• 대한기계학회논문집A
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• 제22권3호
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• pp.688-694
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• 1998

The ability to locate the defects in materials is one of the major attrations of the acoustic emission(AE) technique. The most conventional method for planar AE source localization is to place three or more AE sensors on the plate and to determine the source position by measuring the differences in the arrival times of the AE wave at the sensors, which is called as triangulation method. But this method can not be applied in the material of which elastic wave propagtion velocity is not known. In this paper, we propose two methods, vector method and error minimization method, for AE source location on the material with unknown AE wave velocity. In this method, it is not needed to know the propagation velocity previously, that is, we can apply this method to arbitrary material of which properties are not known exactly. Also, in this paper, the robustness to the error in the measurement of time differences are discussed for both methods. Finally, in order to evaluate the actual performances, experiments using a pencil lead break as the AE source were carried out on the aluminum plate.

• 대한안전경영과학회지
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• 제10권4호
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• pp.127-134
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• 2008

The objective of this study is to evaluate the mechanical behaviors and structural integrity of the weldment of high strength steel by using an acoustic emission (AE) techniques. Monotonic simple tension and AE tests were conducted against the 3 kinds of welded specimen. In order to analysis the effectiveness of weldability, joinability and structural integrity, we used K-means clustering method as a unsupervised learning pattern recognition algorithm for obtained multi-variate AE main data sets, such as AE counts, energy, amplitude, hits, risetime, duration, counts to peak and rms signals. Through the experimental results, the effectiveness of the proposed method is discussed.

• 한국기계가공학회지
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• 제11권4호
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• pp.154-159
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• 2012

Condition monitoring(CM) is a method based on Non-destructive test(NDT). Therefore, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days also. Because its sensitivity is higher than normal accelerometers and it can detect low energy vibration signals. A machine tool consist of many parts such as the bearings, gears, process tools, shaft, hydro-system, and so on. Condition of Every part is connected with product quality finally. To increase the quality of products, condition monitoring of the components of machine tool is done completely. Therefore, in this paper, acoustic emission method is used to detect a machine fault seeded in a gearbox. The AE signals is saved, and power spectrums and feature values, peak value, mean value, RMS, skewness, kurtosis and shape factor, were determined through Matlab.

• Journal of Mechanical Science and Technology
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• 제17권3호
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• pp.391-399
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• 2003

The thermo-acoustic emission (AE) technique has been applied for nondestructive characterization of composite laminates subjected to cryogenic cooling. Thermo-AE events during heating and cooling cycles showed a Kaiser effect. An analysis of the thermo-AE behavior obtained during the 1st heating period suggested a method for determining the stress-free temperature of the composite laminates. Three different thermo-AE types classified by a short-time Fourier transform of AE signals enabled to offer a nondestructive estimation of the cryogenic damages of the composites, in that the different thermo-AE types corresponded to secondary microfracturing in the matrix contacting between crack surfaces and some abrasive contact between broken fiber ends during thermal load cycles.

• Smart Structures and Systems
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• 제18권5호
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• pp.1063-1085
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• 2016

Taking advantage of the high sensitivity and long-distance detection capability of acoustic emission (AE) technique, this paper focuses on the crack detection in rail head, which is one of the most vulnerable parts of rail track. The AE source location and noise cancellation were studied on the basis of practical rail profile, material and operational noise. In order to simulate the actual AE events of rail head cracks, field tests were carried out to acquire the AE waves induced by pencil lead break (PLB) and operational noise of the railway system. Wavelet transform (WT) was first utilized to investigate the time-frequency characteristics and dispersion phenomena of AE waves. Here, the optimal mother wavelet was selected by minimizing the Shannon entropy of wavelet coefficients. Regarding the obvious dispersion of AE waves propagating along the rail head and the high operational noise, the wavelet transform-based modal analysis location (WTMAL) method was then proposed to locate the AE sources (i.e. simulated cracks) respectively for the PLB-induced AE signals with and without operational noise. For those AE signals inundated with operational noise, the Hilbert transform (HT)-based noise cancellation method was employed to improve the signal-to-noise ratio (SNR). Finally, the experimental results demonstrated that the proposed crack detection strategy could locate PLB-simulated AE sources effectively in the rail head even at high operational noise level, highlighting its potential for field application.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.425-430
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• 2008

