• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.7
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• pp.583-589
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• 2008

For the purpose of monitoring by ultrasonic test of the ball bearing conditions in rotating machinery, a system for their diagnosis was developed. ultrasonic technique is used to detect abnormal conditions in the bearing system. And various data such as frequency spectrum, energy and amplitude of ultrasonic signals, and ultrasonic parameters were acquired during experiments with the simulated ball bearing system. Based on the above results and practical application for power plant, algorithms and judgement criteria for diagnosis system was established. Bearing diagnosis system is composed of four parts as follows : sensing part for ultrasonic sensor and preamplifier, signal processing part for measuring frequency spectrum, energy and amplitude, interface part for connecting ultrasonic signal to PC using A/D converter, graphic display and software part for display of bearing condition and for managing of diagnosis program.

• Smart Structures and Systems
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• v.14 no.3
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• pp.377-395
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• 2014

Vibration-based fault detection and condition monitoring of rotating machinery, using statistical process control (SPC) combined with statistical pattern recognition methodology, has been widely investigated by many researchers. In particular, the discrete wavelet transform (DWT) is considered as a powerful tool for feature extraction in detecting fault on rotating machinery. Although DWT significantly reduces the dimensionality of the data, the number of retained wavelet features can still be significantly large. Then, the use of standard multivariate SPC techniques is not advised, because the sample covariance matrix is likely to be singular, so that the common multivariate statistics cannot be calculated. Even though many feature-based SPC methods have been introduced to tackle this deficiency, most methods require a parametric distributional assumption that restricts their feasibility to specific problems of process control, and thus limit their application. This study proposes a nonparametric multivariate control chart method, based on multiscale wavelet scalogram (MWS) features, that overcomes the limitation posed by the parametric assumption in existing SPC methods. The presented approach takes advantage of multi-resolution analysis using DWT, and obtains MWS features with significantly low dimensionality. We calculate Hotelling's $T^2$-type monitoring statistic using MWS, which has enough damage-discrimination ability. A bootstrap approach is used to determine the upper control limit of the monitoring statistic, without any distributional assumption. Numerical simulations demonstrate the performance of the proposed control charting method, under various damage-level scenarios for a bearing system.

• Tribology and Lubricants
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• v.13 no.4
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• pp.47-52
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• 1997

Friction torques, electrical contact resistances and bearing temperatures were measured on high speed angular contact ball beatings for the spindle of machine tools. The test bearings ran with oil-air lubrication at the thrust loads from 320 N to 1920 N and at the rotational speed of up to 12000 rpm. Electrical contact resistances between balls and races were measured to evaluate the formation of the lubricant film in the contact area. The test results with sufficient lubrication showed that the variations of friction torques were sensitive to the thrust loads and the rotational speeds, and that the friction torques were higher than those with insufficient lubrication. With insufficient lubrication and high thrust loads, the collapse of the lubricant film was detected even at a high rotational speed. It was concluded that these high speed beatings to run in condition of fluid lubrication should require monitoring not only the temperature increase of the bearing but also the lubricant film formation in contact areas resulting from the change in the applied load and the lubricant amount.

• Journal of Advanced Marine Engineering and Technology
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• v.12 no.2
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• pp.35-45
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• 1988

In this paper an experimental review of condition monitoring method using time domain vibration signals and statically measured wave forms of a multi-components damaged ball bearing is presented first time. Many investigators studied already about vibration characteristics of a single point damaged ball bearing but they did not make efforts to verify vibration phenomena of a multi-components damaged one. Even in case of a tripple components damaged (i.e, outer race, inner race and rolling element) one, the high frequency resonance technique (HERT) and the displacement time domain technique can be also used for its fault detection. According to experimental results undertaken a static displacement measuring method, the defect locations of components can be proposed confidently with simple calculation of the rotating angles of each component.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.325-329
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• 1992

The development of automatic production system have required intelligent diagnostic and monitoring function to repair system failure and reduce production loss by the failure. In order to perform accurate functions of intelligent system, inference about total system failure and fault analysis due to each mechanical component failures are required. Also the solution about repair and maintenance can be suggested from these analysis results. Generally, bearing is a essential mechanical component in the machinery. The bearing failure is caused by lubricant system failure, metallurgical defficiency, mechanical condition(vibration overloading misalignment), environmental effect. This study described roller bearing fault train due to stress variation and metallurgical defficiency from lubricant failure by using FTA.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.4
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• pp.305-310
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• 2014

