• 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).

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.142-145
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• 1995

It is important from prevention of the malfunction and an important accident by the failuer, to detect a failuer in revolution devices. The acoustic emission(AE) method is expected as means that defects an abnormal phenomenon of revolution devices earlily and utilized. Although a research example by the AE method is reported regarding a gears, little reserch has been conducted using the AE method for running gears in a bending fatigue process of spur gear teeth. Therefore, in this report, with two micro AE sensors attached to the side of the gear, AE was measured in a bending fatigue process of a carburizing gear by using the power circurating-type machine and AE source location in gear teeth were required. By various analysis in these data, the AE characteristics in the fatigue damaging process of the gear tooth were determined.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.360-364
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• 2004

The objective of this study is to estimate the feasibility of acoustic emission method Jar the internal leak from the valves in nuclear power plants. The acoustic emission method was applied to the valves at the site, and the background noise was measured for the abnormal plant condition. From the comparison of background noise data with the experimental results as to relation between leak flow and acoustic signal, the minimum leak flow rates that am be detected by acoustic signal was suggested. When the background noise level are higher than the acoustic signal, the method described below was considered that the analysis the remainder among the background noise frequency spectrum and the acoustic signal spectrum.

• Journal of Welding and Joining
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• v.20 no.1
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• pp.26-33
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• 2002

This study was undertaken to obtain the fundamental knowledges on the weld deflects and it's realtime monitoring method. The paper describes the results of high speed photography, acoustic emission (AE) detection and plasma light emission (LE) measurements during $CO_2$ laser welding of STS 304 stainless steel and A5083 aluminum alloy in different welding condition. The characteristic frequencies of plasma and keyhole fluctuations at different welding speed and shield gases were measured and compared with the results of Fourier analyses of temporal AE and LE spectra, and they had considerably good agreement with keyhole and plasma fluctuation. Namely, the low frequency peaks of AE and LE shifted to higher frequency range with the welding speed increase, and leer the argon shield gas it was higher than that in helium and nitrogen gases. The low frequencies dominating in fluctuation spectra of LE probably reflect keyhole opening instability. It is possible to monitor the weld bead deflects by analyzing the acoustic and/or plasma light emission signals.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.2
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• pp.258-266
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• 2012

Recently, Acoustic Emission (AE) 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 rolling element bearing problems and Wavelet transform is a powerful method to detect faults occurred on gearboxes. However, exact method for AE signal is not developed yet. Therefore, in this paper, two methods, which is Hilbert transforms (HT) and Hilbert-Huang transforms (HHT), will be compared for development a signal processing method for early fault detection system by using AE. AE signals were measured through a fatigue test. HHT has better advantages than HT because HHT can show the time-frequency domain result. But, HHT needs long time to process a signal, which has a lot of data, and has a disadvantage in de-noising filter.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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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.

• Journal of Power System Engineering
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• v.11 no.1
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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.

• 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.

• Proceedings of the Safety Management and Science Conference
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• 2008.04a
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• pp.185-196
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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. Simple tension and AE tests were conducted against the 3 kind of welding test specimens. 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 multivariate 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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.4
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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.