• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.4
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• pp.361-368
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• 2002

The aim of this study was to investigate the effect of preprocessing the transmitted energy spectrum data on development of a robust model to predict the sugar content in intact apples. The spectrum data were measured from 120 Fuji apple samples conveying at the speed of 2 apples per second. Computer algorithms of preprocessing methods such as MSC, SNV, first derivative, OSC and their combinations were developed and applied to the raw spectrum data set. The results indicated that correlation coefficients between the transmitted energy values at each wavelength and sugar contents of apples were significantly improved by the preprocessing of MSC and SNV in particular as compared with those of no-preprocessing. SEPs of the prediction models showed great difference depending on the preprocessing method of the raw spectrum data, the largest of 1.265%brix and the smallest of 0.507% brix. Such a result means that an appropriate preprocessing method corresponding to the characteristics of the spectrum data set should be found or developed for minimizing the prediction errors. It was observed that MSC and SNV are closely related to prediction accuracy, OSC is to number of PLS factors and the first derivative resulted in decrease of the prediction accuracy. A robust calibration model could be d3eveloped by the combined preprocessing of MSC and OSC, which showed that SEP=0.507%brix, bias=0.0327 and R2=0.8823.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.2
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• pp.170-176
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• 2012

In the nuclear industry, wall thinning defect of straight pipe occur the enormous loss in life evaluation and safety evaluation. To use non-destructive technique, we measure deformation, vibration, defect evaluation. But, this techniques are a weak that is the measurement of the wide area is difficult and the time is caught long. In the secondary side of nuclear power plants mostly used steel pipe, artificiality wall thinning defect make in the side and different thickness make to the each other, wall thinning defect part of deformation measure by using shearography. In addition, optical measurement through deformation, vibration, defect evaluation evaluate pipe and thickness defects of pressure vessel is to evaluate quantitatively. By shearography interferometry to measure the pipe's internal wall thinning defect and the variation of pressure use the proposed technique, the quantitative defect is to evaluate the thickness of the surplus. The amount of deformation use thickness of surplus prediction of the actual thickness defect and approximately 7 percent error by ensure reliability. According to pressure the amount of deformation and the thickness of the surplus through DB construction, nuclear power plant pipe use wall thinning part soundness evaluation. In this study, pressure vessel of thickness defect measure proposed nuclear pipe of wall thinning defect prediction and integrity assessment technology development. As a basic research defected theory and experiment, pressure vessel of advanced stability and soundness and maintainability is expected to contribute foundation establishment.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.4
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• pp.283-289
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• 2014

This study was conducted to develop a non-destructive detection method for adulterated powder products using Raman spectroscopy and partial least squares regression(PLSR). Garlic and ginger powder, which are used as natural seasoning and in health supplement foods, were selected for this experiment. Samples were adulterated with corn starch in concentrations of 5-35%. PLSR models for adulterated garlic and ginger powders were developed and their performances evaluated using cross validation. The $R^2_c$ and SEC of an optimal PLSR model were 0.99 and 2.16 for the garlic powder samples, and 0.99 and 0.84 for the ginger samples, respectively. The variable importance in projection (VIP) score is a useful and simple tool for the evaluation of the importance of each variable in a PLSR model. After the VIP scores were taken pre-selection, the Raman spectrum data was reduced by one third. New PLSR models, based on a reduced number of wavelengths selected by the VIP scores technique, gave good predictions for the adulterated garlic and ginger powder samples.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.4
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• pp.360-366
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• 2011

The Elasto-magnetic sensor is applied to detect the local cross-sectional loss of steel cables in this study while it was originally developed for measuring the tensile force in the previous works. To verify the feasibility of the proposed damage detection technique, steel bars which have 4-different diameters were fabricated and the output voltage value was measured at each diameter by the E/M sensor. Optimal input voltage and working point are chosen so that the linearity and resolution of results can ensure through repeated experiments, and then the E/M sensor was measured the output voltage values at the damage points of steel bar specimen that was applied the 4 types of damage condition based on the selected optimal experimental condition. This proposed approach can be an effective tool for steel cable health monitoring.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.5
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• pp.426-431
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• 2007

When a high-energy ultrasound propagates through a solid body that contains a crack or a delamination, the two faces of the defect do not ordinarily vibrate in unison, and dissipative phenomena such as friction, rubbing and clapping between the faces will convert some of the vibrational energy to heat. By combining this heating effect with infrared imaging, one can detect a subsurface defect in material in real time. In this paper a realtime detection of the brazing defect of thin Inconel plates using the UIR (ultrasonic infrared imaging) technology is described. A low frequency (23 kHz) ultrasonic transducer was used to infuse the welded Inconel plates with a short pulse of sound for 280 ms. The ultrasonic source has a maximum power of 2 kW. The surface temperature of the area under inspection is imaged by an infrared camera that is coupled to a fast frame grabber in a computer. The hot spots, which are a small area around the bound between the two faces of the Inconel plates near the defective brazing point and heated up highly, are observed. And the weak thermal signal is observed at the defect position of brazed plate also. Using the image processing technology such as background subtraction average and image enhancement using histogram equalization, the position of defective brazing regions in the thin Inconel plates can be located certainly.

