• International Journal of Precision Engineering and Manufacturing
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• v.8 no.3
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• pp.54-59
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• 2007

It is widely recognized that increasing the accuracy and diversity of rotating machinery necessitates an appropriate diagnostic technique and maintenance system. Until now, operators have monitored machinery using their senses or by analyzing simple changes to root mean square output values. We developed an expert diagnostic system that uses fuzzy inference to expertly assess the condition of a machine and allow operators to make accurate judgments. This paper describes the hardware and software of the expert diagnostic system. An assessment of the diagnostic performance for five fault phenomena typically found in pumps is also described.

• Journal of KSNVE
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• v.10 no.6
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• pp.985-990
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• 2000

The signals that can be obtained from rotating machines often convey the information of machine. For example, if the machine under investigation has faults, then these signals often have pulse signals, embedded in noise. Therefore the ability to detect the fault signal in noise is major concern of fault diagnosis of rotating machine, In this paper, minimum variance cepstrum (MV cepstrum) . which can easily detect impulse in noise, has been applied to detect the type of faults of ball bearing system. To test the performance of this technique. various experiments have been performed for ball bearing elements that have man made faults. Results show that minimum variance cepstrum can easily detect the periodicity due to faults and also shows the pattern of excitation by the faults.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.268-277
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• 1999

Impulsive acoustic and vibration signals within gear are often induced by impacting of fault tooths in gear. Thus the detection of these impulses can be useful for fault diagnosis. Recently there is an increasing trend towards the use of higher order statistics for fault detection within mechanical systems based on the observation that impulsive signals then to increase the kurtosis values. We show that the fourth order Wigner Moment Spectrum, called the Wigner Trispectrum, has found superior detection performance to second order Wigner distribution for typical impulsive signals in a condition monitoring application. These methods are also applied to data sets measured within an industrial gear box.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.21 no.1
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• pp.13-16
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• 2010

Diagnosis of a patient with dysphonia begins with a thorough history and physical examination. Larynx can be visualized either indirectly or directly with a rigid or flexible laryngoscope. One notable limitation of simple indirect laryngoscopy is that the examination dose not yields a recordable and reproducible image of the larynx and vocal tract. And unaided human eye is unable to visualize the vibratory patterns of the true vocal cord during phonantion. When available, stroboscopy provides useful information regarding vocal told closure, vibration, and mucosal wave which is useful to decide between microsurgery, vocal reeducation or a combined treatment Even there are some limitations, recognition of the advantages and disadvantages of stroboscopy allows for optimal appreciation and stroboscopy remains an essential diagnostic tool in the assessment of dysphonia.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.27-28
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• 2018

본 논문에서는 구동 장치의 다양한 상태를 나타내는 소음과 진동으로부터 특징데이터를 추출하여 이를 학습 한 후 실시간으로 장치의 상태를 진단하는 하였다. 실제 현장에서 발생할 수 있는 예측 외 소음환경에 유연하게 대처하기 위해 CNN모델 사용과 소리, 진동 데이터의 Butterworth filter와 Kalman filter를 적용하여 노이즈 배제처리 하였다. 제안된 시스템의 유용성을 확인하기 위해 제안된 시스템과 기존 CNN기반 시스템을 소음환경에서 비교 실험하였다.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.1
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• pp.49-52
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• 2020

Since power plant is an important system to provide electricity, it is necessary to monitor it in order to operate safely. Much information related with machine diagnosis exists in written form instead of digital data. So, it causes difficulties of analyzing and finding solutions. Rulebased expert system can provide flexible and effective solutions to users. In this paper, Recursive Bayesian Estimation is applied in order to increase accuracy of solutions.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.643-646
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• 2005

The paper discusses the main problems in induction motor diagnosis by motor current and vibration signals, possible faults and effects produced by these faults in the signal spectrums. Decision Tree is introduced as a tool to diagnose the motor status, this expert system is implemented to detect the incipient defects, supervise and predict them, and plan the maintenance of the motor.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.452-454
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• 1999

In this paper, sample coils for stator form-wound winding of traction motor were made for the accelerative thermal degradation composed of heat, vibration, moisture and overvoltage. In progress of test periods, diagnosis tests such as insulation resistance, dielectric loss and partial discharge were investigated. Reliability and expected life were evaluated on the insulation system for 200 class traction motor considering various environmental stress.

• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.91-97
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• 1999

We propose a new method for measuring the frequency characteristics of phase velocity along a bone for bending vibration modes to diagnose its mechanical characteristics. By introducing a simple model of a distributed-constant-network, the phase velocity is determined for each frequency from the spatial distribution of velocity along a radius bone surface which is measured by the ultrasonic Doppler method.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.649-659
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• 2019

Vibration-based structural damage detection through optimization algorithms and minimization of objective function has recently become an interesting research topic. Application of various objective functions as well as optimization algorithms may affect damage diagnosis quality. This paper proposes a new damage identification method using Moth-Flame Optimization (MFO). MFO is a nature-inspired algorithm based on moth's ability to navigate in dark. Objective function consists of a term with modal assurance criterion flexibility and natural frequency. To show the performance of the said method, two numerical examples including truss and shear frame have been studied. Furthermore, Los Alamos National Laboratory test structure was used for validation purposes. Finite element model for both experimental and numerical examples was created by MATLAB software to extract modal properties of the structure. Mode shapes and natural frequencies were contaminated with noise in above mentioned numerical examples. In the meantime, one of the classical optimization algorithms called particle swarm optimization was compared with MFO. In short, results obtained from numerical and experimental examples showed that the presented method is efficient in damage identification.