• 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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• 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.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.51 no.6
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• pp.246-252
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• 2002

This paper describes the acoustic emission measurement method to diagnose GIS for particles. We measured and analyzed the signals of acoustic waves using acoustic two types sensors with 125KHz and 50KHz resonant frequency respectively when the particles were dropped on the surfaces of circular plates and inside of GlS tanks. We found that the difference between peak outputs of two sensors depended on the types and materials of particles and the conditions of dropping position. These results showed that the outputs of 125KHz sensor were higher than those of 50KHz sensor in circular plate and 362㎸ GIS tank made of steel and vice versa in circular plate and 800㎸ GIS tank made of aluminum. The ratios outputs of 125KHz sensor to those of 50KHz sensor were 1.4 - 2.37 in 800㎸ GIS tank and were 0.5 - 1.0 in 362㎸ GIS tank. Therefore we knew that adaption of two types acoustic sensors which had different resonant frequencies as a very useful method in diagnosis of GIS.

• 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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.6
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• pp.429-436
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• 2014

Most mechanical systems are now operating consistently and getting faster due to the development of automation systems. Peoples' dependence on machines have increased as when problems occur within the mechanical system, personal injury and production loss may come as a result, as most of the mechanical system's malfunctions are caused by the failure of the rotational bearing. What we need now is a maintenance system that can warn us when it detects abnormal conditions before significant damage occurs to the bearing. In this study, we have developed an acoustic emissions sensor that can figure if the bearing works under the normal condition. With this acoustic emissions sensor, we can inspect the bearing for defects by using the Heterodyne technique, which converts the ultrasound signal into audio, as a signal conditioning process.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.1
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• pp.1-5
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• 2010

Acoustic emission(AE) has emerged as a powerful nondestructive tool to detect or monitor preexisting defects and leaks in the vessel structures. A Bragg grating based acoustic emission sensor system is developed. Various type of fiber Bragg grating sensor including the variable length of sensing part was fabricated and prototype sensor system was tested by using PZT pulser and pencil lead break sources. Two types of sensor attachment were used. First, the fiber Bragg grating sensor was attached fully to the surface using bonding agent. Second one is that one part of fiber was attached to the surface partly by bonding and the other part of fiber will be act as a cantilever. That is, the resonant frequency of the fiber Bragg grating sensor will depend on the length of sensing part. The final goal of the sensor system is to provide on-line monitoring of cracks or leaks in reactor vessel head penetration of nuclear power plants.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.3
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• pp.130-143
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• 1995

This paper presents a new methodology for on-line tool breadage detection by sensor fusion of an acoustic emission (AE) sensor and a built-in force sensor. A built-in piezoelectric force sensor, instead of a tool dynamometer, was used to measure the cutting force without altering the machine tool dynamics. The sensor was inserted in the tool turret housing of an NC lathe. FEM analysis was carried out to locate the most sensitive position for the sensor. A burst of AE signal was used as a triggering signal to inspect the cutting force. A sighificant drop of cutting force was utilized to detect tool breakage. The algorithm was implemented on a DSP board for in-process tool breakage detection. Experiental works showed an excellent monitoring capability of the proposed tool breakage detection system.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.6 s.171
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• pp.109-117
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• 2005

In case of fine machining processes, the cutting state monitoring by a skilled operator is impossible because the physical changes generated during fine machining are very weak. To realize the high efficient and precise fine machining, it is necessary to develop the sensor based monitoring system which is able to detect the fine changes of cutting state. In this paper, the fine acoustic emission monitoring system is developed to monitor the state of the fine machining process. The developed system consists of the AE sensor and the AE signal processing unit. And this has the high-sensitivity and bandwidth which can detect fine AE signal generated during fine machining process. In order to investigate the feasibility of the developed system, evaluation experiments were performed in the fine fixed-abrasive machining processes such as polishing and glass ferrule slicing. Experimental results show that the developed monitoring system possesses an excellent real-time monitoring capability at fine machining processes.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.49-51
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• 2004

This paper presents a realization of fault detection algorithm and Fieldbus based communication for condition monitoring of check valve. We first acquired the AE(Acoustic Emission) sensor data at the KAERI check valve test loop, extract fault features through the learned Neural network, and send the processed data to a remote site. The overall system has been implemented and experimental results are given to show its effectiveness.