• Journal of Biosystems Engineering
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• v.29 no.3
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• pp.261-266
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• 2004

This study was Performed to classify the acoustic emission(AE) signal due to surface cracking and moisture movement in the flat-sawn boards of oak(Quercus Variablilis) during drying using the principal component analysis(PCA) and artificial neural network(ANN). To reduce the multicollinearity among AE parameters such as peak amplitude, ring-down count event duration, ring-down count divided by event duration, energy, rise time, and peak amplitude divided by rise time and to extract the significant AE parameters, correlation analysis was performed. Over 96 of the variance of AE parameters could be accounted for by the first and second principal components. An ANN analysis was successfully used to classify the Af signals into two patterns. The ANN classifier based on PCA appeared to be a promising tool to classify the AE signals from wood drying.

• Korean Journal of Materials Research
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• v.21 no.11
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• pp.623-627
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• 2011

This is a study on the distribution of acoustic emission parameters during a burst test for a type-II CNG vehicle fuel tank. A resonant AE sensor with a central frequency of 150 kHz was attached to the composite materials in the center of the fuel tank. The pressure was increased from 30 to 100% of the expected burst pressure and was maintained for 10 minutes at each level. Damage at 70% of expected burst pressure occurred by various damage mechanisms including fiber breakage and delamination, while that of below 60% only occurred by matrix crack initiation and growth. The count, duration and rise time of the AE signal at 60% of the expected burst pressure are distributed below 500, 5000 ${\mu}s$ and 300 ${\mu}s$, respectively. Then, at above 70% they increased with pressure by superimposing of individual AE signal generated at a nearby place. These results confirmed that the analysis of the distribution of AE parameters is an effective tool for estimating damage of a CNG fuel tank.

• 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 $AE_{mode}$

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.365-368
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• 1995

Rotary Compressor has many AE(Acoustic Emission) sources according to condition of parts because it is operated with combination of various parts. In this study, analysis of AE raw signal generated form Rotary compressor which artificially-made parts inflicted abnormal condition was carried out. AE raw signals were acquired form high-speed A/D board, and many burst type signals were observed. By analyzing burst type signals which is caused form internal AE source,efficient AE parameters for monitoring and diagnosis were presented.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.80-90
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• 2001

The aim of this study is to develop the methodology which enables to identify the mechanical properties of element such as stress intensity factor by using the AE parameters. Considering the multivariate and nonlinear properties of AE parameters such as ringdown count, rise time, energy, event duration and peak amplitude from fatigue cracks of machine element the principal component regression(PCR) and artificial neural network(ANN) models for the estimation of stress intensity factor were developed and validated. The AE parameters were found to be very significant to estimate the stress intensity factor. Since the statistical values including correlation coefficients, standard mr of calibration, standard error of prediction and bias were stable, the PCR and ANN models for stress intensity factor were very robust. The performance of ANN model for unknown data of stress intensity factor was better than that of PCR model.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.240-247
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• 2023

In this paper, effective data management in industrial sites such as intelligent factories using time series data was studied. For effective management of time series data, variables considering the significance of the data were used, and hyper parameters calculated through LSTM AE were applied. We propose an optimized modeling considering the importance of each data section, and through this, outlier data of time series data can be efficiently processed. In the case of applying data significance and applying hyper parameters to which the research in this paper was applied, it was confirmed that the error rate was measured at 5.4%/4.8%/3.3%, and the significance of each data section and the significance of applying hyper parameters to optimize modeling were confirmed.

