• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1108-1113
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• 2000

A condition monitoring methodology for rotating machinery is proposed based on multivariate statistical analysis. The CMS usually are using the vibration signal amplitude such as acceleration RMS, peak and velocity RMS to detect machine faults but the information is not so enough that CMS cannot perform reliable monitoring. So new parameters are added such as shape factor, crest factor, kurtosis and skewness as time domain parameters and spectrum amplitude of rotating frequency, $2^{nd}$ harmonics and gear mesh frequency etc. as frequency domain parameters. Many parameters are combined to represent the machine state using the Hotelling's $T^2$ statistics. The proposed methodology is tested in laboratory and the on-line experiment has shown that the proposed methodology offers a reliable monitoring for rotating machinery.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.343-346
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• 2008

To improve the reliability and extend the life for a wind-turbine gearbox, the gearbox needs to be monitored and analysed exactly. This study was conducted to analyze and detect the gearbox conditions when lubricating oil contaminated by wear particles was used. Characteristics of the gearbox failure by wear particles were monitored simultaneously by the on-line measurement sensor of vibration, oil condition and temperature. For the detail vibration analyses, frequency analysis(FFT) was performed. The results of the study were summarized as follows: Vibrational signal was found sensitive to abnormal changes of the gearbox conditions when lubricant was contaminated by wear particles. Also, using frequency analysis for the harmonics of gear mesh frequency(GMF), it is found that the failure of gearbox was caused by the damages of meshing gears. However, temperature and oil condition measuring signals were found not so effective to detect any gearbox failure by oil contamination.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.5
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• pp.537-543
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• 2012

In this study, we experimentally investigate a noise mechanism related to the machining accuracy of the reducer in the driving state. We fabricate a planetary reducer and four types of gears for use in the planetary reducer. We use signal analysis to determine the noise and vibration of the reducer at different motor speeds; the motor speed is increased from 0 rpm to the maximum speed in a stepwise manner. In addition, we obtain the sound level by using a sound level meter. The machining accuracy of gears is evaluated by public organizations, Korea Testing Laboratory (KTL), on the basis of the Japanese Industrial Standard (JIS). We analyze and compare the results with the noise and vibration of the reducer.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.189-195
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• 2003

This paper represents an identification procedure for leading mechanism of a car A/V system which is composed of a DC motor and a set of plastic gears. In addition, we studied dominant noise source of rattle noise generated by external forced vibration as a car drives. we made a dynamometer to produce stationary operation on loading mechanism of A/V system because noise generated by actual loading mechanism is non-stationary signal. operating the dynamometer setup at various motor speeds, sound pressure spectra are measured and the results are analyzed. its dominant noise source is also identified by using a sound Intensity technique. we made use of multi-dimensional spectral analysis to rind a dominant rattle noise. this method is so useful to eliminate coherence between vibration sources and helps us obtain coherent output spectrum of individual vibration source which make a rattle noise.

• New & Renewable Energy
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• v.9 no.3
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• pp.5-13
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• 2013

In the previous research, dynamic results have been analyzed in the time and frequency regions. Time and frequency region can be transformed by the Fourier transform. This transform is very useful about analyzing system behaviors. However, because of coupling, it cannot give clear results in the real system including lots of defects. In this paper, we introduced the analysis based on quefrency region to represent physical means clearly from complicated results. We simulated the drive train system which has defects, and compared between frequency and quefrency region to show its excellence. To do this process, We established mathematical model. The equation of motion was derived by the Lagrange equation and constraint equations. The constraint equation included relationships about gear mesh, flexibility of shaft. About numerical analysis, the Newmark beta method was used to get results. And FFT (Fast Fourier Transform) which converts results from time domain to frequency, qufrequency was used.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.12
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• pp.1593-1598
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• 2011

The purpose of this study is to perform parameter selection and develop a method for the condition monitoring of an LCD conveyance robot. To determine the vibration characteristics of the driving part of the robot, the gear mesh frequency (GMF) of the speed-reducing gearbox is calculated and confirmed by frequency analysis. In order to ensure reproducibility of the measured data, an appropriate working pattern is selected and experiments are carried out. For condition monitoring of the robot, a wireless measurement system is constructed and used in parameter selection, with the GMF as the center. A method involving the use of the standard deviation of the measured data and another method involving the use of multiple value of amplitude are proposed.