• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.169-173
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• 1993

In this paper, the features extraction of reflected signals from various type of defects existing in the solid has been studied by Wiener filtering technique. In this experiment, three types of the defect have been considered; a flat cut, a angular cut and a circular hole. All of the defects have the same size, 20mm in diameter and have been located at 45mm in depth from the aluminum surface. In the result of the experiment, it has been found that the wiener filtering technique used for features extraction from the reflected signal corresponding to each defect have been very effective for defect classification.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.280-285
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• 2004

In this study, we made a comparative study of backpropagation neural network and probabilistic neural network and bayesian classifier and perceptron as shape recognition algorithm of welding flaws. For this purpose, variables are applied the same to four algorithms. Here, feature variable is composed of time domain signal itself and frequency domain signal itself. Through this process, we comfirmed advantages/disadvantages of four algorithms and identified application methods of four algorithms.

• 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.

• Proceedings of the KIEE Conference
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• 1999.07e
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• pp.2434-2437
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• 1999

In order to detect the ultrasonic that is generated by the partial discharge of the heavy electric machinery, a Laser Doppler Vibrometer (LDV) was developed. A Michelson type interferometer which employed heterodyne signal process technique was built to measure the frequency and amplitude of vibration. The output signal of the fast photodetector was a frequency modulated signal centered at 40 MHz. The signal from the detector was amplified and downconverted to intermediate frequency centered at 1 MHz after mixing process. The voltage output that was proportional to the velocity of the moving surface(PZT) was obtained using PLL. The spectrum of the FM signal was analyzed and integration method was introduced to obtain amplitude information. This LDV can be used to measure the vibration of MEMS devices, automobiles, HDD and CDP.

• 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 for Noise and Vibration Engineering
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• v.26 no.2
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• pp.148-156
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• 2016

The paper deals with improvement of a piezoelectric ultrasonic transducer for measuring both pipe thickness and flow velocity. The transducer structure is based on the conventional transducers for measuring flow velocity by obliquely transmitting ultrasonic waves to the flow direction. The transducer invented earlier for measuring flow velocity and pipe thickness had an advantage of including only one piezoelectric disc, but for the thickness measurement the ultrasonic wave had to be reflected twice in a wedge material to be transmitted vertically to a pipe, and thus the wave signal was too weak. The transducer has been improved to transmit waves for thickness measurement vertically to a pipe without any prior reflection by electrically connecting two piezoelectric discs, one for flow velocity and the other for pipe thickness measurement. By comparing the measured results of specimen thickness with the improved transducer and conventional transducers, the accuracies of the improved one have been evaluated in the pipe thickness measurements.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.5
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• pp.25-30
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• 2017

In this Paper, we Propose the Low-cost Obstacle Recognition System Utilizing the Ultrasonic Sensor. Developed Obstacle Recognition System can be used to Aid the Visually Impaired Person. The Existence of the Obstacle is Notified to the Person through the Embodied Electronic Vibration Motor. The Timing Difference from the Recognition to the Notification Indicates the Distance to the Obstacle. Pulsed Ultrasonic Signal Controlled by MCU is Utilized and the Reflected Pulse through the Obstacle gives the Developed System the Existence of the Obstacle and the Distance to the Object. Pulse is sent Repetitively to Improve the Detection Accuracy. Developed Apparatus gives 30 Degree of Detection Angle and 2cm-30cm of the Detection Range when the Apparatus is Tested under Normal Walking Environment.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.6 no.1
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• pp.29-36
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• 2010

Ultrasonic inspection of heavy walled cast austenitic stainless steel(CASS)welds is very difficult due to complex and coarse grained structure of CASS material. The large size of anisotropic grain strongly affects the propagation of ultrasound by severe attenuation, change in velocity, and scattering of ultrasonic energy. therefore, the signal patterns originated from flaws can be difficult to distinguish from scattered signals. To improve detection and sizing capability of ID connected defect for heavy walled CASS piping welds, the low frequency segmented TRL Pulse Echo and Phased Array probe has been developed. The experimental studies have been performed using CASS pipe mock-up block containing artificial reflectors(ID connected EDM notch). The automatic pulse echo and phase array technique is applied the detection and the length sizing of the ID connected artificial reflectors and the results for detection and sizing has been compared respectively. The goal of this study is to assess a newly developed ultrasonic probe to improve the detection ability and the sizing of the crack in coarse-grained CASS components.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.2116-2124
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• 2001

It's required mechanical properties of in-service facilities to maintain safety operation in power plants as well as chemical plants. In this studdy the four classes of the thermally aged 1Cr-lMo-0.25V specimens were prepared using an artificially accelerated aging method at 630$\^{C}$. Ultrasonic tests, tensile tests, K$\_$IC/ tests and hardness tests were performed in order to evaluate the degree of degradation of the material. The mechanical properties were decreased as degraded, but the attenuation coefficient and the harmonic generation level of a ultrasonic signal were increased. Expecially the nonlinear parameter derived from the harmonic generation level is sensitive and will be a good parameter to evaluate the material degradation.