• Smart Structures and Systems
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• v.18 no.5
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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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.1
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• pp.105-114
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• 1989

This study was carried out to measure the mechanical properties and the acoustic emission (AE) characteristics of the carbon fiber reinforced composites of several types of the stacking sequence. AE signals were detected during the tensile tests. The number of ringdown counts, total ringdown counts were plotted together with the load-displacement curves. The tensile load-displacement behavior of specimen is compared and discussed based on the measured AE properties in relation to the failure mechanism. With the increase of load, AE signals increased. This showed that failure had being propagated by matrix deformation and cracking, delamination, fiber debonding and breakage. Felicity ratio has been obtained by observation of ;the Kaiser effect according to the variation of load ratio. The reloading tests showed that the felicity ratio decreased obviously when the load ratio or damage increased. These AE characteristics are hopeful to be employed as the criteria to evaluate the failure processes of composites.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.12
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• pp.2891-2898
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• 2000

The objective of this paper is to develop a fiber-optic acoustic emission(AE) sensor applicable to on-line monitoring systems which is suitable for long-distance signal transmission. An AE sensor was developed by use of a fiber-optic cantilever and an extrinsic Fabry-Perot interferometer(EEPI). The efficiency of signal processing was improved by driving the high frequency AE signals into the low frequency ones. In order to verify the developed sensor, the tensile and the pencil lead fracture(PLF) tests were performed including the experiment showing the Kaiser effect. Form tests, AE signals were successfully detected in the elastic-plastic deformation range, especially higher signals at the crack propagation. The developed sensor was expected to be used for an on-line monitoring of crack propagation in mechanical system.

• Journal of Biosystems Engineering
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• v.29 no.3
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• pp.261-266
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• 2004

This study was Performed to classify the acoustic emission(AE) signal due to surface cracking and moisture movement in the flat-sawn boards of oak(Quercus Variablilis) during drying using the principal component analysis(PCA) and artificial neural network(ANN). To reduce the multicollinearity among AE parameters such as peak amplitude, ring-down count event duration, ring-down count divided by event duration, energy, rise time, and peak amplitude divided by rise time and to extract the significant AE parameters, correlation analysis was performed. Over 96 of the variance of AE parameters could be accounted for by the first and second principal components. An ANN analysis was successfully used to classify the Af signals into two patterns. The ANN classifier based on PCA appeared to be a promising tool to classify the AE signals from wood drying.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2001.10a
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• pp.116-120
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• 2001

Fiber fracture is one of the dominant failure phenomena to determine total mechanical properties in composites. Fiber fracture locations were measured by optical microscopic method and acoustic emission (AE) as functions of matrix toughness and surface treatment by the electrodeposition (ED), and then two methods were compared. Two AE sensors were attached on the epoxy specimen and fiber fracture signals were detected with elapsed time. The interfacial shear stress (IFSS) was measured using tensile fragmentation test and AE system. In ED-treated case, the number of the fiber fracture measured by an optical method and AE was more than that of the untreated case. The signal number measured by AE were rather smaller than the number of fragments measured by optical method, since some fiber fracture signals were lost while AE detection. However, one-to-one correspondence between the x-position location by AE and real break positions by optical method was generally established well. The fiber break source location using AE can be a valuable method to measure IFSS for semi- or nontransparent matrix composites nondestructively (NDT).

• Journal of the Korean Society for Nondestructive Testing
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• v.11 no.1
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• pp.31-37
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• 1991

Acoustic emission(AE) signals detected during metal cutting were applied as the experimental test to sensing tool wear and chipping on the NC vertical milling machine. The in-process detection of cutting tool wear including chipping, cracking and fracture has been investigated by means of AE in spite of vibration or noise through intermittent metal cutting, then the following results were obtained 1) When the tool wear is increased suddenly, or the amplitude of AE signals changes largely, it indicates chipping or breaking of the insert tip. 2) It was confirmed that AE signal is highly sensitive to the cutting speed and tool wear. 3) At the early period of cutting, the wear were large and RMS value increased highly by the influence of minute chipping and cracking, etc. Therefore, the above situations should be considered for the time when the tool would be changed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.59-64
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• 1997

This paper investigates the relationship between cutting conditions and Acoustic Emission(AE) signals; AEavg, AErms, AEmode, as the base working to monitor the tool wear with in-process. For this purpose, cutting tests were conducted on a CNC lathe with comprehensive cutting conditions.. It is known that AEavg and AErms are proportionaly increased as the increasing of cutting velocity and depth of cut respectively. It is also known that AEmode among three kinds of AE signals may be applied for in-process monitoring to make the self diagnosis system because of its stability to the variation of cutting condition.

• Proceedings of the Acoustical Society of Korea Conference
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• 1992.06a
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• pp.87-90
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• 1992

Detecting acoustic emission (AE) provides an appropriate method to diagonize on-line transformers, since acoustic signal is not influenced by strong electric field. Then AE versus AE signal processing method is investigated. But this processing is difficult that decision of starting point of AE wave with acoustic noise. This problem is sloved by correlation which calculate time interval between two signals eactly. This paper presents a technique locating the eact position of the partial discharge (PD) in a power transformer by the correlation of the AE signals from two ultrasonic sensors. And PD position is displayed on monitor. Laboratory tests confirmed that the proposed method can be used for locating the PD in power transformer.

• Proceedings of the KWS Conference
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• 1999.05a
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• pp.241-244
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• 1999

The purpose of this study is to examine the characteristics of stress corrosion cracking(SCC) and acoustic emission(AE) signals for the weld HAZ of HT-60 steel under corrosion control in synthetic seawater. Corrosive environment was controlled by potentiostat, and SCC experiment was conducted using a slow strain rate test method at strain rate of 10$^{-5}$ /sec. In order to verify the miroscopic fracture behaviour of the weldment during SCC phenomena, AE test was done simultaneously. Besides, correlationship between mechanical parameters and AE ones was investigated. In case of the parent, reduction of area(ROA) at -0.5V was samller than any other applied voltage such as -0.8V and -1.1V. In addition, reduction of area for the PWHT specimens at -0.8mV was larger than that of the weldment due to the softening effect according to PWHT. In case of the weldment, a lots of events was produced because of the singularities of the weld HAZ compared with the parent.

• Smart Structures and Systems
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• v.16 no.1
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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.