• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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• pp.69-76
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• 1998

A precision wear tester is developed to measure the wear rate of a high friction and high pressurized cylinder. The tester consists of indentor system and optical measuring system. The indentor system has two diamond indentors so that they make indents on the inside of the cylinder by using compressed air system. The X-Y-$\theta$ stage of the measuring system can trace the positions of the indents and can measure the diameters of them. The variation of the diameter of each indent after test is converted into the wear rate.

• KSTLE International Journal
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• v.2 no.1
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• pp.65-70
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• 2001

The wear debris is fall off the moving surfaces in oil-lubricated systems and its morphology is directly related to the damage and failure to the interacting surfaces. The morphology of the wear particles are therefore directly indicative of wear processes occurring in tribological system. The computer image processing and artificial neural network was applied to shape study and identify wear debris generated from the lubricated moving system. In order to describe the characteristics of various wear particles, four representative parameter (50％ volumetric diameter, aspect, roundness and reflectivity) from computer image analysis for groups of randomly sampled wear particles, are used as inputs to the network and learned the friction condition of five values (material 3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameters learned. The three kinds of the wear debris had a different pattern characteristics and recognized the friction condition and materials very well by neural network. We discuss how these approach can be applied to condition diagnosis of the oil-lubricated tribological system.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.5
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• pp.98-107
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• 1995

The in-process detection of drill wear and breakage is one of the most importnat technical problems in unmaned machining system. In this paper, the monitoring system is developed to monitor abnormal drilling states such as drill breakage, drill wear and unstable cutting using motor current. Drill breakage is detected by level monitoring. Tool wear is classified by fuzzy pattern recognition. The key feature for classification of tool wear is the estimated flank wear which is calculated by the proposed flank wear model. The characteristic of the model is not sensitive to the variation of cutting conditions but is sensitive to drill wear state. Unstable cutting states due to the unsmooth chip disposal and the overload are monitored by the variance/mean ratio of spindle motor current. Variance/mean ratio also includes the information about the prediction of drill wear and drill breakage. The evaluation experiments have shown that the developed system works very well.

• Fashion & Textile Research Journal
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• v.6 no.5
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• pp.655-659
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• 2004

The purpose of this study is to investigate the somatotype variation & satisfaction with the fit of ready-to-wear for American women. For this study, questionnaires were administered to 192 American women in Louisiana State areas. Employing a sample of 127 data were analyzed by using F-test. The results were as follows: In the satisfaction with the somatotype variation of American women, height items were increased and width items were decreased with aging. At neck, bust, waist, hip and sleeve circumferences, in the satisfaction with the fit of ready-to-wear, were decreased with aging, Correlation for somatotype variation & satisfaction with the fit of ready-to-wear was significantly positive. With aging, the satisfaction with the somatotype & fit of American women's ready-to-wear for sizing system was generally decreased.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.1
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• pp.33-39
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• 2012

The tool wear and failure in automatic production system directly influences the quality and productivity of a product, thus it is essential to monitor the tool state in real time. For such purpose, an ART2-based remote monitoring system has been developed to predict the appropriate tool change time in accordance with the tool wear, and this study aims to experimently find the relationship between the tool wear and the monitoring signals in cutting processes. Also, the roughness of workpiece according to the wool wear is examined. Here, the tool wear is indirectly monitored by signals from a vibration senor attached to a machining center. and the wear dimension is measured by a microscope at the start, midways and the end of a cutting process. A series of experiments are carried out with various feedrates and spindle speeds, and the results show that the sensor signal properly represents the degree of wear of a tool being used, and the roughnesses measured has direct relation with the tool wear dimension. Thus, it is concluded that the monitoring signals from the vibration sensor can be used as a useful measure for the tool wear monitoring.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.5
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• pp.20-24
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• 1999

Grinding System is very difficult to examine closely wear phenomenon or dynamic characterastic because it is very complex and different from a general cutting system, Considering automatization and precision it is very important to examine closely grinding system. In this study grinding wheel surface is acquired by using computer vision system in order to explain wear and loading phenomenon. We investigate the relationship between wear and Fourier spectrum of acquired image and observe the entropy variation in the process of manufacturing.

• Journal of Power System Engineering
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• v.9 no.2
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• pp.57-64
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• 2005

This paper is the study on dry sliding wear behavior of carbon fiber reinforced epoxy matrix composites against lay-up orientation. Tests were investigated on the effect of the lay-up orientation, fiber sliding direction, load and sliding velocity when circumstance keep continuously at $21^{\circ}C$, 60%RH. Pin-on-disk dry sliding wear tests for each experimental condition were carried out with a carbon fiber reinforced plastic pin on stainless steel disk in order to search the friction and wear characteristics. The wear rates and friction coefficients against the stainless steel counterpart were experimentally determined and the wear mechanisms were microscopically observed. The effect on friction and wear behavior are observed differently, according to various conditions. When sliding took place against counterpart, the highest wear resistance and the lowest friction coefficient were observed in the $[0]_{24s}$ lay-up orientation at anti-parallel direction.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1999.06a
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• pp.272-278
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• 1999

It is the effective method to diagnosis damage process of gear system such as automobile transmission to observe wear particle in gear oil. We tested with new transmission and took out gear oil according to drive distance. 4 shape parameters of wear particles in gear oil were calculated and wear volume were presumed with the image processing system. To be applied to damage diagnosis of gear system in transmission of automobile, we discuss number of wear particles, shape characteristics and total wear volume according to driving distance.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1997.04a
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• pp.224-231
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• 1997

Microscopic examination for the morphological estimation of wear debris on the oil-lubrcated moving system is an accepted method for machine condition and fault diagnosis. However wear particle anaysis has not been widely accepted industry because it is dependent on expert interpretation of particle morphology and relies on subjective assessment criteria. This paper was undertaken to estimate the morphology of wear debris on the oil-lubricated movig system by computer image analysis. The wear test was performed under different sliding conditions using a wear test device made in our laboratory and wear testing specimen of the pin-on-disk-type was rubbed in pararline series base oil. In order to describe characteristics of debris of various shape and size, four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) have been developed and outlined in the paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology in machine condition monitoring.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1997.10a
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• pp.135-144
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• 1997

This wear debris can be harvested from the lubricants of operating machinery and its morphology is directly related to the damage to the interacting surfaces from which the particles originated. The morphologies of the wear particles are therefore directly indica- rive of wear processes occuring in machinery and their severity. The neural network was applied to identify wear debris generated from the lubricated moving system. The four parameter(50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction condition of five values(material 3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by neural network. We dicuss how the network determines difference in wear debris feature, and this approach can be applied to condition diagnosis of the lubricated moving system.