• Composites Research
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• 제14권5호
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• pp.46-53
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• 2001

집중하중을 받는 일방향 보강(singly oriented ply, SOP) 섬유 금속 적층판(fiber metal laminate, FML)의 손상 거동을 음향 방출법(acoustic emission, AE)을 이용하여 연구하였다. 섬유 방향의 영향을 연구하기 위하여 다양한 섬유 방향을 가지는 SOP FML을 제작하였으며, UTM을 이용하여 압입 하중을 가하였다. 압입 시험 시 발생하는 AE신호는 150kH의 공진 주파수를 가지는 AE센서를 이용하여 측정하였으며, 여기에서 발생된 신호를 하중-변위 선도와 비교하였다. SOP FML의 손상 과정은 균열 개시, 균열 전파, 관통에 따라 3구간으로 나누어 겼다. 균열 개시전까지의 AE 신호의 특성으로 보아 미소 균열이 시편의 하부에서 발생하고 이 균열이 시편의 두께 방향으로 전파되어 섬유 분리를 발생시키는 것으로 생각된다. 발생된 균열은 섬유 방향을 따라 성장하였으며, 이 때 60~80dB의 AE신호들이 발생되었다. 관통이 발생할 때는 80~100dB의 고진폭의 AE신호가 나타나 섬유의 파괴가 발생함을 보였으며, 섬유의 방향이 증가할수록 섬유의 파괴가 많이 발생되었다 누적 AE count선도는 FML의 압입 특성을 잘 나타내어 FML의 특성 변호 예측에 유용하게 사용될 수 있을 것으로 생각된다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.108-113
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• 2005

In this study, rotary type diamond dressing system for ultra-precision centerless grinding for ferrule was developed at the first time and experiments were conducted with AE sensor and hall sensor system to verify the optimum dressing condition for ultra-precision centerless grinding for ferrule. The correlations with the condition of dressing are evaluated by AE signal analysis with root mean square (RMS) and frequency analysis. And current signals from hall sensor are also studied as a factor of dressing optimum condition selection. Dressing process was conducted to investigate the effects of depth of cut, rotating speed, and the number of overlap to select the optimum condition of rotary dressing system of ultra-precision centerless grinding machine for ferrule fabrication. In order to verify the optimum condition of dressing, AE and current signals were compared with the surface quality of dressing wheel and grinding wheel for ultra-precision ferrule grinding. All of these experiments were completed by Taguchi Methodology to reduce experimental time. Hence, the optimum condition of rotary dressing system for ultra-precision centerless grinding for ferrule fabrication can be selected following to the experiment result from signals of AE and hall sensor.

• 한국정밀공학회지
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• 제7권3호
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• pp.75-82
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• 1990

Automatic monitoring of the cutting conditions is one of the most improtant technologies in machining. In this study, the feasibility in applying acoustic emission(AE) signals for the in-process detection of endmill wear and fracture has been investigated by performing experimental test on the NC vertical milling machine with SM45C for specimen. As the results of detecting and analyzing AE signals on various cutting conditions, the followings have confirmed. (1) The RMS value of acoustic emission is related sensitively to the cutting velocity, but is not affected largely by feed rate. (2) The burst type AE signals of high level have been observed when removing chips distorderly and discontinuously. (3) When the RMS value grows up rapidly due to the increase of wear the endmill are generally broken or fractured, but when the endmills fracture at the conditions of smooth chip-flow or built-up-edge(BUE) occurred frequently, the rapid change of the RMS arenot found. And it is expected that this technigue will be quite useful for in-process sensing of tool wear and fracture.

• Structural Monitoring and Maintenance
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• 제7권1호
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• pp.13-25
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• 2020

One of the most important aspects in structural health monitoring is the detection of fatigue damage. Structural components such as heavy-duty bolts work under high dynamic loads, and thus are prone to accumulate fatigue damage and cracks may originate. Those heavy-duty bolts are used, for example, in wind power generation and mining equipment. Therefore, the investigation of new and more effective monitoring technologies attracts a great interest. In this study the acoustic emission (AE) technology was employed to detect incipient damage during fatigue testing of a M36 bolt. Initial results showed that the AE signals have a high level of background noise due to how the load is applied by the fatigue testing machine. Thus, an advanced signal processing method in the time-frequency domain, the Hilbert-Huang Spectrum (HHS), was applied to reveal AE components buried in background noise in form of high-frequency peaks that can be associated with damage progression. Accordingly, the main contribution of the present study is providing insights regarding the detection of incipient damage during fatigue testing using AE signals and providing recommendations for further research.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1468-1473
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• 2013

This paper dealt with the propagation characteristics of acoustic signals produced by partial discharges and the positioning of PD origin in insulation oil to develop insulation diagnostic techniques of oil-immerged transformers. Electrode systems such as needle to plane, plane to plane, and particle electrodes were fabricated to simulate some defects of power transformers. In addition, the frequency spectrum and propagation characteristics of acoustic signals with partial discharge (PD) in insulation oil were analyzed. Although there were differences based on the type of defect, the frequency spectra of the acoustic signals measured by wide and narrow band acoustic emission (AE) sensors were distributed in the range of 50 kHz-400 kHz. Therefore, a narrowband AE sensor is suitable for the diagnosis of oil-immersed power transformers. We could find the position of the PD source with an error margin of 10% in the experiments by calculating the position of the PD occurrence using the time difference of arrival measured by five AE sensors.

