Dynamic Capacity of Oscillating Rolling Element Bearings

1968 ◽  
Vol 90 (1) ◽  
pp. 130-138 ◽  
Author(s):  
J. H. Rumbarger ◽  
A. B. Jones
Keyword(s):  
Rolling Bearing ◽  
Rolling Element Bearings ◽  
Critical Amplitude ◽  
Weibull Statistics ◽  
Dynamic Capacity ◽  
Roller Bearings ◽  
Rolling Element ◽  
Life Tests

The results of life tests of 388 caged, needle-roller bearings under combinations of load, speed, and amplitude of oscillation are analyzed with Weibull statistics. The rolling bearing theory of Lundberg and Palmgren is extended to cover oscillating roller bearings and is favorably compared with the life tests. A formula for basic dynamic capacity in oscillation is developed for amplitudes of oscillation which are less than the critical amplitude. Capacity formulas are also presented for both ball and roller bearings for any amplitude of oscillation.

The Effect of Wear Evolution on Vibration-based Fault Detection in Tapered Roller Bearings

2019 ◽  
Vol 9 (1) ◽  
pp. 18-23
Author(s):  
K Rabeyee ◽  
X Tang ◽  
F Gu ◽  
A D Ball
Keyword(s):  
Condition Monitoring ◽  
Rolling Element Bearings ◽  
Rolling Bearings ◽  
Roller Bearings ◽  
Fault Type ◽  
Rolling Element ◽  
Tapered Roller ◽  
Magnitude Variation ◽  
Tapered Roller Bearings ◽  
The Impact

Rolling element bearings (REBs) are typical tribological components used widely in rotating machines. Their failure could cause catastrophic damage. Therefore, condition monitoring of bearings has always had great appeal for researchers. Usually, the detection and diagnostics of incipient bearing faults are achieved by characterising the weak periodic impacts induced by the collision of defective bearing components. However, race wear evolution, which is inevitable in bearing applications, can affect the contact between bearing elements and races, thereby decreasing the impact magnitudes and impeding detection performance. In this paper, the effect of wear evolution on the condition monitoring of rolling bearings is firstly analysed based on internal clearance changes resulting from the wear effect. Then, an experimental study is ingeniously designed to simulate wear evolution and evaluate its influence on wellknown envelope signatures according to measured vibrations from widely used tapered roller bearings. The fault type is diagnosed in terms of two indices: the magnitude variation of characteristic frequencies and the deviation of such frequencies. The experimental results indicate a signature decrease with regard to wear evolution, suggesting that accurate severity diagnosis needs to take into account both the wear conditions of the bearing and the signature magnitudes.

scholarly journals Experimental Assessment of Influence of the Ball Bearing Raceway Curvature Ratio on the Level of Vibration

2020 ◽  
Vol 22 (4) ◽  
pp. 103-111 ◽  
Author(s):  
Pawel Zmarzly
Keyword(s):  
Experimental Studies ◽  
Rolling Bearing ◽  
Rolling Element Bearings ◽  
Test Results ◽  
Curvature Ratio ◽  
Rolling Element ◽  
Innovative System ◽  
Bearing Raceway ◽  
Bearing Rings ◽  
Car Transportation

Raceway curvature ratio is a very important parameter, because its values influence the performance characteristics of rolling-element bearings, their durability and the level of generated vibrations. However, the level of generated vibrations is one of the most important operating parameters of the rolling-element bearings. Excessive vibrations generated by rolling-element bearings affect the operation of the whole mechanism. The article presents experimental studies aimed at evaluation of influence of the inner and outer raceway curvature ratios of 6304-type rolling-element bearings on generated vibrations values. The raceway curvature ratio was determined based on results of metrological measurements. For this purpose, the radii of the inner and outer raceways as well as the diameters of the balls were measured. Design and principle of operation of an innovative system for analysis of the raceway geometry of the rolling bearing rings was presented. The vibration analysis was carried out in three frequency ranges, i.e. low (50-300 Hz), medium (300-1,800 Hz) and high (1,800-10,000 Hz). Values of measured vibrations were expressed in Anderon units. The test results showed that increase in the raceway curvature ratio causes a moderate decrease in the value of the generated vibrations. The research results presented in this article will serve as a guidance to designers and manufacturers of the rolling-element bearings on how to modify the geometry of raceways and balls to obtain bearings that generate low vibration values. That is very important in car transportation.

Multi-Objective Robust Optimization of Deep Groove Ball Bearings Considering Manufacturing Tolerances Based on Fatigue and Wear Considerations

2021 ◽  
pp. 1-43
Author(s):  
Md Saif Ahmad ◽  
Rajiv Tiwari ◽  
Twinkle Mandawat
Keyword(s):  
Objective Function ◽  
Ball Bearings ◽  
Rolling Element Bearings ◽  
Objective Functions ◽  
Dynamic Capacity ◽  
Multi Objective ◽  
Design Variables ◽  
Deep Groove ◽  
Rolling Element ◽  
Manufacturing Tolerances

