-risk defects. Many defective bearings may never be detected by TADS™ since a high-risk defect is a spall which spans more than 90% of a bearing’s raceway, and there are less than 20 systems in operation throughout the United States and Canada. Much like the TADS™, the HBD is a device that sits on the side of the rail-tracks and uses a non-contact infrared sensor to determine the temperature of the train bearings as they roll over the detector. These wayside detectors are reactive in the detection of a defective bearing and require emergency stops in order to replace the wheelset containing the defective bearing. These costly and inefficient train stoppages can be prevented if a proper maintenance schedule can be developed at the onset of a defect initiating within the bearing. This proactive approach would allow for railcars with defective bearings to remain in service operation safely until reaching scheduled maintenance. Driven by the need for a proactive bearing condition monitoring system in the rail industry, the University Transportation Center for Railway Safety (UTCRS) research group at the University of Texas Rio Grande Valley (UTRGV) has been developing an advanced onboard condition monitoring system that can accurately and reliably detect the onset of bearing failure using temperature and vibration signatures of a bearing. This system has been validated through rigorous laboratory testing at UTRGV and field testing at the Transportation Technology Center, Inc. (TTCI) in Pueblo, CO. The work presented here builds on previously published work that demonstrates the use of the advanced onboard condition monitoring system to identify defective bearings as well as the correlations developed for spall growth rates of defective bearing outer rings (cups). Hence, the system uses the root-mean-square (RMS) value of the bearing’s acceleration to assess its health. Once the bearing is determined to have a defective outer ring, the RMS value is then used to estimate the defect size. This estimated size is then used to predict the remaining service life of the bearing. The methodology proposed in this paper can prove to be a useful tool in the development of a proactive and cost-efficient maintenance cycle for railcar owners