• 비파괴검사학회지
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• 제29권5호
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• pp.473-478
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• 2009

본 연구에서는 비파괴법을 이용하여 압력용기 강 다층용접부에서 채취한 표준 샤르피 시험편의 균열선단에서 형성되는 소성변형 거동을 평가하였다. 모재, 후열처리재 및 용접재를 대상으로 시험편에 기계적인 노치를 가공한 후 예균열(pre-crack)을 낸 다음 4점 굽힘실험과 음향방출(acoustic emission: AE)실험을 동시에 실시하였다. 균열선단은 용접재외 후열처리재의 경우 용융선 근처에 위치하도록 하였다. 하중이 가해짐에 따라 균열선단에서 형성되는 소성영역의 크기는 응력확대계수를 이용하여 구했으며, 각 시험편에 대한 소성역의 크기와 음향방출 특성과의 관계는 축적된 AE 에너지 관점에서 고찰하였다. 시험편에 관계없이 탄성역역에서는 거의 AE신호가 감지되지 않았으며, 대부분의 AE신호는 소성변형 과정에서 발생하였다. 또한, 용접재가 모재와 후열처리재에 비해 AE신호가 훨씬 많이 발생하였다. 모재와 후열처리재 및 용접재의 균열선단에서 소성영역 크기와 축적된 AE에너지와의 관계는 현저히 다르게 나타났으며, 용접재의 AE counts는 모재와 후열처리재에 비해 많이 발생하였다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.39-45
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• 2000

This paper describes the fundamental investigations on the in-process monitoring techniques focused on Acoustic Emission(AE) based on analytical method. Experiments were conducted on a CNC lathe using conventional carbide insert tools under various cutting conditions. As the result of this study a suggestion is given about the multi-purpose use of AE-signals detected with a single sensor for the monitoring of tool wear, built-up edge and chatter vibration in turning process.

• 한국임상약학회지
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• 제32권1호
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• pp.1-7
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• 2022

Objective: The purpose of this study was to detect signals of Adverse Events (AEs) after varenicline treatment using spontaneous AEs reporting system in Korea. Methods: This study was conducted by Korea Institute of Drug Safety and Risk Management-Korea Adverse Event Reporting System Database (KIDS-KD) reported from January 2013 to December 2017 through Korea Adverse Event Reporting System. Signals of varenicline that satisfied the data-mining indices, proportional reporting ratio, reporting odds ratio and information component were defined. The detected signals were checked whether they included in drug labels in South Korea and United States of America (USA). Results: A total number of drug AE reports associated with all drugs in the KIDS-KD reported between January 2013 and December 2017 was 2,665,429. Among them, the number of AE reports associated with varenicline was 1,398. Eighteen meaningful signals of varenicline were detected that satisfied with the criteria of data-mining indices. Finally, two signals such as hypotonia, incorrected dose administered were not included in the drug labels. Conclusion: New AE signals of varenicline that were not listed on the drug labels in South Korea and USA were detected. However, further pharmacoepidemiological studies such as randomized controlled trial are needed to evaluate the causality of the signals of varenicline.

• 한국생산제조학회지
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• 제5권2호
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• pp.38-45
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• 1996

This study was focused on the prediction of the approprite tool life by clarifying the correlation between progressive drill wear and AE signal. on drilling SM45C the following results have been obtained; RMSAE, AE CUM-CNTS had a tendency to increase slowly according to wear size, at 1000rpm, 150mm/min However, these increased suddenly in the range of 0.20~0.22mm wear, about 102 holes and had a tendency to go up and down until the drilling was impossible. The sudden increase of AE signals shows that something is wrong and it is closely connected with drill wear and chipping. It also makes the working surface bad From the above results, AE signals could be used to monitor the drill's condition and to determine the right time to change tools.

• 한국철도학회논문집
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• 제4권3호
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• pp.79-86
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• 2001

The signal pattern recognition method by acoustic emission signal is applied to detect and classify the defects of a journal bearing in a power plant. AE signals of main defects such as overheating, wear and corrosion are obtained from a small scale model. To detect and classify the defects, AE signal pattern recognition program is developed. As the classification methods, the wavelet transformation analysis, the frequency domain analysis and time domain analysis are used. Among three analyses, the wavelet transformation analysis is most effective to detect and classify the defects of the journal bearing..