Abstract In designing any machine element, we need to optimize the design to attain its maximum utilization. Herein deep groove ball bearings has been chosen for optimization. Optimization has been done in such a way that the design is robust so that manufacturing tolerances can be considered in the design. Robust design ensures that changes in design variables due to manufacturing tolerances have minimum effect on the objective function, i.e. its performance. Robustness is achieved by maximizing the mean value of the objective function and minimizing its deviation. For rolling element bearings, its life is one of the most crucial considerations. The rolling bearing rating life depends on dynamic capacity, lubrication conditions, contamination, mounting, lubrication, manufacturing accuracy, material quality, etc. and thus the dynamic capacity and elasto-hydrodynamic minimum film thickness has been taken as objective functions for the current problem. Rolling element bearings have standard boundary dimensions, which include the outer diameter, inner diameter and bearing width for the case of deep groove ball bearings. So the performance can be improved by changing internal dimensions, which are the bearing pitch diameter, ball diameter, the inner and outer raceway groove curvature coefficients and, the number of rolling elements. These five internal geometrical parameters are taken as design variables, moreover five design constraint factors are also included. Thirty-six constraint equations are considered, which are mainly based on geometrical and strength considerations. In the present work, the objective functions are optimized individually (i.e., the single-objective optimization) and then simultaneously (i.e., the multi-objective optimization). NSGA-II (non-dominated sorting genetic algorithm) has been used as the optimization tool. Pareto optimal fronts are obtained for one of the bearings. Out of many points on the Pareto-front, only the knee solutions have been presented in the tables. This work shows that geometrically feasible bearings can be designed by optimizing multiple objective functions simultaneously and also incorporating the variations in dimensions, which occur due to manufacturing tolerance.

scholarly journals Multifault Diagnosis for Rolling Element Bearings Based on Intrinsic Mode Permutation Entropy and Ensemble Optimal Extreme Learning Machine

2014 ◽  
Vol 6 ◽  
pp. 803919 ◽  
Author(s):  
Jianzhong Zhou ◽  
Jian Xiao ◽  
Han Xiao ◽  
Weibo Zhang ◽  
Wenlong Zhu ◽  
...  
Keyword(s):  
Extreme Learning Machine ◽  
Rolling Bearing ◽  
Ensemble Empirical Mode Decomposition ◽  
Permutation Entropy ◽  
Rolling Element Bearings ◽  
Bearing Fault Diagnosis ◽  
Bee Colony ◽  
Mode Decomposition ◽  
Rolling Element ◽  
Learning Machine

This paper presented a novel procedure based on the ensemble empirical mode decomposition and extreme learning machine. Firstly, EEMD was utilized to decompose the vibration signals into a number of IMFs adaptively and the permutation entropy of each IMF was calculated to generate the fault feature matrix. Secondly, a new extreme learning machine was proposed by combining ensemble extreme learning machine and the evolutionary extreme learning machine which used an artificial bee colony algorithm to optimize the input weights and hidden bias. The proposed diagnosis algorithm was applied on the three rolling bearing fault diagnosis experiments. The numerical experimental results demonstrated that the proposed method had an improved generalization performance than traditional extreme and other variants.

scholarly journals The Hybrid KICA-GDA-LSSVM Method Research on Rolling Bearing Fault Feature Extraction and Classification

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jiyong Li ◽  
Shunming Li ◽  
Xiaohong Chen ◽  
Lili Wang
Keyword(s):  
Feature Extraction ◽  
High Speed ◽  
Wavelet Packet ◽  
Rolling Bearing ◽  
Least Square ◽  
Support Vector ◽  
Rolling Element Bearings ◽  
Kernel Independent Component Analysis ◽  
Rolling Element ◽  
Independent Features

Rolling element bearings are widely used in high-speed rotating machinery; thus proper monitoring and fault diagnosis procedure to avoid major machine failures is necessary. As feature extraction and classification based on vibration signals are important in condition monitoring technique, and superfluous features may degrade the classification performance, it is needed to extract independent features, so LSSVM (least square support vector machine) based on hybrid KICA-GDA (kernel independent component analysis-generalized discriminate analysis) is presented in this study. A new method named sensitive subband feature set design (SSFD) based on wavelet packet is also presented; using proposed variance differential spectrum method, the sensitive subbands are selected. Firstly, independent features are obtained by KICA; the feature redundancy is reduced. Secondly, feature dimension is reduced by GDA. Finally, the projected feature is classified by LSSVM. The whole paper aims to classify the feature vectors extracted from the time series and magnitude of spectral analysis and to discriminate the state of the rolling element bearings by virtue of multiclass LSSVM. Experimental results from two different fault-seeded bearing tests show good performance of the proposed method.

An overview of dynamic modeling of rolling-element bearings

2020 ◽  
pp. 095745652094827
Author(s):  
Surajkumar G Kumbhar ◽  
Edwin Sudhagar P ◽  
RG Desavale
Keyword(s):  
Dynamic Behavior ◽  
Dynamic Modeling ◽  
Operating Conditions ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Roller Bearings ◽  
Rolling Element ◽  
Vibration Responses ◽  
Vibration Signature ◽  
Element Bearing

The marvelous uniqueness of vibration responses of faulty roller bearings can be simply observed through its vibration signature. Therefore, vibration analysis has been claimed as an effective tool not only for primitive detection but also for subsequent analysis. The dynamic behavior of roller bearings has been investigated by systematic modeling of system and its validation under diverse operating conditions. This article presents an overview of imperative marks in the development of dynamic modeling of rolling-element bearing, which especially predicted vibration responses of damaged bearings. This study aims to address dimensional analysis; a new and imperative way to model the dynamic behavior of rolling-element bearings and their real-time performance in a rotor-bearing system. The findings are described with influential advantages over earlier research to pinpoint the intention behind its development. A literature summary is trailed by remarkable findings and future directions for research.

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