• Journal of the Korean Wood Science and Technology
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• v.50 no.4
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• pp.246-255
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• 2022

The need for non-destructive testing and evaluation of Korean traditional wooden buildings is increasing because of their widespread deterioration. Among all types of deterioration, termite damage in wooden columns is the most difficult to detect with the naked eye because it starts inside the wood, and the initial deterioration is small. X-ray computed tomography (CT) is the best technology to investigate the inner state of wood that has less damage, but applying it to wooden columns between walls is challenging. Therefore, the feasibility of tomosynthesis, which is a method to reconstruct a coronal section of a subject with a few X-ray projections from a limited angle of rotation, was studied as an alternative to CT. Pine (P. densiflora) with three artificial holes was prepared as a specimen to evaluate the quality of reconstructed tomosynthesis images according to the different number of projections. The quality of the tomosynthesis images in the in-focus plane was evaluated using the contrast-to-noise ratios, while a vertical resolution between the images was assessed by determining the artificial spread function. The quality of the tomosynthesis image in the in-focus plane increased as the number of projections increased and then remained constant as the number of projections reached 21 or over. In the case of vertical resolution, there was no significant difference when 21 projections or more were used to reconstruct the images. A distinct difference between coronal section images was found when the distance was more than 10 mm from one plane to another plane.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.208-213
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• 2021

There is a lack of studies comparing the internal quality of fruit with its external quality. However, issues of internal quality of fruit such as internal browning are important. We propose a method of classifying normal apples and internally browned apples using a near-infrared (NIR) non-destructive system. Specifically, we found the optimal wavelength and characteristics of the spectra for determining the internal browning of Fuji apples. The NIR spectra of apples were obtained in the wavelength range of 470-1150 nm. A group of normal apples and a group of internally browned apples were identified using principal component analysis (PCA), and a partial least squares regression (PLSR) analysis was performed to develop and evaluate the discriminant model. The PCA analysis revealed a clear difference between the normal and internally browned apples. From the PLSR, the correlation coefficient of the predictive model without pretreatment was determined to be 0.902 with an RMSE value of 0.157. The correlation coefficient of the predictive model with pretreatment was 0.906 with an RMSE value of 0.154. The results show that this model is suitable for classifying normal and internally browned apples and that it can be applied for the sorting and evaluation of agricultural products for internal and external defects.

• Agribusiness and Information Management
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• v.6 no.2
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• pp.32-39
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• 2014

The goal of this research was to develop a portable system that could be used to evaluate the quality of milk in real time at a raw milk production site. A real-time portable quality evaluation system for raw milk was developed to enable non-destructive quality evaluation of somatic cell count (SCC), fat, protein, lactose, and total solid (TS) in milk samples. A prediction model of SCC, fat, protein, lactose, and TS was constructed using partial least squares (PLS) and 200 milk samples were used to evaluate the prediction performance of the portable quality evaluation system and high performance spectroscopy. Through prediction model development and verification, it was found that the accuracy of high performance spectroscopy was 90% for SSC, 96% for fat, 96% for protein, 91% for lactose, and 97% for TS. In comparison, the accuracy of the portable quality evaluation system was relatively low, at 90% for SSC, 95% for fat, 92% for protein, 89% for lactose, 92% for TS. However, the measurement time for high performance spectroscopy was 10 minutes for 1 sample, while for the portable quality evaluation system it was 6 minutes. This means that the high performance spectroscopy system can measure 48 samples per day (8 hours), while the portable quality evaluation system can measure 80 (8 hours). Therefore, it was found that the portable quality evaluation system enables quick on-site quality evaluation of milk samples.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.334-343
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• 1996

Quality evaluation for food and agricultural products have always been one of the most elusive problems associated with the handling , processing and marketing in a food plant production. In order to detect physical foreign materials in food and agricultural products, non-destructive techniques have been developed for many years. Application of X-ray system to detect physical foreign materials in food and agricultural products could be considered to be a high potential method. Especially , it is impossible to detect internal physical foreign materials by visual inspections. In this study, it was tried to be applied for two different X-ray devices. Soft X-ray system with CdTe sensor and X-ray CT scanner were evaluated for advantage of the detection of non-meltallic foreign materials in food and agricultural products . Though the soft X-ray is not a high energy radiation, it is possible to detect small different density in a material. The CdTe sensor has a high resolution for t e soft X-ray energy region. The density characteristics of foods and foreign material were expressed region. The density characteristics of foods and foreign materials were expressed as a soft X-ray energy spectrum. The energy spectrum was analyzed by a personal computer with a multi-channel analyzer. X-ray CT scanner can provide visual image and analyze by three dimensional information inside food and agricultural products. The X-ray CT scanner using as a medical equipment was used to detect a foreign material. The density characteristics of food and foreign materials in food were tried to be detected by the threshold value on the basis of the CT numbers. The soft X-ray absorption characteristics for acrylin plates and distilled water were obtained and could be found the possibility of detecting a small physical foreign materials such as a plastic wrapping film , a stone and grasshopper in food and agricultural products.

