• Journal of the Korean Society for Nondestructive Testing
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• v.11 no.2
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• pp.15-21
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• 1991

A wireless acoustic emission (AE) system has been developed for continuous monitoring of rotating structures such as turbine rotors. The cable between preamplifier and signal processing unit of a conventional AE system was replaced by the frequency modulated telemetry. The detected signals were modulated and transmitted as an RF signals by the transmitting module, then received and demodulated by the receiving module. The distance between the transmitting and the receiving antennas could be separated up to 10cm within a reasonable signal-to-noise ratio. The simulated AE signals generated by pencil lead breaks from rotating structures were successfully detected using the developed wireless AE monitoring system.

• Journal of the Korean Society of Safety
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• v.6 no.3
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• pp.50-55
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• 1991

It is well known that mechanisms of fracture and crack growth depend upon material characteristics such as fracture toughness, environmental condition, cracd geometry and mechanical properties. It seems to be very important to investihate the effects of the above factors on the behavior of structural components which contain flaws for the detailed evaluation of their intehrity. In this experimental research, fracture behaviors of moterials were investigated by using Acoustic Emission(AE) technique. The fracturing processes of materials were estimated through both the tension specimens. For the detrmlnatlon of yied strength or fracture toughness, the critical applied load at the crack initiation and propagation is thought to be very important. The critical applied load(PQ) was determined through AE signal. The source of AE signal was estimated by fractography analysis. These experimental results may contribute to the safety analyses and the evaluation of strength of structures.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.47-54
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• 2003

Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing process. STD11 has been known as difficult-to-cut materials. The micro-grooving machine was developed for this study and the experiments were performed using CBN blade for machining STD11. Evaluating the machining conditions, frequency spectrum analysis of acoustic emission (AE) signals according to each conditions were applied. Fuzzy clustering method for associating the preprocessor outputs with the appropriate decisions was followed by frequency spectrum analysis. FFT is used to decompose AE signal into different frequency bands in time domain, the root mean square (RMS) values extracted from the decomposed signal of each frequency band were used as features.

• 한국기계연구소 소보
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• s.19
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• pp.61-68
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• 1989

As the system monitoring technology become required in order to improve the system performance and the productivity, we’ve studied to the detection for the tool wear and the tool breakage using AE sensors that is able to detection of generated high frequency stress pulse at cutting. The detection system is consist of a sensing part, a amplifier part, a signal processing part, and a analysis & output part. The moment (a rms and a kurtosis) of statistical method is used for analysis of AE singnal. The experiment are carried out in a CNC lathe. In this study, we achieved that the amplitude level of the AE signal and statistical moments was largely changed as the tool failure. The change rate of Kurtosis was especially large, but the change rate of the rms was small.

• Journal of Ocean Engineering and Technology
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• v.16 no.2
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• pp.67-71
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• 2002

Damage process of CFRP laminates was characterized by Acoustic Emission (AE). The main objective of this study is to determine if the sources of AE in CERP laminates could be identified from the characteristics of the waveform signals recorded during monotonic tensile test. The time history and power spectrum of each individual wave signal recorded during test were examined and classified according to their special characteristics. The wave from and frequency of AE signal from a specimens is an aid to the determination of the extent of the different fracture mechanism such as matrix crack, debonding, fiber pull-out and fiber fracture as load is increased. Four distinct types of signals were observed regardless of specimen condition. The result showed that the AE method could be effectively used for analysis of fracture mechanism in CFRP laminates.

