• Journal of Korean Tunnelling and Underground Space Association
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• v.9 no.4
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• pp.403-413
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• 2007

As rock bolts become one of the main support systems in tunnels and underground structures, the integrity of the rock bolts affects the safety of these types of structures. The purpose of this study is the evaluation of rock bolt integrity using Fourier and wavelet transforms of the guided ultrasonic waves. After five rock bolt specimens with various defect ratios are embedded into a large scale concrete block, guided waves are generated by a PZT (lead zirconate titanate) element and measured by an acoustic emission (AE) sensor. The captured signals are analyzed in the frequency domain using the Fourier transform, and in the time-frequency domain using the wavelet transform based on a Gabor wavelet. The spectrum obtained from the Fourier transform shows that a portion of high frequency contents increases with increase in the defect ratio. Peak values in the time-frequency domain represent the interval of travel time of each echo. The energy velocities of the guided waves increase with the defect ratio. This study shows that the spectrum ratio and the energy velocity may be indicators fur the evaluation of rock bolt integrity.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.62-68
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• 2001

In order to characterize the microscopic fracture behaviour of the weldment din stress corrosion cracking(SCC) phenomena, SCC and acoustic emission(AE) tests were carried out simultaneously and the correlation between mechanical paramenters obtained from SCC and AE tests was investigated. In the case of base metal, much more AE events were produced at -0.5V than at -0.8V because of the dissolution mechanism before the maximum load. Regardless of the applied voltages to the specimens, however, AE events decreased after the maximum load. In the case of weldment, lots of AE events with larger amplitude $range(40{\sim}100dB)$ were produced because of the singularities of weld HAZ in comparision to the base metal and post-weld heat-treated(PWHT) specimens. Numerous and larger cracks for the weldment were observed on the fractured surfaces by SEM examination. From these results, it was concluded that SCC for the weldment appeared most severely in synthetic seawater. Weld HAZ was softened by PWHT which also contributed to the reduced susceptibility to corrosive environment in comparison to the weldment.

• Journal of the Korean Geotechnical Society
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• v.25 no.12
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• pp.5-12
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• 2009

As rock bolts become one of the main support systems in tunnels and underground structures, the integrity of the rock bolts affects the safety of these structures. The purpose of this study is the evaluation of rock bolt integrity using wavelet transforms of the guided ultrasonic waves by using transmission test in the field. After several rock bolts with various defect ratios are embedded into a large scale concrete block and rock mass, guided waves are generated by a piezo disk element and measured by an acoustic emission (AE) sensor. The captured signals are analyzed in the time-frequency domain using the wavelet transform based on a Gabor wavelet. Peak values in the time-frequency domain represent the interval of travel time of each echo. The energy velocities of the guided waves increase with an increase in the defect ratio. The suitable curing time for the evergy velocity analysis is proposed by the laboratory test, and in-situ tests are performed in two tunnelling sites to verify the applicability of rock bolt integrity tests performed after proposed curing time. This study proves that time-frequency domain analysis is an effective tool for the evaluation of the rock bolt integrity.

• Journal of the Korean Society for Nondestructive Testing
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• v.18 no.3
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• pp.191-204
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• 1998

One of the key issues in acoustic emission (AE) during hydroproof test of filament-wound composite rocket motor cases is the determination of the optimal component of elastic wave to be monitored. To solve this problem, broadband ultrasonic wave was generated into a symmetrically filament-wound composite motor case, and was received at 105 different locations after the propagation through the composite case with different distances and directions. By analysis of the received signals, characteristics of elastic wave propagation such as frequency components, the maximum propagating distance, and velocity surface were investigated. This analysis was performed for two different conditions of the motor case; air-filled and hydraulically pressurized. Based on these information, the effect of hydraulic pressure on the wave propagation characteristics was investigated and furthermore, the optimal component of elastic wave for AE during hydroproof test of the motor case was successfully determined.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.8
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• pp.44-49
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• 2003

In case of an extrinsic Fabry-Perot interferometric sensor, the phase compensating technique is particularly necessary in applying the interferometer to detecting acoustic emission signals because of signal-fading problems. The technique makes it possible to maintain the phase at the quadrature point. In this paper, we developed the stabilization control sensor system that is composed of a broadband light source, a tunable Fabry-Perot (F-P) filter and a control-circuit board. A tension test of a composite specimen was performed to verify if the developed system could compensate the phase change induced from the tension strain and keep the phase at the quadrature point.

