• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.6
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• pp.71-77
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• 1999

Monitoring of Cutting tool wear is a critical issue in automated machining system and has been extensively studied for many years. An austempered ductile iron(ADI) exhibits the excellent mechanical properties and the wear resistance. ADI has generally the poor machinability due to the characteristic. This paper presents the in-process detection of flank wear of cutting tools using the acoustic emission sensor and the digital oscilloscope. The amplitude level of AE signal(AErms) is mainly affected by cutting speed and it is proportional to cutting speed. There have been the relationship of direct proportion between the amplitude level of AE signals and the flank wear width of cutting tool. The flank wear with corresponding to the tool life is successfully detected with the monitor-ing system used in this study.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.266-269
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• 2002

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. For this study, the micro-grooving machine was developed. The experiments were performed using diamond blade and CBN blade f3r machining STD11. Evaluating the machining conditions, frequency spectrum analysis of acoustic emission (AE) signals according to each conditions were applied.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.163-170
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• 1997

End milling experiments are conducted to investigate characteristics of acoustic emission (AE) and cutting force singals due to tool fracture. The AE signals are obtained with a sensor attached to cutting fluid discharge nozzle. Tool states are identified with scanning electron microscopy and optical microscopy. It is demonstrated that the AE signals provide reliable informations about the cutting processes and tool states. Morever, tool fracture can be detected successfully using both the AE count rate and the standard deviation of principal cutting force.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.05a
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• pp.39-43
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• 2002

As the concept of the smart structure, monitoring of acoustic emission (AE) can be applied to inspect the fracture of the entire structure in operating condition using built-in sensors. The objective of this study is to find the characteristics of matrix crack signals in composites due to the different specimen shapes. To detect matrix crack signals, we performed tensile tests by changing the thickness, width and length of the specimen. For the quantitative evaluation, time frequency analysis such as short-time Fourier transform (STFT) was used to characterize the matrix crack signals from PZT sensor. The experimental result shows the distinctive signal features in frequency domain due to the different specimen shapes.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.20-27
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• 2000

A chatter vibration and a workpiece burn are the main phenomena to be monitored in modern grinding processes. This study describes a trouble diagnosis of the cylindrical plunge grinding process using the power and acoustic emission (AE) signals. The raw signals of the power and the AE occurred during the grinding operation were sampled and analyzed to determine the relationship between each fault and change of signals. A neural network that has a high success rate of the fault detection was used. Furthermore, an analysis on the influence of parameters to the chatter vibration and the grinding burn was conducted.

• Computers and Concrete
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• v.8 no.5
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• pp.563-581
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• 2011

The signal-based acoustic emission (AE) characterization of concrete fracture process utilizing home-programmed AE monitoring system was performed for three kinds of static loading tests (Cubic-splitting, Direct-shear and Pull-out). Each test was carried out to induce a distinct fracture mode of concrete. Apart from monitoring and recording the corresponding fracture process of concrete, various methods were utilized to distinguish the characteristics of detected AE waveform to interpret the information of fracture behavior of AE sources (i.e. micro-cracks of concrete). Further, more signal-based characters of AE in different stages were analyzed and compared in this study. This research focused on the relationship between AE signal characteristics and fracture processes of concrete. Thereafter, the mode of concrete fracture could be represented in terms of AE signal characteristics. By using cement-based piezoelectric composite sensors, the AE signals could be detected and collected with better sensitivity and minimized waveform distortion, which made the characterization of AE during concrete fracture process feasible. The continuous wavelet analysis technique was employed to analyze the wave-front of AE and figure out the frequency region of the P-wave & S-wave. Defined RA (rising amplitude), AF (average frequency) and P-wave & S-wave importance index were also introduced to study the characters of AE from concrete fracture. It was found that the characters of AE signals detected during monitoring could be used as an indication of the cracking behavior of concrete.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.359-360
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• 2008

• Journal of the Korean Society for Nondestructive Testing
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• v.7 no.1
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• pp.7-17
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• 1987

Leak detection testing for the pipeline system was performed by the acoustic emission method. It was found that the detected signal spectrum was influenced by the frequency response of sensors and pressure changes. AE parameters and frequency spectrum distributions were used to analyze the leak signals. The slope rise time of AE parameters were the important factors for distinguishing leak signals. The amplitude of leak signal was more affected by the changes of leak, rate and pressure than those of leak type.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.56-60
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• 1996

An experimental study on the grinding temperature and Acoustic Emission(AE) signals due to the different shapes of wheel was conducted. The grinding characteristics by slotted shapes of wheel changed by width and helical angle, were compared with those by general one. Lower grinding temperature was obtained for 30$^{\circ}$ helical angle with 10mm width, Root Mean Square(RMS) values of AE signals were higher for slotted wheel rather than general one.

• Nuclear Engineering and Technology
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• v.47 no.4
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• pp.454-460
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• 2015

Acoustic emission (AE) is one of the promising methods for detecting the formation of stress corrosion cracks (SCCs) in laboratory tests. This method has the advantage of online inspection. Some studies have been conducted to investigate the characteristics of AE parameters during SCC propagation. However, it is difficult to classify the distinct features of SCC behavior. Because the previous studies were performed on slow strain rate test or compact tension specimens, it is difficult to make certain correlations between AE signals and actual SCC behavior in real tube-type specimens. In this study, the specimen was a AISI 304 stainless steel tube widely applied in the nuclear industry, and an accelerated test was conducted at high temperature and pressure with a corrosive environmental condition. The study result indicated that intense AE signals were mainly detected in the elastic deformation region, and a good correlation was observed between AE activity and crack growth. By contrast, the behavior of accumulated counts was divided into four regions. According to the waveform analysis, a specific waveform pattern was observed during SCC development. It is suggested that AE can be used to detect and monitor SCC initiation and propagation in actual tubes.