• Korean Journal of Food Science and Technology
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• v.22 no.6
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• pp.675-680
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• 1990

A near-infrared reflectance spectroscopic(NIRS) method which has been recently developed for a non-destructive method for measuring ingredients in foods and agricultural products especially was evaluated for the determination of capsanthin, total sugar, capsaicin and moisture contents in Korean domestic red peppers. A multiple linear regression analysis with the data obtained by standard-laboratory methods(capsaicin by GC, capsanthin by Colorimetry, total sugar by HPLC and moisture by Vacuum drying method) and NIRS method was carried out to make a calibration. The accuracy of the NIRS method was found to be adequate when the standard-laboratory values for a set of sample that were not included in the calibration, were compared. It is concluded that the NIRS method is suitable for the determination of total sugar and capsanthin.

• Journal of Welding and Joining
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• v.32 no.5
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• pp.50-57
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• 2014

Friction Stir Welding (FSW) is a complex process with several mutually interdependent parameters. A slight difference from known settings may lead to imperfections in the stirred zone. These inhomogeneities affect on the mechanical properties of the FSWed joints. In order to prevent the failure of the welded joint it is necessary to detect the most critical defects non-destructive. Especially critical defects are wormhole and lack of penetration (LOP), because of the difficulty of detection. Online thermography is used process-accompanying for defect detecting. A thermographic camera with a fixed position relating to the welding tool measures the heating-up and the cool down of the welding process. Lap joints with sound weld seam surfaces are manufactured and monitored. Different methods of evaluation of heat distribution and intensity profiles are introduced. It can be demonstrated, that it is possible to detect wormhole and lack of penetration as well as surface defects by analyzing the welding and the cooling process of friction stir welding by passive online thermography measurement. Effects of these defects on mechanical properties are shown by tensile testing.

• Progress in Superconductivity and Cryogenics
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• v.10 no.3
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• pp.1-4
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• 2008

For the effective evaluation of superconducting properties of a coated conductor, with a long length, a non destructive characterization technique including a reel-to-reel (R2R) Hall measuring system have been developed. A non-contact R2R Hall sensor array system was particularly designed to measure the superconducting property of coated conductors. The superconducting properties of long length coated conductors were measured by using this device. It was demonstrated that this system was convenient to measure the intensity and distribution of the magnet field applied perpendicular to the surfaces of the coated conductors. Using this device, the defect and low critical current density(Jc) area of coated conductors could be detected in real-time measurement.

• Journal of The Korean Society of Grassland and Forage Science
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• v.24 no.1
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• pp.81-90
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• 2004

Farmers need timely information on the nutritional status of their animals and the nutritive value of pastures and supplementary feeds if they are to apply successfully this existing nutritional information. Near infrared reflectance(NIR) spectroscopy has been used over the last forty years to analyse accurately protein, fiber, and other organic components in animal foods. NIR spectroscopy is a rapid, non-destructive, and non-polluting technology. When properly calibrated, NIR spectroscopy is used successfully with both concentrate and forage feeds. NIR methods predict in vitro digestibility accurately and precisely, and can predict in vivo digestibility at least as well as conventional "wet chemistry" methods such as in vivo digestion or the pepsin-cellulase method, and much more rapidly. NIR technology has been applied to the routine monitoring (through analysis of feces samples) of the nutritional status of cattle and other grazing animals. This report reviews the use of near infrared reflectance(NIR) spectroscopy to monitor the nutritive value of animal feeds and the nutritional status of grazing animals.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.5
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• pp.497-519
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• 2003

Science and technology is an essential ingredient of the progress in modern society. Measurements enable action and actions enable results. Non-Destructive Evaluation (NDE) - the science and technology of measurements without affecting the Properties and performance of the test object is an interdisciplinary domain area of high significance far ensuring quality, productivity and safety thus enabling better qualify of lift to the inhabitants on this planet. The test object can be material, component, plant, earth, environment etc. Total qualify management, total productivity management, concurrent engineering and many other essential ingredients of success in plant engineering and manufacturing industry are dependent on NDE far success and good returns on investments.

• Computers and Concrete
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• v.21 no.4
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• pp.407-417
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• 2018

Concrete which is a composite material is one of the most important construction materials. Compressive strength is a commonly used parameter for the assessment of concrete quality. Accurate prediction of concrete compressive strength is an important issue. In this study, we utilized an experimental procedure for the assessment of concrete quality. Firstly, the concrete mix was prepared according to C 20 type concrete, and slump of fresh concrete was about 20 cm. After the placement of fresh concrete to formworks, compaction was achieved using a vibrating screed. After 28 day period, a total of 100 core samples having 75 mm diameter were extracted. On the core samples pulse velocity determination tests and compressive strength tests were performed. Besides, Windsor probe penetration tests and Schmidt hammer tests were also performed. After setting up the data set, twelve artificial intelligence (AI) models compared for predicting the concrete compressive strength. These models can be divided into three categories (i) Functions (i.e., Linear Regression, Simple Linear Regression, Multilayer Perceptron, Support Vector Regression), (ii) Lazy-Learning Algorithms (i.e., IBk Linear NN Search, KStar, Locally Weighted Learning) (iii) Tree-Based Learning Algorithms (i.e., Decision Stump, Model Trees Regression, Random Forest, Random Tree, Reduced Error Pruning Tree). Four evaluation processes, four validation implements (i.e., 10-fold cross validation, 5-fold cross validation, 10% split sample validation & 20% split sample validation) are used to examine the performance of predictive models. This study shows that machine learning regression techniques are promising tools for predicting compressive strength of concrete.