Rolling-Element Fatigue Testing and Data Analysis—A Tutorial

Vlcek, Brian L.; Zaretsky, E. V.

doi:10.1080/10402004.2011.568673

Cited by 25 publications

(16 citation statements)

References 25 publications

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“…However, the life predictions are statistical and only as good as the loading data provided [3]. RCF life is significantly influenced by the material microstructure, which is inherently inhomogeneous, and therefore the RCF lives of a seemingly identical batch of bearings operating under identical load, speed, lubrication, and environmental conditions show a significant degree of scatter [1,5], so infantile failures can and do occur. However, premature failures of train wheel bearings have also been blamed by operators and design authorities on various operational issues including vibration, grease failure, overloading or uneven loading, misalignment, electrical shorts, wheel flats, installation problems and suspension design.…”

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confidence: 98%

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Observing early stage rail axle bearing damage

Symonds

Corni

Wood

et al. 2015

Engineering Failure Analysis

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(Your abstract must use Normal style and must fit in this box. Your abstract should be no longer than 300 words. The box will 'expand' over 2 pages as you add text/diagrams into it.)This work presents initial results from a new approach to condition monitoring of rail axle bearings, in particular some early-stage failures. Background:Premature failure of rail axle bearings causes a significant increase in train operating costs and can impact on train safety. Rail axle bearings have an anticipated service life; however, some bearings do not achieve this. A new approach to degradation diagnostics is now in use on Southeastern / Bombardier trains and provides real-time vibration condition monitoring. Each independent wireless sensor unit bolts to a wheel bearing housing. The units are self-powered by vibration harvesting. This emerging methodology has been made possible by the decreasing power budget of sensor and wireless technologies.

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confidence: 98%

“…Bearing manufacturers provide life predictions; this information gives the operator a statistical indication (L 10 or B 10 ) of when RCF might occur [4][5][6]. The operator then sets a service life (given in miles) and when a bearing has reached it, it must be replaced.…”

mentioning

confidence: 99%

Observing early stage rail axle bearing damage

Symonds

Corni

Wood

et al. 2015

Engineering Failure Analysis

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“…Where < 1, the factor a 3 in Eq. [8] can vary from 0.2 to 0.5 (Zaretsky (22)). If the effect of boundary lubrication had not been considered by the actuator manufacturer, the bearing lives summarized in Table 2 would be as much as 80% less than those shown.…”

Section: Rolling-element Bearing Life Analysismentioning

confidence: 99%

Space Shuttle Rudder/Speed Brake Actuator—A Case Study. Probabilistic Fatigue Life and Reliability Analysis

Oswald

Savage

Zaretsky

2014

Tribology Transactions

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The U.S. Space Shuttle fleet was originally intended to have a life of 100 flights for each vehicle, lasting over a 10-year period, with minimal scheduled maintenance or inspection. The first space shuttle flight was that of the Space Shuttle Columbia (OV-102), launched April 12, 1981. The disaster that destroyed Columbia occurred on its 28th flight, February 1, 2003, nearly 22 years after its first launch. In order to minimize risk of losing another Space Shuttle, a probabilistic life and reliability analysis was conducted for the Space Shuttle rudder/speed brake actuators to determine the number of flights the actuators could sustain. A life and reliability assessment of the actuator gears was performed in two stages: a contact stress fatigue model and a gear tooth bending fatigue model. For the contact stress analysis, the Lundberg-Palmgren bearing life theory was expanded to include gear-surface pitting for the actuator as a system. The mission spectrum of the Space Shuttle rudder/speed brake actuator was combined into equivalent effective hinge moment loads including an actuator input preload for the contact stress fatigue and tooth bending fatigue models. Gear system reliabilities are reported for both models and their combination. Reliability of the actuator bearings was analyzed separately, based on data provided by the actuator manufacturer. As a result of the analysis, the reliability of one half of a single actuator was calculated to be 98.6% for 12 flights. Accordingly, each actuator was subsequently limited to 12 flights before removal from service in the Space Shuttle.

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“…Therefore due to existing conflict and insufficient information to determine life factor iso a for each reported data set, modified LP Eq. [5] is used for analysis in this work.…”

Section: Load Life Equationmentioning

confidence: 99%

“…One of the reasons for this under prediction is that reliability, material and lubrication conditions of the bearings were not considered in the original LP model. To account ACCEPTED MANUSCRIPT ACCEPTED MANUSCRIPT 6 for these operating conditions, Zaretsky (4) modified original LP equation with three life factors 1 a , 2 a and 3 a as: 1 2 3 ae ö = ç ÷ è ø p s e C L a a a F [5] It was observed that these life adjustment factors are independent of load life exponent 'p', except for the case when inner ring raceways experience tensile hoop stresses due to interference fits (Vlcek and Zaretsky (5) where, ISO a is integrated life adjustment factor which is dependent on four interdependent factors: lubrication, contamination, load and the fatigue stress limit of the bearing material.…”

Section: Load Life Equationmentioning

confidence: 99%

Reevaluation of Rolling Element Bearing Load-Life Equation Based on Fatigue Endurance Data

Londhe

Arakere

Haftka

2015

Tribology Transactions

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The load life exponents used in the modified life rating equation for rolling element bearings were determined by statistical analysis of the experimental data generated in 1940s, following Lundberg and Palmgren's seminal work. Based on fracture mechanics arguments, the fatigue life is known to be inversely proportional to the square root of the size of the non-metallic inclusions. However, modern high performance VIMVAR bearing steels are clean and non-metallic inclusions are no longer the weak link. Fatigue life predictions ( 10 L life) for modern bearings using the modified load life relations greatly under-predicts observed life. Hence there is a need to update parameters of these equations using more recent life data. Based on the endurance data reported in Harris and McCool (1), validation analysis of modified life rating equation was performed to reevaluate the values of load life exponent for both ball and cylindrical roller bearings. The results from this study indicate that the load life exponent for ball 1 Corresponding Bearing 10 L life calculated using the corrected load-life exponents values show better agreement with observed life. Details of the sampling technique used for reducing epistemic uncertainty in experimental data and the process of statistical reevaluation using Bayesian updating are discussed in detail. Accuracy of reevaluation results are presented using logarithmic plots of the ratio of predicted to actual fatigue lives for all the data samples.

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Rolling-Element Fatigue Testing and Data Analysis—A Tutorial

Cited by 25 publications

References 25 publications

Observing early stage rail axle bearing damage

Observing early stage rail axle bearing damage

Space Shuttle Rudder/Speed Brake Actuator—A Case Study. Probabilistic Fatigue Life and Reliability Analysis

Reevaluation of Rolling Element Bearing Load-Life Equation Based on Fatigue Endurance Data

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