• Structural Monitoring and Maintenance
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• v.1 no.1
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• pp.111-130
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• 2014

The increased use of carbon fiber reinforced polymer (CFRP) in retrofitting reinforced concrete (RC) members has led to the need to develop non-destructive techniques that can monitor and characterize the unique damage mechanisms exhibited by such structural systems. This paper presented the damage characterization results of six CFRP retrofitted RC beam specimens tested in the laboratory and monitored using acoustic emission (AE). The focus of this study was to continuously monitor the change in AE parameters and analyze them both qualitatively and quantitatively, when brittle failure modes such as debonding occur in these beams. Although deterioration of structural integrity was traceable and can be quantified by monitoring the AE data, individual failure mode characteristics could not be identified due to the complexity of the system failure modes. In all, AE was an effective non-destructive monitoring tool that can trace the failure progression in RC beams retrofitted with CFRP. It would be advantageous to isolate signals originating from the CFRP and concrete, leading to a more clear understanding of the progression of the brittle damage mechanism involved in such a structural system. For practical applications, future studies should focus on spectral analysis of AE data from broadband sensors and automated pattern recognition tools to classify and better correlate AE parameters to failure modes observed.

• Journal of Power System Engineering
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• v.21 no.3
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• pp.102-107
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• 2017

A tungsten inert gas (TIG) welding method was used for the bonding of stainless steel. TIG welding using inert gas (He or Ar gas) is a method to prevent oxidation and nitriding of materials and to combine non-ferrous metals. This method has the advantage of obtaining a smooth weld surface. In this study, the welding characteristics of 304 stainless steel welded by TIG welding method were analyzed by using nondestructive technique. Ultrasonic and Acoustic Emission (AE) was applied to evaluate the micro-damage of TIG welded 304 stainless steel. The velocity and damping coefficient of ultrasonic wave showed a slight difference in HAZ, which is the welding part of stainless steel. The AE parameters of average frequency, rise time and event were analyzed for the dynamic behavior of stainless steel during loading. Optimal AE parameters for evaluating the degree of damage to the specimen have been derived. Fractograph and metal structures of 304 stainless steel using SEM and optical microscope were discussed.

• Journal of Power System Engineering
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• v.2 no.3
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• pp.49-54
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• 1998

This paper is investigated of hardness and adhesiveness of plasma sprayed coating steels by AE(Acoustic Emission) testing when loading a tensile. AE Parameters used are Event, Count, Energy and Amplitude. Test specimens are carbon steel(S45C) with sprayed coating layers of Ni-4.5wt.%Al(bond coating) and $TiO_2$(top coating), and carry out heat treatment at $800^{\circ}C\;and\;1000^{\circ}C$, respectively. The micro-hardness of the heat treatment specimen have been improved more than that of non-heat treatment. On the tensile test, the process and occurence of the exfoliation of the sprayed coating layer can be estimated by AE Characteristics of AE parameters, such as event, count, amplitude and energy, on the layer exfoliation are shown the similar aspects. The exfoliation of bond coating occure at about 20% of strain and top coating is about 5% of strain.

• Journal of Convergence Korean Medicine
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• v.6 no.1
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• pp.5-20
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• 2024

Objectives: This study was aimed to evaluate the hemodynamic feasibility using pulse parameters as a way to establish safe dose guidelines for Chunwangbosim-dan, and to provide a foundation for developing evidence-based guidelines for clinical use. Methods: Forty-one volunteers were recruited to participate in a study examining the changes in pulse wave characteristics following the ingestion of Chunwangbosim-dan, over a period of 2 weeks, and pulse wave measurements were taken before and after the administration. Pulse wave parameters were measured in this study using a 3-dimensional radial pulse tonometry device(DMP-Lifeplus). In addition, questionnaire, blood pressure, temperature, and body composition were also measured as secondary measures. Results: Fifteen minutes after administration of Chunwangbosim-dan, the non-adverse event group(non-AE) exhibited a statistically significant increase in several power and pressure-related parameters, including h1, h3, h4, h5, SA, PA and PW, while the adverse event group(AE) showed a trend of decreasing stroke volume and increasing Systemic Vascular Resistance Index(SVRI) and applied pressure. After 2 weeks of administration, non-adverse event group(non-AE) exhibited significant changes in standard deviation of pulse rate and HRV_LH ratio. Notably, there are significant differences between AE group and non-AE group in h4/h1, w/t, applied pressure, SV and pulse rate. Conclusion: These findings suggest that pulse parameters may be a useful way to establish safe dosing guidelines for Chunwangbosim-dan. Further research is needed to confirm these results and to develop evidence-based guidelines for clinical use.