• Proceedings of the KSME Conference
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• 2004.04a
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• pp.25-30
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• 2004

In this paper, the compensation of interfacial scatter due to adhesive layer and adherend thickness ratio variation was applied to improve measuring precision by calculating ultrasonic attenuation coefficient in the Al/Epoxy dissimilar bonded components. The optimum condition of theoretical value and experimental measuring accuracy by the ultrasonic method in the Al/Epoxy dissimilar bonded components have been investigated. From the experimental results, we proposed a measurement method of the interfacial crack lengths by the ultrasonic attenuation coefficient and discussed it.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.2
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• pp.67-75
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• 2006

In this paper, the compensation of ultrasonic scattering on interface crack depending on thickness variations of A1/Epoxy bonded dissimilar components was applied to improve measuring accuracy by using ultrasonic attenuation coefficient. The optimum conditions of theoretical value and experimental measuring accuracy by the ultrasonic method in A1/Epoxy bonded dissimilar components have been investigated. From the experimental results, the measurement method of interfacial crack lengths by using ultrasonic attenuation coefficient was proposed and discussed. After the ultrasonic scattering compensation depending on thickness variations of bonded dissimilar components was carried out, the measuring accuracy of interfacial crack length was improved by 5%.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1121-1137
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• 2015

This study presents probabilistic-based damage identification technique for highlighting damage in metallic structures. This technique utilizes distributed piezoelectric transducers to generate and monitor the ultrasonic Lamb wave with narrowband frequency. Diagnostic signals were used to define the scatter signals of different paths. The energy of scatter signals till different times were calculated by taking root mean square of the scatter signals. For each pair of parallel paths an error function based on the energy of scatter signals is introduced. The resultant error function then is used to estimate the probability of the presence of damage in the monitoring area. The presented method with an autofocusing feature is applied to aluminum plates for method verification. The results identified using both simulation and experimental Lamb wave signals at different central frequencies agreed well with the actual situations, demonstrating the potential of the presented algorithm for identification of damage in metallic structures. An obvious merit of the presented technique is that in addition to damages located inside the region between transducers; those who are outside this region can also be monitored without any interpretation of signals. This novelty qualifies this method for online structural health monitoring.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.421-431
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• 2009

This paper is the study on the verification of structural health monitoring (SHM) algorithm based on the ultrasonic guided wave. An active inspection system using Lamb wave (LW) for SHM was considered. The basic study about the application of this algorithm was performed for detecting the circular notch defect in steel plate. LW testing technique, pitch-catch method, was used for interpretation of circular notch defect with depth of 50% of plate thickness and 7 mm width. Damage characterization takes place by comparing $S_0$ mode sensor signals collected before and after the damage event. By subtracting the signals of both conditions from each other, a scatter signal is produced which can be used for damage localization. The continuous Gabor wavelet transform is used to attain the time between the arrivals of the scatter and sensor signals. A new practical damage monitoring algorithm, based on damage monitoring polygon and pitch-catch method, has been proposed and verified with good accuracy. The possible damage location can be estimated by the average on calculated location points and the damage extent by the standard deviation.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.103-111
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• 2002

In this study, the natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.304-309
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• 2003

In this study, natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. Feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.6
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• pp.62-70
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• 2007

In this study, the natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. Feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.11
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• pp.1011-1020
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• 2017

This study was conducted to investigate the material properties of stainless steel 316L specimens of untreated and UNSM treated material, hydrogen attacked material(100 bar, $300^{\circ}C$ at 120 h) and UNSM treated hydrogen attacked material at room temperature. Results demonstrated that the hydrogen attacked materials showed a tendency toward a slightly decreased fatigue strength, while the hydrogen embrittlement effect was smaller than the S-N curve of conventional untreated material. As compared to untreated material, the fatigue limit of the UNSM treated material increased by 43.8%, while it was 57.1％ higher in the UNSM treated hydrogen attacked material than in untreated hydrogen attacked material. The plastic deformation layer was ${\sim}152{\mu}m$ thick, as confirmed by maps showing the level of local plastic deformation affected by the UNSM treatment in three ways: an image quality map, inverse pole figure map, and kernel average misorientation map captured via electron back scatter diffraction. Owing to hydrogen embrittlement, about 90％ of surface cracks were smaller than the average grain size of $35{\mu}m$.