To verify the system performance of portable AE leak diagnosis system which can measure with moving conditions, AE activities such as RMS voltage level, AE signal trend, leak rate degree according to AE database, FFT spectrum were measured during operation on total 11 valves of the secondary system in nuclear power plant. AE activities were recorded and analyzed from various operating conditions including different temperature, type of valve, pressure difference, valve size and fluid. The results of this field study are utilized to select the type of sensors, the frequency band for filtering and thereby to improve the signal-to-noise ratio for diagnosis for diagnosis or monitoring of valves in operation. As the final result of application study above, portable type leak diagnosis system by AE was developed. The outcome of the study can be definitely applied as a means of the diagnosis or monitoring system for energy saving and prevention of accident for power plant valve. The purpose of this study is to verify availability of the acoustic emission in-situ monitoring method to the internal leak and operating conditions of the major valves at nuclear power plants. In this study, acoustic emission tests are performed when the pressurized temperature water and steam flowed through glove valve(main steam dump valve) and check valve(main steam outlet pump check valve) on the normal size of 12 and 18 ". The valve internal leak monitoring 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, frequency analysis, voltage analysis and amplitude analysis of acoustic signal emitted from the valve operating condition internal leak.

• 한국암반공학회:학술대회논문집
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• 한국암반공학회 2006년도 춘계학술발표회 논문집
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• pp.79-93
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• 2006

It is well known that acoustic emission (AE) is indicator of rock fracturing or damage as rock is brought to failure under the uniaxial compressive loads. In this paper, an experimental study on the source location of acoustic emission on the cylindrical specimens of granite under uniaxial compression test was made. The AE source location was made by measuring the six channel AE data. Comparing to this experiment, the numerical method is applied to model the initiation and propagation of fracture by AE using a numerical code, RFPA (Realistic Failure Process Analysis). This code incorporates the mesoscopic heterogeneity in Young's modulus and rock strength characteristic of rock masses. In the numerical models, values of Young's modulus and rock strength are realized according to a Weibull distribution in which the distribution parameters represent the level of heterogeneity of the medium. The results of the simulations show that RFPA can be used not only to produce acoustic emission similar to those measurements in our experiments, but also to predict fracturing patterns under uniaxial loading condition.

• 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

• 한국해양공학회지
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• 제17권3호
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• pp.46-51
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• 2003

Acoustic emission (AE) signals, emanated during local failure of aluminum alloys, have been the subject of numerous investigations. It is well known that the characteristics of AE are strongly influenced by the previous thermal and mechanical treatment of the sample. Possible sources of AE during deformation have been suggested as the avalanche motion of dislocations, fracture of brittle particles, and debonding of these particles from the alloy matrix. The goal of the present study is to determine if AE occurring as the result of fatigue crack propagation could be evaluated by the joint time-frequency analysis method, short time Fourier transform (STFT), and Wigner-Ville distribution (WVD). The time-frequency analysis methods can be used to analyze non-stationary AE more effectively than conventional techniques. STFT is more effective than WVD in analyzing AE signals. Noise and frequency characteristics of crack openings and closures could be separated using STFT. The influence of various fatigue parameters on the frequency characteristics of AE signals was investigated.

• Smart Structures and Systems
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• 제16권1호
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• pp.213-222
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• 2015

Early detection and precise location of leakage is of great importance for life-cycle maintenance and management of municipal pipeline system. In the past few years, acoustic emission (AE) techniques have demonstrated to be an excellent tool for on-line leakage detection. Regarding the multi-mode and frequency dispersion characteristics of AE signals propagating along a pipeline, the direct cross-correlation technique that assumes the constant AE propagation velocity does not perform well in practice for acoustic leak location. This paper presents an improved cross-correlation method based on wavelet transform, with due consideration of the frequency dispersion characteristics of AE wave and the contribution of different mode. Laboratory experiments conducted to simulate pipeline gas leakage and investigate the frequency spectrum signatures of AE leak signals. By comparing with the other methods for leak location identification, the feasibility and superiority of the proposed method are verified.