• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.6 s.58
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• pp.115-125
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• 2009

In these days, carbon fiber-reinforced polymers (CFRP) have been widely used for retrofitting and/or strengthening structural elements. However, there are not enough test data to predict the long-term performance of the retrofitted structures exposed to freeze-thawing cycles. This paper presents the results of experimental program undertaken to investigate the effects of freeze-thawing cycling (from-18 to $4^{\circ}C) on the behavior and failure characteristics of reinforced concrete (RC) beams strengthened in shear with CFRP sheet and plate using acoustic emission (AE) technique.

• Journal of the Korean Society for Nondestructive Testing
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• v.14 no.2
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• pp.122-131
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• 1994

Journal bearings in the rotating machineries are vulnerable to the contamination or the insufficient supply of lubricating oil, which is likely to be the cause of unexpected shutdown or malfunction of these systems. Various destructive and nondestructive testing methods had been used for the reduction of maintenance cost and the operational safety problems due to the accidents related to bearing damages. In this experimental approach, acoustic emission monitoring is employed to the detection of incipient failure caused by intervention of foreign particles most probable in the journal bearing systems. Experimental schedules for the intervention of foreign particles was composed to be more quantitative and systematic than last study in consideration of minimum oil film thickness and particle size. The experiment was conducted under such designed conditions as inserting alumina particles to the lubrication layer in the simulated journal bearing system. Several parameters such as AE rms level, waveform, AE energy distribution and other AE event parameters are used for analysis and characterization of damage source. The results showed that the history of damage was well correlated with the changes of AE rms level and the type of damage source signal can be verified using other informations such as waveform, distributions of AE parameters etc.

• Journal of the Korean Society for Nondestructive Testing
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• v.15 no.4
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• pp.520-530
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• 1996

In this study, the artificial defects in rotary compressor are classified using pattern recognition of acoustic emission signal. For this purpose the computer program is developed. The neural network classifier is compared with the statistical classifier such as the linear discriminant function classifier and empirical Bayesian classifier. It is concluded that the former is better. It is possible to acquire the recognition rate of above 99% by neural network classifier.

• 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.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.124-129
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• 1997

The experimental investigation is mainly focused to detect tool wear by cutting signal measurements in multi-insert face milling SS 41 and STS 304. This research have investigated the effects on the insert number, which has relationship with mean-cutting force. AE(acoustic emission) signal, tool life and surface roughness in machining SS41 and STS 304. The cutting force and AE signal are monitored to analyse the cutting process, The surface roughness of the specimens machined by TiN coated tool with the various insert numbers measured at various cutting speeds, feed rates and depths of cut, The width of flank wear is also observed.

• Tunnel and Underground Space
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• v.10 no.2
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• pp.227-236
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• 2000

The fracture toughness can be measured by the two testing methods using chevron-notched specimen according to the ISRM Working Group of Commission of Testing Methods. They are chevron bend (CB) test and short rod (SR) test. In this study, the suggested methods (Level I tests) were conducted on the CB and SR specimens of Chuncheon granite. In addition. the J-integral analysis was combined with an acoustic emission technique to determine the fracture toughness. The results from two telling methods were analyzed in terms of the anisotropy and the acoustic emission characteristics.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.240-246
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• 2000

An in-process estimation of the ground surface roughness is a bottle-neck and an essential field in conventional grinding operation. We defined the dimensionless average roughness factor (D.A.R.F) that exhibits a roughness characteristics of ground surface. The D.A.R.F was composed easily of the absolute average and the standard deviation values which were the analytic parameters of the acoustic emission (AE) signal generated during the machining process. The theoretical equation between the surface roughness and the D.A.R.F has been derived from the linear regressive analysis and verified its availability through the experimentation on the surface grinding machine.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.1
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• pp.31-36
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• 2009

Micro-machining technology has been adopted for shape accuracy of micrometer and sub-micrometer scale, surface roughness of tens nanometer in industries. In micro-machining process the quality of machined surface is derived from machining condition and tooling. This paper investigates AE(acoustic emission) and cutting force signals according to machined surface quality related to machining condition. Machined surface quality was analyzed by the AE and cutting force parameter which reflect surface morphology. The characteristics of signal were extracted for process optimization by monitoring both the tool condition and the machined surface texture in micro end milling process.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.466-471
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• 2003

In order to analyze linear motor driven feed system, preliminary studies have been conducted focusing on the performance evaluation of the system based on the various combination of control gain along with acceleration. Tentative simulation revealed that due to the complexity of control system reduced number of control condition is recommended. Actual machining process with conventional feed system using endmill tool was employed as a preliminary study. Several sensing methods including AE, acceleration sensors and tool dynamometer were used. Results revealed the consistency in AE and cutting resistance. There were inconsistent empirical results in accelerometer probably due to the insensitivity of the sensor signal with respect to the experimental system

• 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.