• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1060-1070
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• 1992

In this paper, characteristics of Acoustic Emission in Low Density Polyethylene were studied from tree initiation to breakdown under long-term inhomogeneous alternative electrical field. The voltage levels used were 9, 11 and 14[kV]. Especially, a newly developed automatic measuring system was used to measure time variations of AE average amplitude, AE pulse number, AE pulse distribution patterns due to polarities. The patterns wer specially the variated patterns, when tree propagated. Also, parameters for dielectric breakdown prediction, which were suggested by Okamoto, were calculated. The result was analysed by tree shapes and partial discharge activities in tree due to tree initiation and propagation.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.6
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• pp.616-621
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• 2003

There are various Non-Destructive Evaluation (NDE) techniques used for measurement of residual stresses in material, such as magnetic methods, X-ray diffraction, Ultrasonic velocity measurement etc. The capabilities, applications and limitations of these techniques for evaluation of cold work/plastic deformation were studied and compared. Mild steel plates were subjected to different degree of cold deformation and were analyzed by Magneto-mechanical Acoustic Emission (MAE), Barkhausen Noise (BN) and magnetic properties (hysteresis loop parameters analysis). Further, these specimens were analyzed by X-ray diffraction and ultrasonic velocity measurements. The microhardness measurement and microstructure studies of these cold worked plates were also carried out. The results of all these studies and comparison of different techniques are discussed in this paper.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.6
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• pp.64-71
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• 1998

This paper investigates the relationship between cutting conditions and Acoustic Emission(AE) signals; $AE_{avg}$, $AE_{rms}$, $AE_{mode}$$AE_{avg}$ and $AE_{rms}$ are increased as the increasing of cutting velocity and depth of cut respectively. The new parameters, derived from $AE_{avg}$ and $AE_{rms}$, which may be used for the in-process detection of tool wear is discussed. It is also known that $AE_{mode}$

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.8
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• pp.1910-1920
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• 1993

An experimental study to investigate the unconventional chip formation called triangulation of chip in cutting with a SPRT (self-propelled rotary tool) is performed using acoustic emission (AE) signal analysis. In doing that, a quantitative model of the AE RMS signal in triangulation with a SPRT is first developed. The predicted results from this model show good correlation between the AE RMS signal and the general characteristics of triangular chip formation. Then, effects of various process parameters such as cutting conditions (cutting speed, depth of cut, oblique angle and normal rake angle) and the work material properties on the chip formation in cutting with a SPRT are explored. Special attention is paid to the work material properties which are found to have significant effects on triangulation.

• Journal of Mechanical Science and Technology
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• v.14 no.7
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• pp.773-781
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• 2000

The focus of this study is the development of a credible fault detection system of the cylindrical plunge grinding process. The acoustic emission (AE) signals generated during machining were analyzed to determine the relationship between grinding-related faults and characteristics of changes in signals. Furthermore, a neural network, which has excellent ability in pattern classification, was applied to the diagnosis system. The neural network was optimized with a momentum coefficient, a learning rate, and a structure of the hidden layer in the iterative learning process. The success rates of fault detection were verified.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.3
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• pp.11-16
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• 2004

In this study, the characteristics of signals such as acoustic emission, vibration amplitude and noise level which are derived from the abnormal condition of compressor are investigated. The normal condition, vane stick sound and roller defect condition are chosen to analyze the signal in each cases. From the feature extraction of each signals, the dominant parameters of each signals which can identify the abnormal condition are suggested.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.115-119
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• 1996

An estimation of surface roughness value is a very important and difficult issue in grinding process. The definition of the D.A.R.F(Dimensionless Average Roughness Factor) has been made including the absolute average and tile standard deviation that are the parameters of the AE(Acoustic Emission) sign. The theoretical equation of the surface roughness applying the D.A.R.F has been derived from the regressive analysis and specified with respect to the availability through the experimental approach on the machine.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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• pp.90-98
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• 2005

A monitoring system is necessary to make the polishing process more reliable in order to ensure the high quality and performance of the final products. Generally, AE (Acoustic Emission) is known to be closely related to the material removal rate (MRR). As the surface becomes rougher, the MRR and AE increase. Therefore, the surface roughness can be indirectly estimated using the AE signal measured during the polishing. In this study, an AE sensor-based monitoring system was fabricated to detect the very small AE signal resulting from the friction between a tool and a workpiece during polishing. The performance of this monitoring system was estimated according to polishing conditions, the relation between the level of the AE RMS and the surface roughness during the polishing was investigated.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.245-248
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• 2006

The objective of this study is to take the first step in creating a user-friendly health monitoring system for recycled aggregate concrete structure using acoustic emission(AE). Each specimen was a cube, the edge of which was 150mm. For pull-out tests, a steel rebar, 13mm in diameter, was embedded in the center of each specimen and casting directions(i.e., vertical and horizontal) were considered in this paper. The AE parameters were analyzed for damage levels(i.e. internal cracking stage, pull-out stage) of all specimens. Results from this study show that event, duration versus amplitude of a signal, showed a clear difference for different loading stages depending upon the concrete casting directions.