• 오토저널
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• 제9권2호
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• pp.47-57
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• 1987

The objective of this study is to establish the comprehensive analytical relationship between acoustic emission and fundamental parameters of the orthogonal cutting process. The sources of acoustic emission in the orthogonal metal cutting process was identified as deformation in the shear zone and sliding friction at the chip-tool interface. The validity of this relationship is evaluated by a series of tests varing cutting speed and rake angle for A16063 tube. Strong dependence of the RMS voltage of acoustic emission on cutting speed and rake angle was observed. It was also found that the percentage contribution of AE energy at each zone for the total AE activity is constant in accordance with the change of cutting speed. The relationship between the RMS of acoustic emission and the fundamental cutting parameters was modified in order to be utilized independent of rake angle.

• Computers and Concrete
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• 제18권2호
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• pp.267-278
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• 2016

In order to observe the internal damage of concrete in real time, we introduced acoustic emission nondestructive detecting technology into a series of fracture tests; the test results revealed the whole process that concrete undergoes when it sustains damage that leads to failure, according to the change rules of the acoustic emission parameters. The results showed that both the initiation and unstable loads can be accurately determined using the abrupt change of the acoustic emission rate curves and the turning point of the acoustic emission parameters' accumulative curves. The whole process, from damage to failure, includes five phases, beginning with damage, such as cracking, a stable crack growth process, a critical unstable stage, and unstable propagation. The brittle fracture characteristics of concrete change when steel bars are joined, because the steel bars and the concrete structure bond, which causes an increase in the acoustic emission signals within the fracture process of the reinforced concrete. The unstable propagation stage is also extended. Our research results provide a valid methodology and technical explanations, which can help researchers to monitor the cracking process of concrete structures, in real time, during actual projects.

• 한국터널지하공간학회 논문집
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• 제21권5호
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• pp.657-673
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• 2019

최근 음향방출(Acoustic Emission, AE) 센서를 이용하여 지하 암반 내 구조물의 손상을 평가하는 기법이 활발하게 사용되고 있다. 암반 손상 시 발생되는 미소파괴음은 시간 및 주파수 영역에서 다양한 음향방출 특성인자로 분석된다. 암반 내 초기 균열 발생부터 최종 파괴까지의 특징을 파악하기 위해서는 외부응력 수준과 암반 강도에 따른 음향방출 특성인자 발생 양상을 이해하는 것이 중요하다. 본 연구에서는 경암과 연암 강도를 가진 화강암 시편을 이용하여 일축 압축시험을 수행하여, 암석 시편 파괴 시 발생하는 음향방출 특성인자를 분석하였다. 실험결과, 응력 비율이 증가할수록 이벤트 횟수, 실효값, 최대 진폭, 절대 에너지가 경암 시편에서 연암 시편 보다 높은 경향을 보였다. 또한, 주파수 관련 특성인자는 응력 비율 증가나 시편의 물성특성에 대해 민감도가 낮은 것으로 분석되었다. 본 연구에서 암석 시편 파괴에 따른 음향방출 특성인자 분석 결과, 실효값(RMS)이 가장 민감한 인자로 평가되었다. 본 연구의 결과는 음향방출 기반 모니터링 수행 시 암반 손상 정도 평가를 위하여 유용하게 활용될 수 있을 것으로 기대된다.

• 한국생산제조학회지
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• 제6권4호
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• pp.46-53
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• 1997

This paper presents a method of detection localized defects on tapered roller bearing in main spindle of machine tool system. The feature vectors, i.e. statistical parameters, in time-domain analysis technique have been calculated to extract useful features from acoustic emission signals. These feature vectors are used as the input feature of an neural network to classify and detect bearing defects. As a results, the detection of bearing defect conditions could be sucessfully performed by using an neural network with statistical parameters of acoustic emission signals.