• Journal of the Korean Institute of Gas
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• v.11 no.4
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• pp.64-72
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• 2007

Under the AE methods, the valid condition analysis and evaluation the leak etc, resulted by the AE signal pattern on the bottom plate of ground tank at full. In next more, the gradient of accumulation amplitude distribution analysis and comparison the energy, count, and duration time that noise of EMI signal were removed. EMI signal showed height-energy, count, and duration time, it also appeared great gradient of accumulation distribution. Then, with the pure remaining AE signals cluster analysis and location. It would possibly assume of damage with corrosion. Total cluster 20 and energy showed between the maximum 11,990 and 8,565 which is much lower than above figure and event number showed from 8 to 5. Even when it difficult to certify damage by open, as it is raised higher height-sensitivity and threshold by 60 dB. It would possibly presume of location source more accurately.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.331-337
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• 2013

Acoustic Emission technique is widely applied to develop the early fault detection system, and the problem about a signal processing method for AE signal is mainly focused on. In the signal processing method, envelope analysis is a useful method to evaluate the bearing problems and Wavelet transform is a powerful method to detect faults occurred on rotating machinery. However, exact method for AE signal is not developed yet. Therefore, in this paper two methods which are Hilbert transform and DET for feature extraction. In addition, we evaluate the classification performance with varying the parameter from 2 to 15 for feature selection DET, 0.01 to 1.0 for the RBF kernel function of SVR, and the proposed algorithm achieved 94% classification accuracy with the parameter of the RBF 0.08, 12 feature selection.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.7
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• pp.891-897
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• 2013

In this study, the compressive deformation behaviors of aluminum alloy under high strain rates were investigated by means of a SHPB test. An acoustic emission (AE) technique was also employed to monitor the signals detected from the deformation during the entire impact by using an AE sensor connected to the specimen with a waveguide in real time. AE signals were analyzed in terms of AE amplitude, AE energy and peak frequency. The impacted specimen surface and side area were observed after the test to identify the particular features in the AE signal corresponding to the specific types of damage mechanisms. As the strain increased, the AE amplitude and AE energy increased whereas the AE peak frequency decreased. It was elucidated that each AE signal was closely associated with the specific damage mechanism in the material.

• Composites Research
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• v.14 no.1
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• pp.1-7
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• 2001

In this study, damage evaluation of glass fiber reinforced thermoplastic composites was investigated with acoustic emission method. Specimens of 1.7mm thickness laminate were made from PET and 7 layers o171ass fabrics. Notch and impact loading were added to the specimen and normal tensile test and tensile test with the dead load were carried out. AE signal was measured as the functions of notch ratio to the width0 and impact energy in order to find out the correlation between fracture mode and AE parameters. The result has shown that low amplitude of AE signal was due to the microcrack of matrix and its growth, whereas the amplitude in the mid range was the response to the delamination and interfacial separation. In the range of high amplitude above 90dB. the fracture of glass fabric was found. Tensile strength decreased with increasing notch ratio to the width and impact energy because of tile effect or delamination, the cracking of matrix and stress concentration. In proportion to the size of damaged area. AE signal showed its wider range of frequency and energy as well as increased number of hits.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.3
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• pp.231-238
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• 2020

This paper investigates the soundness of porcelain insulators associated with the acoustic emission (AE) technique. The AE technique is a popular non-destructive method that measures and analyzes the burst energy that occurs mainly when a crack occurs in a high-frequency region. Typical AE methods require continuous monitoring with frequent sensor calibration. However, in this study, the AE technique excites a porcelain insulator using only an impact hammer, and it applies a high-pass filter to the signal frequency range measured only in the AE sensor by comparing the AE and the acceleration sensors. Next, the extracted time-domain signal is analyzed for the damage assessment. In normal signals, the duration is about 2ms, the area of the envelope is about 1,000, and the number of counts is about 20. In the damage signal, the duration exceeds 5ms, the area of the envelope is about 2,000, and the number of counts exceeds 40. In addition, various characteristics in the time and frequency domain for normal and damage cases are analyzed using the short-time Fourier transform (STFT). Based on the results of the STFT analysis, the maximum energy of a normal specimen is less than 0.02, while in the case of the damage specimen, it exceeds 0.02. The extracted high-frequency components can present dynamic behavior of crack regions and eigenmodes of the isolated insulator parts, but the presence, size, and distribution of cracks can be predicted indirectly. In this regard, the characteristics of the surface crack region were derived in this study.