• Tribology and Lubricants
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• v.26 no.1
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• pp.52-55
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• 2010

This study investigates the friction of the roll stands in the high performance multi- holes slate fin machine which pin is using in heat transfer of radiator, oil cooler, inter cooler, condenser and evaporator. The roll stand part is very important to maintain the high performance fin machine. This multi-holes form roll type is the first time in our country so it will be helpful to increases the export and product of heat transfer. It was include the technical of form rolling system which was self development. Then it will be improve the electric home appliances, future motor vehicle device and industrial machine.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.5
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• pp.500-505
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• 2012

Recently, a high speed spindle is an essential part of machine tools to satisfy latest demand of high precision product and machining of hard materials. But, there are many disadvantages such as heat generation of built-in-motor, bearing friction, noise, vibration and displacement because of the high speed. Many researches on spindle systems have been conducted for solving these problems. In this study, technical trend of machine tools spindle systems are analyzed with patent PSM, mapping and grouping. The analysis is carried out for the applied patent during January 2000 and December 2009 in Korea, Japan, EU and U.S.A. And development of the direction, strategy and promising technologies of the spindle system are suggested.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.31 no.3
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• pp.317-322
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• 1998

Generally, the conventional fish size grading methods just adopt the mechanical technique. So the grading methods have a problem such that the graded fish is easy to hurt on the skin and in the internal organs. In this paper, a fish size grading machine is developed using an image processing method. The grading method is based on the principal axis theorem. The length and projected area of a fish are obtained by getting the principal axis and the product of inertia moment on the captured image of a target fish. The developed machine uses an uncontact technique that the target fishes go through the front side of the CCD camera. So the above stated problem can be improved. The performance of this method is discussed with the experimental results.

• Journal of Multimedia Information System
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• v.2 no.3
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• pp.255-262
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• 2015

The modern manufacturing systems and technologies produce products that are more accurate day by day. This can be reached mainly by improvement the manufacturing process with at the same time restricting more and more the quality specifications and reducing the uncertainty in part. The main objective an industry becomes to lower the part's variability, since the less variability - the better is product. One of the part of this task is measuring the object's uncertainty. The main purpose of this study is to understand the application of bootstrap method for uncertainty evaluation. Bootstrap method is a collection of sample re-use techniques designed to estimate standard errors and confidence intervals. In the case study a surface of an automobile engine block - (Top view side) is measured by Coordinate Measuring Machine (CMM) and analyzed for uncertainty using Geometric Least Squares in complex with bootstrap method. The designed experiment is composed by three similar measurements (the same features in unique reference system), but with different points (5, 10, 20) concentration at each level. Then each cloud of points was independently analyzed by means of non-linear Least Squares, after estimated results have been reported. A MatLAB software tool used to generate new samples using bootstrap function. The results of the designed experiment are summarized and show that the bootstrap method provides the possibility to evaluate the uncertainty without repeating the Coordinate Measuring Machine (CMM) measurements many times, i.e. potentially can reduce the measuring time.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.8
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• pp.110-116
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• 2020

Aircraft hydraulic oil reservoirs made with aluminum 7075 have an anodized coating to enable airtightness and corrosion resistance. To maintain a stable oil pressure, the internal surface roughness of the reservoir should be less than approximately 0.2 ㎛. To this end, precision polishing must be performed. However, ensuring the processing quality is challenging, as most polishing operations are performed manually, owing to which, the inner surface roughness is not uniform, and the product quality is irregular. Therefore, we developed a special superfinishing machine to realize the efficient inner polishing of an aircraft hydraulic oil reservoir, by using an abrasive film to improve the process throughput and uniformity. In the experiment involving the superfinishing of an anodized aluminum 7075 cylinder specimen by using the proposed machine, a higher surface roughness than that achieved in the repetitive manual polishing process could be realized.