• 터널과지하공간
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• 제10권1호
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• pp.59-69
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• 2000

암석 재료의 변형에 따른 미시적 파괴 현상으로부터 발생하는 미소파괴음(Acoustic Emission, AE)을 측정하여 암석 구조물 내의 미세균열의 생성과 전파를 탐지하는 연구는 지하 암반 구조물의 안정성을 비파괴검사로 평가하는데 대단히 중요하다. 본 연구에서는 암반 구조물의 보강재로 사용되는 콘크리트와 대리석 암석 시험관에 대하여 전과정 응력-변형률 곡선을 얻기 위한 강성압축시험을 실시하였고, 시험 중에 미소파괴음 발생을 측정하여 미소파괴음 파라미터 분석 및 음원추적을 수행하여 대리석과 콘크리트의 변형 및 파괴거동 특성을 살펴보았다. 또한 시험편에 계단식 반복재하시험을 수행하여 그 변형거동을 고찰하였으며, 미소파괴음 측정을 통하여 재료의 손상, 암반의 현지응력 및 콘크리트 구조물의 응력이력 등과 관련된 카이저효과를 검증하였다

• 동력기계공학회지
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• 제11권1호
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• pp.45-50
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• 2007

Acoustic emission technology is applied to diagnosis the internal leak and operating conditions of the major valves at nuclear power plants. The purpose of this study is to verify availability of the acoustic emission as in-situ diagnosis method. In this study, acoustic emission tests are performed when the pressurized high temperature steam flowed through gate valve(1st stage reheater valve) and glove valve(main steam dump valve) on the normal size of 4 and 8". The valve internal leak diagnosis system for practical field was designed. The acoustic emission method was applied to the valves at the site, and the background noise was measured for the abnormal plant condition. To improve the reliability, a judgment of leak on the system was used various factors which are AE parameters, trend analysis, signal level analysis and RMS(root mean square) analysis of acoustic signal emitted from the valve operating condition internal leak.

• 대한기계학회논문집
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• 제10권6호
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• pp.906-915
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• 1986

본 논문에서는 에너지 법칙(energy principle)에 기초한 AE RMS값과 절삭 파 라미터들 사이의 해석적인 관계를 구하기 위하여 Lee와 Shaffer의 미끄름선장 영역을 변형되는 부피로 가정하여 이론적인 식을 제시하였으며 Al의 2차원 절삭시험을 통하여 이 관계가 절삭과정의 감시에 유용하리라는 것을 확인하였다.

• 한국정밀공학회지
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• 제19권2호
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• pp.133-139
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• 2002

A number of experimental studies on burr formation in face milling operations have been pursued. They usually focus on machining parameters such as depth of cut, leed rate, spindle speed and in-plane exit angle. But it if difficult to set the correlation between burrs and the parameters on burr when such parameters are considered at the same time. Therefore, in this paper, acoustic emission (AE) is considered as an alternate way to predict burr types regardless of machining conditions. AE signals during face milling were sampled and processed, then fed into an artificial neural network to classify burr types \\\"on-line\\\".\\\".uot;.

• 한국멀티미디어학회논문지
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• 제9권12호
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• pp.1572-1579
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• 2006

An usual acoustic emission(AE) event has two widely characterized parameters in time domain, peak amplitude and event duration. But noise in AE measuring may disturb the signals with its parameters and aggrandize the signal incertitude. Experiment activity of detection of the nick inside of porcelain with AE was made and study on AE signal processing with statistic be presented in this paper in order to pick-up information expected from the signal with noise. Effort is concentrated on developing a novel arithmetic to improve extraction of the characteristic from stochastic signal and to enhance the voracity of detection. The main purpose discussed in this paper is to treat with signals on amplitudes with statistic mutuality and power density spectrum in frequency domain, and farther more to select samples for neural networks training by means of least-squares algorithm between real measuring signal and deterministic signals under laboratory condition. By seeking optimization with the algorithm, the parameters representing characteristic of the porcelain object are selected, while the stochastic interfere be weakened, then study for detection on neural networks is developed based on processing above.

• 한국항공운항학회지
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• 제17권4호
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• pp.42-47
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• 2009

Recently, the wide range of the composite materials is used for the making airplanes, trains and automobiles body for the lightweight. Despite having complex structures, composite materials usually have well defined mechanical characteristics. However, composite materials are difficult to understand the fracture mechanism clearly by simple mechanical test. Nondestructive evaluation (NDE) combined with mechanical testing can play a more important role and especially Acoustic Emission Testing (AET) would become known to be a useful tool to assess damage and fracture behavior of composites. In this study The experiment was performed to acquire the acoustic emission signal during tensile test using unidirectional CFRP specimen and the data was analyzed the acoustic emission parameters with the waveform.