• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3383-3388
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• 2007

To compare the sensor performance of AE leak diagnosis system which can measure valve leak conditions, AE activities such as RMS voltage level, AE signal trend, leak rate degree according to AE database, FFT spectrum were measured on valve of the simulated test system for power plant. AE activities were recorded and analyzed from various operating conditions including different temperature, pressure difference, valve size and fluid using both piezoelectric acoustic emission sensor and Pb-Free acoustic emission sensor. The results of this study are utilized to select the type of sensors, the frequency band for filtering and thereby to improve the signal-to-noise ratio for diagnosis or monitoring of valves in operation. As the final result of application study above, portable type leak diagnosis system by AE was developed. The outcome of the study can be definitely applied as a means of the diagnosis or monitoring system for energy saving and prevention of accident for power plant valve.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.899-900
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.560-565
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• 2001

Recently, machining process monitoring technique based on AE(acoustic emission) signal is used widely and becomes very important technique in machining process for improving the efficiency and the confidence of the systems. In this study, we fabricated a cheap acoustic emission sensor and monitoring system and estimated the properties of them through comparing with commercial AE sensor systems. In addition, we evaluated the performance of the fabricated sensor in polishing process. Futhermore, we are scheduled to develop the multi-point polishing process monitoring system through fabrication of the more AE sensors and complement of the monitoring system.

• Smart Structures and Systems
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• v.6 no.3
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• pp.197-209
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• 2010

The structural state of a bridge is currently examined by visual inspection or by wired sensor techniques, which are relatively expensive, vulnerable to inclement conditions, and time consuming to undertake. In contrast, wireless sensor networks are easy to deploy and flexible in application so that the network can adjust to the individual structure. Different sensing techniques have been used with such networks, but the acoustic emission technique has rarely been utilized. With the use of acoustic emission (AE) techniques it is possible to detect internal structural damage, from cracks propagating during the routine use of a structure, e.g. breakage of prestressing wires. To date, AE data analysis techniques are not appropriate for the requirements of a wireless network due to the very exact time synchronization needed between multiple sensors, and power consumption issues. To unleash the power of the acoustic emission technique on large, extended structures, recording and local analysis techniques need better algorithms to handle and reduce the immense amount of data generated. Preliminary results from utilizing a new concept called Acoustic Emission Array Processing to locally reduce data to information are presented. Results show that the azimuthal location of a seismic source can be successfully identified, using an array of six to eight poor-quality AE sensors arranged in a circular array approximately 200 mm in diameter. AE beamforming only requires very fine time synchronization of the sensors within a single array, relative timing between sensors of $1{\mu}s$ can easily be performed by a single Mote servicing the array. The method concentrates the essence of six to eight extended waveforms into a single value to be sent through the wireless network, resulting in power savings by avoiding extended radio transmission.

• 한국초전도학회:학술대회논문집
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• v.16
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• pp.76-76
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• 2006

• Transactions of Materials Processing
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• v.29 no.1
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• pp.20-26
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• 2020

In the design of the metal forming processes, various types of ductile fracture criteria are used to predict crack initiation and to fabricate metallic products without any defects. However, the quantitative measurement method for determination of crack initiation is insufficient. It is very difficult to detect crack initiation in ductile metals with excellent deformability because no significant load drop is observed due to crack generation. In this study, the applicability of acoustic emission sensors, which are commonly used in facility diagnostics, to measure crack initiation during the metal forming process was analyzed. Cylindrical notch specimens were designed using the finite element method to induce a premature crack on the surface of pre heat-treated steel (ESW90) material. In addition, specimens with various notch angles and heights were prepared and compression tests were carried out. During the compression tests, acoustic emission signal on the dies and images of the surface of the notch specimen were recorded using an optical camera in real time. The experimental results revealed that the acoustic emission sensor can be used to detect crack initiation in ductile metals due to severe plastic deformation.

• Nuclear Engineering and Technology
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• v.36 no.6
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• pp.540-548
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• 2004

Check valve failure is one of the worst problems in nuclear power plants. Recently, many researches have been based on new technology using accelerometers and ultrasonic and magnetic flux detection have been carried out. Here, we have suggested a method that uses acoustic emission sensors for detecting the failures of check valves through measuring and analyzing backward leakage flow, a system that works without disassembling the check valve. For validating the suggested acoustic emission sensor methodology, we designed a hydraulic test loop with a check valve. We have assumed in this study that check valve failure is caused by disk wear or by the insertion of a foreign object. In addition, we have developed diagnostic algorithms by using a neural network model to identify the type and size of the failure in the check valve. Our results show that the proposed diagnostic algorithm with acoustic emission sensors is a good solution for identifying check valve failure without necessitating any disassembly work.

• Smart Structures and Systems
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• v.4 no.5
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• pp.565-582
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• 2008

This paper presents a feasibility study of flexible piezoelectric paint for use in wide-band low-profile surface-mount or embeddable ultrasonic sensor for in situ structural health monitoring. Piezoelectric paint is a piezoelectric composite with 0-3 connectivity. Because of its ease of application, piezoelectric paint can be readily fabricated into sensing element with complex pattern. This study examines the characteristics of piezoelectric paint in acoustic emission signal and ultrasonic guided wave sensing. A series of ultrasonic tests including pitch catch and pencil break tests were performed to validate the ultrasonic wave sensing capability of piezoelectric paint. The results of finite element simulation of ultrasonic wave propagation, and acoustic emission generated by a pencil lead break on an aluminum plate are also presented in this paper along with corresponding experimental data. Based on the preliminary experimental results, the piezoelectric paint appears to offer a promising sensing material for use in real-time monitoring of crack initiation and propagation in both metallic and composite structures.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.280-284
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• 2003

The field application of acoustic emission(AE) testing for brand-new metal pressure vessel were performed. We will introduce the test procedure for acoustic emission test such as instrument check distance between sensors, sensor location, whole system calibration, pressurization sequence, noise reduction and evaluation. The data of acoustic emission test contain many noise signal, these noise can be reduced by time filtering which based on the description of observation during AE test.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.5
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• pp.9-16
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• 2001

Turning experiments are conducted to investigate characteristics of acoustic emission due to wear of the coated tool. The AE signals are obtained with a sensor attached to tool holder side. 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. Moreover, tool wear can be detected successfully using the AE-RMS.