In this study, a non-destructive evaluation (NDE) mothod is proposed for ball bearings contaminated with micro foreign substances, which were inserted into a ball bearing to create a defective specimen. The non-contact quantitative infrared thermographic technique was applied for NDE condition monitoring. Passive thermographic experiments were conducted to perform early fault diagnosis, for bearings operated at optimized torque status under a dynamic load condition. The temperature profiles for normal and defective specimens were quantitatively compared, and the thermographic data analyzed. Based on the NDE results, the temperature characteristics and abnormal fault detection of the ball bearing were quantitatively analyzed according to the rise in temperature.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.4 s.109
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• pp.404-413
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• 2006

Induction motors are the workhorse of our industry because of their versatility and robustness. The diagnosis of mechanical load and power transmission system failures is usually carried out through mechanical signals such as vibration signatures, acoustic emissions, motor speed envelope. The motor faults including mechanical rotor imbalances, broken rotor bar, bearing failure and eccentricities problems are reflected in electric, electromagnetic and mechanical quantities. The recent research has been directed toward electrical monitoring of the motor with emphasis on inspecting the stator current of the motor, The stator current spectrum has been widely used for fault detection in induction motor systems. The motor current signature analysis is the useful technique to assess machine electrical condition. This paper describes the motor condition detected by the current signatures Paralleled with vibration signatures analysis of induction motors with the roller bearing and the journal bearing type for large vertical pumps in power plant as examples to discuss for motor fault detection and diagnosis.

• 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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.2
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• pp.131-143
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• 2013

Vibration condition monitoring of low-speed rotational slewing bearings is essential ever since it became necessary for a proper maintenance schedule that replaces the slewing bearings installed in massive machinery in the steel industry, among other applications. So far, acoustic emission(AE) is still the primary technique used for dealing with low-speed bearing cases. Few studies employed vibration analysis because the signal generated as a result of the impact between the rolling element and the natural defect spots at low rotational speeds is generally weak and sometimes buried in noise and other interference frequencies. In order to increase the impact energy, some researchers generate artificial defects with a predetermined length, width, and depth of crack on the inner or outer race surfaces. Consequently, the fault frequency of a particular fault is easy to identify. This paper presents the applications of empirical mode decomposition(EMD) and ensemble empirical mode decomposition(EEMD) for measuring vibration signals slewing bearings running at a low rotational speed of 15 rpm. The natural vibration damage data used in this paper are obtained from a Korean industrial company. In this study, EEMD is used to support and clarify the results of the fast Fourier transform(FFT) in identifying bearing fault frequencies.

• Tribology and Lubricants
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• v.33 no.4
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• pp.134-140
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• 2017

With the increase in adoption of tilting pad journal bearings (TPJBs), various failure mechanisms related to TPJBs have been reported, of which pad wear is a frequently reported one. Pad wear causes change in geometry of the bearing, which can sometimes result in the failure of the entire system. The objective of this research is to investigate the influence of pad wear on the pad temperature, which is one of the widely used condition monitoring methods for TPJBs. For the theoretical investigation, thermohydrodynamic (THD) analysis was conducted by solving the generalized Reynolds equation and the 3D energy equation. The results of the analysis show that the temperature of the loaded pad increases while that of the unloaded pad decreases, when there is wear on the loaded pads. In addition, the minimum film thickness decreases with an increase in the wear depth. A validation test was conducted with a test rig, which mimics the axial turbine when a test rotor is supported by two TPJBs. The test bearing consists of five pads with a diameter of 60 mm, and a resistance temperature detector (RTD) is installed in the pad for temperature monitoring. The test was performed by replacing the two loaded pads with the worn pad. The test result for the TPJB with wear depth of $30{\mu}m$ show that the temperatures of the loaded pads are $8^{\circ}C$ higher and that of the unloaded pad is $2.5^{\circ}C$ lower than that of the normal TPJB. In addition, the predicted pad temperature shows good agreement with the measured pad temperatures.