• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.130-134
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• 1996

The characteristics of AE(Acoustic Emission) signal is related to cutting conditio, tool material, and tool geometry in metal cutting. The relation between AE signal and tool life was investigated experimentally. Experiment is carried out by gear shaping and SCM 420 workpiece. AE RMS voltage were increased according totool wear. It is suggested that maximum value of AE RMS voltage is an effective parameter to monitor tool life.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.3
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• pp.30-36
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• 2004

As fiber reinforced composite materials are widely used in aircraft, space structures and robot arms, the study on the non-destructive testing methods of the composite materials has become an important research area for improving their reliability and safety. In this paper, the AE signal analyzer with the resonance circuit to extract the specified frequency of the acoustic emission signal were designed and fabricated. The noise levels of the fabricated AE signal analyzer by the disturbance such as impact or mechanical vibration had a very small value comparable to those of the conventional AE signal analyzer. Also, the fabricated AE signal analyzer was proved to have about the same crack detection capabilities with the conventional AE signal analyzer under the static and dynamic tensile tests of the composite materials.

• Journal of Power System Engineering
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• v.11 no.3
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• pp.35-40
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• 2007

Leak would happen because of the damage of high temperature and high-pressure valve in nuclear power plant. condition based prevention maintenance is essential by using the suitable method based on local condition. Energy loss prevention can prevent from an accurate test, Local actually and ability. The methods of test for high energy fluid leak at present are analysis of ${\Delta}T$, AE(Acoustic Emission) analysis, and thermal image. The result for test of secondary system in nuclear power plant Unit reveals that the AE occurred clearly in leakage situation, but thermal image didn't occur. It is identified that leak is occurred when the orifice located front and back of valve operates. It shows that making a impatient judgment by using the single method if it is leakage is containing uncertainty. So we think that using the Multi-Measuring method is more sound judgment than single-measuring method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.46-53
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• 1997

This paper presents a method of detection localized defects on tapered roller bearing in main spindle of machine tool system. The feature vectors, i.e. statistical parameters, in time-domain analysis technique have been calculated to extract useful features from acoustic emission signals. These feature vectors are used as the input feature of an neural network to classify and detect bearing defects. As a results, the detection of bearing defect conditions could be sucessfully performed by using an neural network with statistical parameters of acoustic emission signals.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.39-45
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• 2000

This paper describes the fundamental investigations on the in-process monitoring techniques focused on Acoustic Emission(AE) based on analytical method. Experiments were conducted on a CNC lathe using conventional carbide insert tools under various cutting conditions. As the result of this study a suggestion is given about the multi-purpose use of AE-signals detected with a single sensor for the monitoring of tool wear, built-up edge and chatter vibration in turning process.

• Journal of Power System Engineering
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• v.13 no.4
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• pp.43-48
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• 2009

The purpose of this study is to show how to eliminate the noises and to obtain the data related with the relationship between AE signal characteristics and mechanical behaviors for the pressure vessel steel. Various kinds of noises are introduced into the AE data in the course of experiments. Accordingly, real AE data have to be obtained after tests. AE test was carried out under four point bending load. Among AE signals, counts and signal strength are used to find out the differences of AE characteristics between the basemetal and weldment. After tests, this paper shows the procedures of filtering the noises against basemetal of the pressure vessel steel to obtain the real data around crack tip. Relationships between plastic zone size and cumulative AE counts are shown also. AE signals were absent within an elastic region, regardless of the specimens. Most of AE signals are produced in the process of plastic deformation. The deformation and fracture modes of basemetal and weldment are quiet different.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.946-956
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• 2008

Acoustic emission(AE) is low-energy seismic event associated with a sudden inelastic deformation such as the sudden movement of existing fractures, the generation of new fractures or the propagation of fractures. These events rapidly increase before major failure and happen within a given rock volume and radiate detectable seismic waves. Rock slopes are usually large in scale and there are many discontinuities in rock mass. AE waves are strongly attenuated when they propagate through joints. Thus we should resolve the attenuation problem to monitor large volume. In this study, we developed waveguide which is composed of two different materials, cement mortar and stainless steel rod. And several laboratory tests on developed waveguide are performed to obtain generalized AE parameters to predict the failure stage in rock slope. Comparing field data with experimental data in laboratory tests, failure stage of rock slope can be evaluated. To verify and optimize the developed monitoring method, we are now carrying out the field application at a rock slope.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.327-332
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• 2004

Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. This sound propagation due to leak in water pipelines is not a non-dispersive wave any more because of the surrounding pipes and soil. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than loom.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.360-367
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• 2009

The acoustic emission(AE) behavior of reinforced concrete slab under flexural loading was investigated to assess the integrity. This study was aimed at identifying the characteristics of AE response associated with damage development. By applying cyclic loading in various load steps, it was able to differentiate each AE source such as distributed micro crack initiation, friction, flexural crack and localized diagonal tension crack. The secondary peak and the change of AE hit rate gave valuable criteria fur assessment. From the analysis of the felicity ratio, furthermore, it was shown that this values can be used for evaluating the degree of concrete damage. Based on the experimental results, this approach for practical AE application may provide a promising method for estimating the level of damage and distress in concrete structures.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.300-304
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• 1993

Chip formation control is an important problem in the automation of manufacturing process, since the continuous chip can cause catastrophic failures of the tooling and entangle the workpiece causing damage. However, it is impossible to predict chip form correctly due to the complex nature of cutting process. In order to detect the chip form for unmanned manufacturing, a new identification method is proposed. The feasibility of using acoustic emission signals from the sensing plate for identification of chip form is investigated. Experiments were conducted under the various cutting conditions. When the acoustic emission sensor is attached to the sensing plate, it turns out that the moving averaged AE signals correlated well with the collision of segmented chips with the plate. The sensitivity of moving averaged AE signals to chip congestions due to continuous chip formation is illustrated as well.