• Journal of Power System Engineering
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• v.14 no.2
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• pp.34-39
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• 2010

Recently, technical trend for machine tools is focused on enhancement of speed and accuracy. High speedy processing causes thermal and structural deformation of objects from the machine tools. Water cooler has to be applied to machine tools to reduce the thermal negative influence with accurate temperature controlling system. Existing On-Off control type can't control temperature accurately because compressor is operated and stopped repeatedly and causes increment of power consumption and decrement of the expected life of compressor. The goal of this study is to minimize temperature error in steady state. In addition, control period of an electronic expansion valve were considered to increment of lifetime of the machine tools and quality of product with a water cooler. PI controller is designed using type of hot-gas bypass for precise control of temperature. Gain of PI is decided easily by method of critical oscillation response, excellent performance of control is shown with 4.24% overshoot and ${\pm}0.2^{\circ}C$error of steady state. Also, error range of temperature is controlled within $0.2^{\circ}C$although disturbance occurs.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.394-399
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• 2012

In recent years, MEMS sensors show huge attraction in machine condition monitoring, which have advantages in power, size, cost, mobility and flexibility. They can integrate with smart sensors and MEMS sensors are batch product. So the prices are cheap. And the suitability of it for condition monitoring is researched by experimental study. This paper presents a comparative study and performance test of classification of MEMS sensors in target machine fault classification by 3 intelligent classifiers. We attempt to signal validation of MEMS sensor accuracy and reliability and performance comparisons of classifiers are conducted. MEMS accelerometer and MEMS current sensors are employed for experiment test. In addition, a simple feature extraction and cross validation methods were applied to make sure MEMS sensors availabilities. The result of application is good for using fault classification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1558-1563
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• 2010

This paper describes a study on algorithm for the development of machine vision system as well as the inspection of automobile's plastic part locking lever to replace a human worker's eye inspection. Before developing the machine vision system based on the PC, the purpose of this research is to develop the algorithm to decide whether a product is a good/bad one in real time inspection. NI-LabVIEW software is used in the inspection method and an inspection program is developed using LabVIEW Vision image functions. The inspection program was built and validated to help the system operator set up the inspection area and change the criteria number in the program.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.3
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• pp.117-129
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• 2013

The increasing demand for monitoring wildfires and their impact on the land surface have prompted studies of burned area extraction and analysis. To differentiate burned and unburned area, the earlier method of the Moderate Resolution Imaging Spectro-radiometer (MODIS) Burned Area Detection Algorithm was proposed to estimate the change in land surface based on the reflectance energy. The energy, whose wavelengths are sensitive to burning, was selected to calculate the change parameter $Z_{score}$. This method was applied using the MODIS images to produce a MODIS Burned Area product. The approach was to simplify this algorithm to make it compatible with the Landsat 7 ETM+ SLC-off images. To extract the refined version of burned regions, post-processing was carried out by applying a median filter, dilation morphology algorithm, and finally a gap filling method. The experimental results showed that the detailed burned areas extracted from the proposed method exhibited more spatial details than those of the MODIS Burned products in the large U.S areas. The results also revealed the discontinuous distribution of burned regions in Vietnam forests.

• Structural Engineering and Mechanics
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• v.68 no.6
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• pp.691-700
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• 2018

Ground granulated blast furnace slag (GGBS) is a by product obtained from iron and steel industries, useful in the design and development of high quality cement paste/mortar and concrete. This paper investigates the applicability of relevance vector machine (RVM) based regression model to predict the compressive strength of various GGBS based concrete mixes. Compressive strength data for various GGBS based concrete mixes has been obtained by considering the effect of water binder ratio and steel fibres. RVM is a machine learning technique which employs Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM is an extension of support vector machine which couples probabilistic classification and regression. RVM is established based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Compressive strength model has been developed by using MATLAB software for training and prediction. About 70% of the data has been used for development of RVM model and 30% of the data is used for validation. The predicted compressive strength for GGBS based concrete mixes is found to be in very good agreement with those of the corresponding experimental observations.