• Computational Structural Engineering
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• v.36 no.1
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• pp.15-23
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• 2023

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.4
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• pp.405-413
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• 2000

This paper present study on the application of sound pressure and vibration signals to detect the presence of defects in a rolling element bearing using a statistical analysis method. The well established statistical parameters such as the crest factor and the distribution of moments including kurtosis and skew are utilized in this study. In addition, other statistical parameters derived from the beta distribution function are also used. A comparison study on the performance of the different types of parameter used is also performed. The statistical analysis is used because of its simplicity and quick computation. Under ideal conditions, the statistical method can be used to identify the different types of defect present in the bearing. In addition, the results also reveal that there is no significant advantages in using the beta function parameters when compared to using kurtosis and the crest factor for detecting and identifying defects in rolling element bearings from both sound and vibration signals.

• Tribology and Lubricants
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• v.36 no.6
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• pp.371-377
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• 2020

In In this study, we compared the results of a ball bearing life prediction model based on rolling element loads with the results of fatigue life prediction of ball bearings when a stress-based contact fatigue life prediction technique is applied to the ball bearing. We calculate the load acting on each rolling element by the external load of the bearing and apply the result to the Lundberg-Palmgren (LP) theory to calculate ball bearing life based on the rolling element. We also calculate stress-based ball bearing life through contact and fatigue analyses based on contact modeling of the ball and raceway while considering the fatigue test results of AISI 52100 steel. In stress-based life prediction, we use three high-cycle fatigue-determination equations that can predict the fatigue life when multi-axis proportional loads such as rolling-slide contact conditions are applied. These equations are derived from the stress invariant and critical plane methods and the mesoscopic approach. Life expectancy results are compared with those of the LP model. Results of the analysis indicated that the fatigue life was predicted to be lower in the order of the Crossland, Dang Van, and Matake models. Of the three, the Dang Van fatigue model was found to be the closest to the LP life.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.324-328
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• 2007

Vibration monitoring of rolling element bearings is probably the most established diagnostic technique for rotating machinery. Acoustic Emission (AE) Analysis is an extremely powerful technology that can be used within a wide range of applications of non destructive testing. Therefor, this paper investigates the detection methods using AE for rolling element bearings about low-speed. Two transducers, the accelerometer and acoustic emission sensor, are used to acquire data and the results are compared for the capacity of early fault detection.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.11a
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• pp.166-171
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• 2001

In order to improve the efficiency of the design process and the quality of the resulting design for the application-based exclusive rolling element bearings, this study propose design methodologies by using a genetic-based combinatorial optimization. By the presence of discrete variables such as the number of rolling element (standard component) and by the engineering point of views, the design problem of the rolling element bearing can be characterized by the combinatorial optimization problem as a fully discrete optimization. A genetic algorithm is used to efficiently find a set of the optimum discrete design values from the pre-defined variable sets. To effectively deal with the design constraints and the multi-objective problem, a ranking penalty method is suggested for constructing a fitness function in the genetic-based combinatorial optimization. To evaluate the proposed design method, a robust performance analyzer of ball bearing based on quasi-static analysis is developed and the computer program is applied to some design problems, 1) maximize fatigue life, 2) maximize stiffness, 3) maximize fatigue life and stiffness, of a angular contact ball bearing. Optimum design results are demonstrate the effectiveness of the design method suggested in this study. It believed that the proposed methodologies can be effectively applied to other multi-objective discrete optimization problems.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2003.11a
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• pp.377-383
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• 2003

In this study, the methodology for determination of shoulder height in the internal shape design of ball bearing using 3D contact analysis is proposed. The quasi-static analysis of a ball bearing was performed to calculate the distribution of applied contact load and angles among the rolling elements. From each rolling element loads and the contact geometry between ball and inner/outer raceway, 3D contact analyses using influence function are conducted. These methodology is applied to HDD ball bearing. The critical axial load and the critical shoulder height which are not affected by edge in the present shoulder height is calculated. The proposed methodology may be applied to other rolling element bearing for the purpose of reducing the material cost and improving the efficiency of the bearing design process.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.49-56
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• 1999

This paper present a study on the application of sound pressure and vibration signals to detect the presence of defects in a rolling element bearing using a statistical analysis method. The well established statistical parameters such as the crest factor and the distribution of moments including kurtosis and skewless are utilized in this study. In addition, other statistical parameters derived from the beta distribution function are also used. A comparison study on the performance of the different types of parameter used is also performed. The statistical analysis is used because of its simplicity and quick computation. Under ideal conditions, the statistical method can be used to identify the different types of defect present in the bearing. In addition, the results also reveal that there is no significant advantages in using the beta function parameters when compared to using kurtosis and the crest factor for detecting and identifying defects in rolling element bearings from both sound and vibration signals.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1439-1444
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• 2005

Induction motors are the most commonly used electrical drives because they are rugged, mechanically simple, adaptable to widely different operating conditions, and simple to control. The most common faults in squirrel-cage induction motors are bearing, stator and rotor faults. Surveys conducted by the IEEE and EPRI show that the most common fault in induction motor is bearing failure (${\sim}$40% of failure). Thence, this paper addresses experimental results for diagnosing faults with different rolling element bearing damage via motor current spectral analysis. Rolling element bearings generally consist of two rings, an inner and outer, between which a set of balls or rollers rotate in raceways. We set the experimental test bed to detect the rolling-element bearing misalignment of 3 type induction motors with normal condition bearing system, shaft deflection system by external force and a hole drilled through the outer race of the shaft end bearing of the four pole test motor. This paper takes the initial step of investigating the efficacy of current monitoring for bearing fault detection by incipient bearing failure. The failure modes are reviewed and the characteristics of bearing frequency associated with the physical construction of the bearings are defined. The effects on the stator current spectrum are described and related frequencies are also determined. This is an important result in the formulation of a fault detection scheme that monitors the stator currents. We utilized the FFT, Wavelet analysis and averaging signal pattern by inner product tool to analyze stator current components. The test results clearly illustrate that the stator signature can be used to identify the presence of a bearing fault.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.05a
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• pp.105-110
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• 2002

The use of microporous polymer lubricants (MPLs) can eliminate the storage, sealing, and pumping problems associated with liquid lubricants, This paper discusses the use of MPLs for a component as rolling-element bearings. An MPL composed of 40% HDPE and 60% ester oil was synthesized and the MPL was applied to a ball bearing. The MPL ball bearing, filled with the MPL instead of the usual grease pack, tested and compared with the usual grease sealed ball bearing. The MPL applied to a ball bearing showed lubricant properties as good as usual grease, and showed higher performance in bearing oil leakage test, rotating torque test and thermal test at high speed running than usual grease.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1993.12a
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• pp.77-84
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• 1993

Systems with journal bearings generally operate in large scale and under severe loading conditions such as steam generator turbines and internal combustion engines, in contrast to the machineries using rolling element bearings. Failure of the bearings in these machineries can result in the system breakdown. To avoid the time consuming repair and considerable economic loss, the detection of incipient failure in journal bearings becomes very important. In this experimental approach, acoustic emission monitoring is employed to the detection of incipient failure caused by intervention of foreign particles most probable in the journal bearing systems. It has been known that the intervention of foreign materials, insufficient lubrication and misassembly etc. are principal factors to cause bearing failure and distress. The experiment was conducted under such designed conditions as inserting alumina particles to the lubrication layer in the simulated journal bearing system. The results showed that acoustic emission could be an effective tool to detect the incipient failure in journal bearings.