• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.6
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• pp.429-436
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• 2014

Most mechanical systems are now operating consistently and getting faster due to the development of automation systems. Peoples' dependence on machines have increased as when problems occur within the mechanical system, personal injury and production loss may come as a result, as most of the mechanical system's malfunctions are caused by the failure of the rotational bearing. What we need now is a maintenance system that can warn us when it detects abnormal conditions before significant damage occurs to the bearing. In this study, we have developed an acoustic emissions sensor that can figure if the bearing works under the normal condition. With this acoustic emissions sensor, we can inspect the bearing for defects by using the Heterodyne technique, which converts the ultrasound signal into audio, as a signal conditioning process.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.2
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• pp.189-194
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• 2017

An compressor that is combined with the rotor and pneumatic technology has been researching for the performance of pressure. However, the control of operations, an accurate diagnosis and the maintenance of compressor system are limited though the simple structure of compressor and compression are advantaged to reduce the energy. In this paper, the characteristic of the compressor operating under the normal or abnormal condition is realized. and the efficient diagnosis method is proposed through feature based analysis. Also, by using the GA (genetic algorithm) and SVM (support vector machine) of machine learning, the performance of feature analysis is conducted. Different misalignment mode of learning data for compressor is evaluated using the fault simulator. Therefore, feature based analysis is conducted considering misalignment mode of the compressor and the possibility of a diagnosis of misalignment is evaluated.

• Proceedings of the KSR Conference
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• 2003.10a
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• pp.125-130
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• 2003

Korean High Speed Train (KHST) designed to operate at 350km/h has been tested on high speed line in JungBu site since it was developed in 2002. The dynamic performances of railway vehicle are generally stability, safety and ride comfort. The stability performance of KHST was proved that it is stable at 400Km/h through Roller Rig test. The safety and ride comfort need to be predicted the capability of it at 350km/h by the on-line test because KHST is testing at 300km/h up to now. Therefor, in this paper, the safety and ride comfort at 350km/h are predicted the performance using the acceleration results at 300kw/h and these results show that the KHST's dynamic performances are very good. Also, it illustrate the two cases occurred the abnormal vibration of KHST during some on-line tests. The first case is that the variation of vertical acceleration of wheel is analyzed when an abrasion occur on wheel. The second case is that the lateral acceleration of wheel, bogie and body are analyzed when the KHST is unstable at high speed. The occurrences of these special phenomena were due to the some faults of the suspension and braking systems and the faults were improved. In present, it is testing with safety.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.86-91
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• 2004

It is very important to detect the bearing defects in rotating machinery since the critical failure of bearing cause a machinery shutdown. However it is difficult to detect the vibration signal resulting from the initial defects of bearing because of the high level of broadband noise. A signal processing technique, called the adaptive line enhancer(ALE) as one of adaptive filter, is studied in this work. This technique is to eliminate broadband noise without a prior knowledge of the noise and signal characteristics. Also we propose the optimal methods for selecting the three main ALE parameters such as correlation length, filter order and adaptation constant used in the adaptative process. Vibration signals for three abnormal bearings, including inner and outer raceways and ball defects, were acquired from Anderon(angular derivative of radius on)meter. The experimental results showed that the proposed technique can reliably detect the bearing defective signals masked by broadband noise.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.8
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• pp.965-970
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• 2011

We develop a diagnostic system to monitor failures in an engine-assembly line. Existing techniques such as sensory analysis, time domain analysis, frequency analysis, and statistical analysis have limitations in the diagnosis of engine-assembly failure when there are abnormal vibration waveforms (crashing and damping signals) during the assembly. We use a wavelet technique to deal with crashing and damping signals. We also implement a new technique for developing diagnostic rules from sensor data, and we demonstrate its validity.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.527-532
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• 2014

Generator is the main equipment of a power plant that generates electric power. The line frequency is 60Hz, since that is operated at 3600rpm in fossil power plant. Therefore, the specific frequency 120Hz by the electromagnetic excitation force is generated inherently. If the looseness of stator at generator happens, abnormal sound that has 120Hz and the harmonic frequency is emitted from generator frame. In that case, binding of end-winding or re-wedging is needed for the reduction of sound level. In case of severe level of sound, belly band can be additionally installed at core. In this paper, the characteristics of generator sound is described and modal data is analyzed after installation of belly band.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.1
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• pp.57-60
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• 2008

Since human listening is very sensitive to sound, for evaluating of a sound quality is required. Therefore, in the analysis for each situation, the sound evaluation is composed with sound quality factor. My researchers spends their effort to make a more reliable and more accurate of sound in term of sound quality index for various system noise. The previous methods to evaluation of the SQ about vehicle interior noise are linear regression analysis of subjective SQ metrics by statistics and the estimation of the subjective SQ values by neural network. But these are highly dependent on jury test and have many difficulties due to various environmental factors. So, to reduce jury test weight. we suggested a new method using Mahalanobis distance for SQ evaluation. Threrefore, in this study Mahalanobis distance for the vehicle interior noise was derived using the objective SQ except jury test. Finnaly, the results of the SQ evaluation was analyzed discrimination between reference and abnormal group.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.87-91
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• 2019

The diagnosis of the failure for the existing electrical facilities was based on regular preventive maintenance, but this preventive maintenance was limited in preventing a lot of cost loss and sudden system failure. To overcome these shortcomings, fault prediction and diagnostic techniques are critical to increasing system reliability by monitoring electrical installations in real time and detecting abnormal conditions in the facility early. As the performance and quality deterioration problem occurs frequently due to the increase in the number of users of the motor pump, the purpose is to build an intelligent control system that can control the motor pump to maximize the performance and to improve the quality and reliability. To this end, a vibration sensor, temperature sensor, pressure sensor, and low water level sensor are used to detect vibrations, temperatures, pressures, and low water levels that can occur in the motor pump, and to build a system that can identify and diagnose information to users in real time.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.363-369
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• 2019

Various studies have been conducted for the diagnosis of noise condition of complex rotary machines. In this study, diagnosis index using vibration signal is developed for the efficient and objective assessment of noise condition of a blower motor. The noise most commonly caused by the abnormal blower motor are Tick/Click noise and Tone noise. According to cause and noise characteristics, time-frequency analysis is used to diagnose Tick/Click noise, and smoothing in frequency domain is used to diagnose tone noise condition. The noise condition of the blower motors were diagnosed using the developed index and these results are compared with the diagnostic results by the experts. As a result, the agreement rate was about 95 %.

• Journal of the Semiconductor & Display Technology
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• v.16 no.2
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• pp.32-38
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• 2017

This paper is about the analysis on the vibration characteristic of tooling units on the precision bed in high-speed automatic lathe for precision machining. An automatic lathe operating at about 25,000 RPM is a critical factor in the self-weight stress and deformation of the bed. Especially, the resonance frequency should be grasped in advance to prevent abnormal vibration that may occur during processing. If the wrong bed is used, the resonant frequency can have a fatal influence on the precision machining and increase the defective rate of precision machined parts such as semiconductor parts. In this paper, vibration characteristics were evaluated through static load and resonance frequency analysis of automatic lathe bed. As a result, the maximum stress was 0.14MPa, the maximum deformation amount was $17.9{\mu}m$, and the natural frequency was 364.72Hz. The resonance frequency was calculated as 718Hz, and the stability was confirmed by being in the range of 400Hz or more, which is the processing condition.