• Journal of the Korean Magnetics Society
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• v.26 no.4
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• pp.133-136
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• 2016

In this study, we have constructed a measuring system to investigate tensile stress of tendons, which is employed in bridges, by means of the magnetic non-destructive testing (NDT) method. For the twisted 7-strands tendon, we have used Wiedemann effect. An ac current was applied to the tendon and voltage induced from Search Coil on Tendon (SCT) under applying tensile stress was measured. The measuring system consists of tensile stress applying apparatus up to 2 GPa, and ac current supply to apply current to the tendon directly to magnetize the tendon. We have invested two kinds of tendon which were produced by different companies for testing with constructed measuring system. Voltage induced from SCT was decreased up to 1.5 GPa linearly and two kinds of tendon which were produced by different companies shows similar trends. Thus, Wiedemann effect was also applicable to measure tensile stress of tendon by means of magnetic NDT.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.5
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• pp.443-451
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• 2013

Acoustic emission(AE) has emerged as a powerful nondestructive tool to detect any further growth or expansion of preexisting defects or to characterize failure mechanisms. Recently, this kind of technique, that is an in-situ monitoring of inside damages of materials or structures, becomes increasingly popular for monitoring the integrity of large structures like a huge wind turbine blade. In this study, the activities of AE signals generated from external artificial sources was evaluated and located by new developed signal mapping source location method and this test is conducted by 750 kW full-scale blade. And a new source location method was applied to assess the damage in the wind turbine blade during step-by-step static load test. In this static loading test, we have used a full scale blade of 100 kW in capacity. The results show that the acoustic emission activities give a good agreement with the stress distribution and damage location in the blade. Finally, the applicability of the new source location method was confirmed by comparison of the result of source location and experimental damage location.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.4
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• pp.410-417
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• 2012

Currently domestic thermal and nuclear power plants are comprised of many type's condenser and steam generator tubes to produce the electricity of good quality. There are some methods to inspect these tubes in the event that several defects were discovered in these facilities. Among many non-destructive methods, we used guided wave to inspect the soundness of tubes, because this method is very fast to detect the defect and very simple to install the equipment and also, can inspect up to the long range at a fixed point. Also, this method has a drawback that does not detect a very small size defect. So, we made an effort to overcome this drawback through the experimentation and signal analysis according to the size and shape of the defect through the manufacture of various artificial cracks capable to generate within the small size tube in the study and we anticipate that these detect limits can be overcome along with the development of the signal processing and manufacturing technology of the sensor for the inspection.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.1
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• pp.31-37
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• 2014

The aim of this study was the non-destructive evaluation of bloody eggs using VIS/NIR spectroscopy. The bloody egg samples used to develop the sorting mode were produced by injecting chicken blood into the edges of egg yolks. Blood amounts of 0.1, 0.7, 0.04, and 0.01 mL were used for the bloody egg samples. The wavelength range for the VIS/NIR spectroscopy was 471 to 1154 nm, and the spectral resolution was 1.5nm. For the measurement system, the position of the light source was set to $30^{\circ}$, and the distance between the light source and samples was set to 100 mm. The minimum exposure time of the light source was set to 30 ms to ensure the fast sorting of bloody eggs and prevent heating damage of the egg samples. Partial least squares-discriminant analysis (PLS-DA) was used for the spectral data obtained from VIS/NIR spectroscopy. The classification accuracies of the sorting models developed with blood samples of 0.1, 0.07, 0.04, and 0.01 mL were 97.9%, 98.9%, 94.8%, and 86.45%, respectively. In this study, a novel nondestructive sorting technique was developed to detect bloody brown eggs using spectral data obtained from VIS/NIR spectroscopy.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.35-44
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• 2016

Seed viability is one of the most important parameters that is directly related with seed germination performance and seedling emergence. In this study, a hyperspectral imaging (HSI) system having a range of 1000-2500 nm was used to classify viable watermelon seeds from nonviable seeds. In order to obtain nonviable watermelon seeds, a total of 96 seeds were artificially aged by immersing the seeds in hot water ($25^{\circ}C$) for 15 days. Further, hyperspectral images for 192 seeds (96 normal and 96 aged) were acquired using the developed HSI system. A germination test was performed for all the 192 seeds in order to confirm their viability. Spectral data from the hyperspectral images of the seeds were extracted by selecting pixels from the region of interest. Each seed spectrum was averaged and preprocessed to develop a classification model of partial least square discriminant analysis (PLS-DA). The developed PLS-DA model showed a classification accuracy of 94.7% for the calibration set, and 84.2% for the validation set. The results demonstrate that the proposed technique can classify viable and nonviable watermelon seeds with a reasonable accuracy, and can be further converted into an online sorting system for rapid and nondestructive classification of watermelon seeds with regard to viability.