• 한국안전학회지
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• 제18권2호
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• pp.6-15
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• 2003

A method is presented for diagnosing the converter bearings by using acoustic emission. The flaking mechanism causing the large-scale bearing for furnace to flaw is investigated and a possibility of defect is verified by Finite Element method. he diagnosis logic is proposed fir detecting the flaw of a non-continuous rotating machine. It is proved that the acoustic emission energy can be used as a representative parameter for an acoustic event. Applying the method to the tilting bearings for steel mill in operation, the effectiveness of this logic is evaluated. It is shown that AE signal is generated only when the bearing is tilting, and the trend analysis can be focused upon this process.

• 음성과학
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• 제5권1호
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• pp.151-165
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• 1999

This paper describes a series of researches to diagnose vocal diseases using the statistical method and the acoustic signal analysis method. Speech materials are collected at the hospital. Using the pathological database, the basic parameters for the diagnosis are obtained. Based on the statistical characteristics of the parameters, valid parameters are chosen and those are used to diagnose the pathological speech signal. Cepstrum is used to extract parameters which represents characteristics of pathological speech. 3 layered neural network is used to train and classify pathological speech into normal, benign and malignant case.

• 한국공작기계학회논문집
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• 제12권6호
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• pp.22-28
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• 2003

We should maintain the maximum operation capacity for production facilities and find properly out the fault of each equipment rapidly in order to decrease a loss caused by its failure. The acoustic signals of a machine always carry the dynamic information of the machine. These signals are very useful for the feature extraction and fault diagnosis. We performed a fundamental study which develops a system of fault diagnosis for a pump. We obtained noises by a microphone, analysed and compared the signals converted to Sequency range for normal products, artificially deformed products. We tried to search a change of noise signals according to machine malfunctions and analyse the type of deformation or failure. The results showed that acoustic signals as well as vibration signals can be used as a simple method for a detection of machine malfunction or fault diagnosis.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 춘계학술대회 논문집
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• pp.99-104
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• 2003

We should maintain the minimum operation capacity for production facilities and find properly out the fault of each equipment rapidly in order to decrease a loss caused by its failure. The acoustic signals of a machine always carry the dynamic information of the machine. These signals are very useful for the feature extraction and fault diagnosis. We performed a fundamental study which develops a system of fault diagnosis for a pump. We obtained noises by a microphone, analysed and compared the signals converted to frequency range for normal products, artificially deformed products. We tried to search a change of noise signals according to machine malfunctions and analyse the type of deformation or failure. The results showed that acoustic signals as well as vibration signals can be used as a simple method for a detection of machine malfunction or fault diagnosis.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2198-2202
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• 2005

In this paper we have presented a condition monitoring method of check valve using neural network. The acoustic emission sensor was used to acquire the condition signals of check valve in direct vessel injection (DVI) test loop. The acquired sensor signal pass through a signal conditioning which are consisted of steps; rejection of background noise, amplification, analogue to digital conversion, extract of feature points. The extracted feature points which represent the condition of check valve was utilized input values of fault diagnosis algorithms using pre-learned neural network. The fault diagnosis algorithm proceeds fault detection, fault isolation and fault identification within limited ranges. The developed algorithm enables timely diagnosis of failure of check valve’s degradation and service aging so that maintenance and replacement could be preformed prior to loss of the safety function. The overall process has been experimented and the results are given to show its effectiveness.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권1호
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• pp.33-37
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• 2002

Insulation aging diagnosis system provides early warning regarding electrical equipment defects. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. Since relations of insulation aging and partial discharge dynamics are non-linear. it is very difficult to provide early warning in an electrical equipment. In this paper, we propose the design method of insulation aging diagnosis system that use a electromagnetic wave and acoustic signal to diagnose an electrical equipment. Proposed system measures the partial discharge on-line from DAS(Data Acquisition System and acquires 2D patterns from analyzing it. For filtering the noise contained in sensor signals we used ICA algorithms. Using this data, we design of the neuro-fuzzy model that diagnoses an electrical equipment and is investigated in this paper. Validity of the new method is asserted by numerical simulation.

• 한국음향학회지
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• 제21권8호
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• pp.744-756
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• 2002

현재 복부용 초음파 진단장치에 가장 일반적으로 사용되고 있는 3.5 ㎒의 굴곡형 선형배열 (curved linear array) 탐촉자가 인체 중에 만드는 과도음장을 체계적으로 해석함으로써, 음장의 측면에서 보다 우수한 초음파 영상이 기대되는 탐촉자의 설계 파라메터를 도출하고자 시도하였다. 음장해석에 있어서는 방사파형을 일정하게 가정한 상태에서 탐촉자 요소의 크기, 곡률 반경, 개구내 압전소자에 대한 구동신호의 진폭 가중치 적용 등의 파라메터를 음장 형성의 지배적인 요소로서 고려하였다. 시뮬레이션의 결과, 탐촉자의 곡률 반경 및 개구높이를 줄이고 해밍 (Hamming) 창 형태의 진폭 가중치 적용을 실시함으로써 기존의 전형적인 탐촉자보다 부엽 (side lobe)의 영향이 적은 우수한 초음파 빔을 형성하는 새로운 탐촉자의 설계 파라메터가 얻어졌다.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제52권5호
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• pp.219-225
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• 2003

This paper described about the acoustic wave measurement method to diagnose GIS for particles. We measured and analyzed the signals of acoustic waves with two type acoustic sensors having 125kHz and 50kHz resonant frequency respectively when the particles were bounced on the inside surfaces of GIS tanks by the electrostatic force. To use two sensors for the diagnosis of GIS, we set up the calibration method for this measurement method. We showed the output characteristics of two sensors according to the sizes and materials of particles in the experiment. As the results, the inception voltages bouncing particles depended on the materials and the extinction voltages bouncing them depended on the sizes and materials. We found out that the relationship between sizes of particles and output voltages of sensors didn't have linearity but the ratios of between peak values of two sensors depended on the materials of GIS enclosures and the sizes of particles.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권5호
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• pp.219-219
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• 2003

This paper described about the acoustic wave measurement method to diagnose GIS for particles. We measured and analyzed the signals of acoustic waves with two type acoustic sensors having 125kHz and 50kHz resonant frequency respectively when the particles were bounced on the inside surfaces of GIS tanks by the electrostatic force. To use two sensors for the diagnosis of GIS, we set up the calibration method for this measurement method. We showed the output characteristics of two sensors according to the sizes and materials of particles in the experiment. As the results, the inception voltages bouncing particles depended on the materials and the extinction voltages bouncing them depended on the sizes and materials. We found out that the relationship between sizes of particles and output voltages of sensors didn′t have linearity but the ratios of between peak values of two sensors depended on the materials of GIS enclosures and the sizes of particles.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 추계학술대회논문집
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• pp.43-48
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• 2008

Gear system has been widely used in industrial applications and unexpected failures of gears are not only extremely damaging but also lead to economic losses. So, early detection of fault is important for diagnosis machine condition. And acoustic emission is an efficient non destructive testing technique for the diagnosis of machine health and is useful technique for early detection of fault because it can find low-amplitude and high-frequency signal on account of high sensibility. Therefore, in this paper, the AE signal was measured and preprocessed using envelop analysis for gearbox with misalignment between pinion and gear. And then the vibration characteristic of gear misalignment was analyzed.