• Smart Structures and Systems
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• v.26 no.2
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• pp.227-239
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• 2020

Despite proven effectiveness and accuracy in laboratories, the existing damage assessment based on guided ultrasonic waves (GUWs) or acoustic emission (AE) confronts challenges when extended to real-world structural health monitoring (SHM) for railway tracks. Central to the concerns are the extremely complex signal appearance due to highly dispersive and multimodal wave features, restriction on transducer installations, and severe contaminations of ambient noise. It remains a critical yet unsolved problem along with recent attempts to implement SHM in bourgeoning high-speed railway (HSR). By leveraging authors' continued endeavours, an SHM framework, based on actively generated diffuse ultrasonic waves (DUWs) and a benchmark-free condition contrast algorithm, has been developed and deployed via an all-in-one SHM system. Miniaturized lead zirconate titanate (PZT) wafers are utilized to generate and acquire DUWs in long-range railway tracks. Fatigue cracks in the tracks show unique contact behaviours under different conditions of external loads and further disturb DUW propagation. By contrast DUW propagation traits, fatigue cracks in railway tracks can be characterised quantitatively and the holistic health status of the tracks can be evaluated in a real-time manner. Compared with GUW- or AE-based methods, the DUW-driven inspection philosophy exhibits immunity to ambient noise and measurement uncertainty, less dependence on baseline signals, use of significantly reduced number of transducers, and high robustness in atrocious engineering conditions. Conformance tests are performed on HSR tracks, in which the evolution of fatigue damage is monitored continuously and quantitatively, demonstrating effectiveness, adaptability, reliability and robustness of DUW-driven SHM towards HSR applications.

• Composites Research
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• v.15 no.1
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• pp.53-60
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• 2002

Composite ablative tubes required capabilities of ablative and structural characteristics were fabricated through filament winding technique and several experiments were conducted to evaluate the structural performance of composite ablative tubes. For this purpose, manufacturing procedures were briefly described and then resin digestion method was applied to measure the fiber volume fraction and the void content of composite ablative tubes. The configuration of tensile specimen fur composite ablative tubes with not losing the continuity of reinforced fibers was suggested by evaluating mechanical properties of several types of the specimen with different widths. Also, suitable processing variables for composite ablative tubes were determined by evaluating mechanical properties of several types of the specimen with different processing variables. In addition, acoustic emission signals were obtained during the proof test and could be applicable to study the crack initiation and the damage mode of composite ablative tubes. Finally, the structural reliability of composite ablative tubes could be verified to satisfy design requirements through the proof and burst tests.

• The Journal of Engineering Geology
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• v.6 no.2
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• pp.59-64
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• 1996

Acoustic Emission(AE) signals are emitted by a sudden release of strain energy associated with material damage. A multi-channels of LeCroy system and piezoelectric pressure transducers are employed for AE measurement to investigate the roles of AE in the propagation of macro cracks as well as the characteris-tics of AE wave in occurrence, amplitude and dominant frequency with changes in macro loading modes. Deduced crack opening volume of micro cracks varied widely and implies that AE events could be caused by crystal dislocations on a small scale and grain boundary movements on a large scale. Amplitude of first arrival AE wave emitted during mode I test was approximately 3 times higher than those from mixed mode test, while the number of AE count in mode I test was only 25% of mixed mode. It may imply that the total energy required for generation of a given fracture surface is similar regardless in change of macroloading modes.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.46-53
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• 2001

The purpose of this paper is to develop a new feature selection method for AE signal classification. The neural network of back propagation algorithm is used. The proposed feature selection method uses the difference between feature coordinates in feature space. This method is compared with the existing methods such as Fisher's criterion, class mean scatter criterion and eigenvector analysis in terms of the recognition rate and the convergence speed, using the signals from the defects in welding zone of austenitic stainless steel and in the metal contact of the rotary compressor. The proposed feature selection methods such as 2-D and 3-D criteria showed better results in the recognition rate than the existing ones.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.3
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• pp.121-126
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• 2020

Sound-based machine fault diagnosis is the automatic detection of abnormal sound in the acoustic emission signals of the machines. Conventional methods of using mathematical models were difficult to diagnose machine failure due to the complexity of the industry machinery system and the existence of nonlinear factors such as noises. Therefore, we want to solve the problem of machine fault diagnosis as a deep learning-based image classification problem. In the paper, we propose a CNN-based automatic machine fault diagnosis method using Spectrogram images. The proposed method uses STFT to effectively extract feature vectors from frequencies generated by machine defects, and the feature vectors detected by STFT were converted into spectrogram images and classified by CNN by machine status. The results show that the proposed method can be effectively used not only to detect defects but also to various automatic diagnosis system based on sound.