• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.4
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• pp.109-114
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• 2008

The fractal dimension aims to quantitatively define the irregular characteristics of the shape in nature. It can be useful in describing morphological characteristics of various wear particles. This paper was undertaken to diagnose failure condition for sliding members in lubrication using fractal dimension. The experiments were undertaken to analyze the shape of wear particles and to diagnose failure condition for sliding members in lubrication using the image processing and the fractal parameters. It was possible to diagnose wear mechanism, friction, and damage state of machines through analysis of shape characteristics for wear particle in driven condition using fractal parameters.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.79-87
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• 1999

The most part of the faculty drop a trouble and damage of machine equipment even if whatever cause they break out take place at local and trifling place and the factor dominating their trouble is due to wear debris occurred in the lubricated machine moving surface. This study has been car-ried out to identify morphology of wear debris on the lubricated machine moving system by means of computer image analysis. Namely the wear debris contained in lubricating oil extracted from movable machine equipment will be filtered through membrane filter(void diameter 0.45${\mu}m$) and will be analyzed with its data information such as 50% volume diameter aspect roundness and reflectivity. Morphological characteristic of wear debris is easily distinguished by four shape parameters it is necessary to divide small class of every 100 wear debris in total wear particles in order to distinguish morphological characteristic of wear debris more easily by computer image analysis. We are sure that operation condition diagnosis of the lubricated machine moving surfaces is possible by computer image analysis.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.4
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• pp.136-142
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• 2003

The morphological analysis of wear debris can provide early a failure diagnosis in lubricated moving system. It can be effective to analyze operating conditions of oil-lubricated tribological system with shape characteristics of wear debris in a lubricant. But, in order to predict and recognize an operating condition of lubricated machine, it is needed to analyze and to identify shape characteristics of wear debris. Therefore, If the morphological characteristics of wear debris are recognized by computer image analysis using the neural network algorithm, it is possible to recognize operating condition of hydraulic driving members. In this study, wear debris in the lubricating oil are extracted by membrane filter (0.45 ${\mu}{\textrm}{m}$), and the quantitative values of shape parameters of wear debris are calculated by the digital image processing. This shape parameters are studied and identified by the artificial neural network algorithm. The result of study could be applied to prediction and to recognition of the operating condition of hydraulic driving members in lubricated machine systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.646-649
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• 2002

It can be effect on diagnosis of hydraulic machining system to analyze working conditions with shape characteristics of wear debris in a lubricated machine. But, in order to predict and estimate working conditions, it is need to analyze the shape characteristics of wear debris and to identify. Therefor, if shape characteristics of wear debris is identified by computer image analysis and the neural network, it is possible to find the cause and effect of moving condition. In this study, wear debris in the lubricant oil are extracted by membrane filter, and the quantitative value of shape characteristics of wear debris we calculated by the digital image processing. This morphological informations are studied and identified by the artificial neural network. The purpose of this study is In apply morphological characteristics of wear debris to prediction and estimation of working condition in hydraulic driving systems.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.11a
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• pp.53-58
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• 2001

Fractal dimension is the method to measure the roughness and the irregularity of something that cannot be defined obviously by Euclidean dimension. And the analysis method of this dimension don't need perfect, accurate boundary and color like analysis lot diameter, perimeter, aspect or reflectivity of wear particles or surface. If we arranged the morphological characteristic of various wear particle by using the characteristic of fractal dimension, it might be very efficient to the diagnosis of driving condition. In order to describe morphology of various wear particle, the wear test was carried out under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are boundary fractal dimension and surface fractal dimension.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2004.11a
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• pp.312-315
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• 2004

A lubricated state of an automobile transmission can not be inspected directly with eyes. Thus, it needs to develop a more general method. Wear debris can be collected from the lubricants of operating transmission of an automobile and its morphology is directly related to the fiction condition of the interacting materials from which the wear particles originated in lubricated transmission. In this paper, to identify the friction condition for transmission gear by neural network, the wear test of ball-on-disk type and the analysis of friction state were carried out for carburized SCM420 and nitrocarburized NT100 under different experimental conditions. The four shape parameters($50\%$ volumetric diameter, aspect, roundness and reflectivity) of wear debris were calculated by the image processing system. They were used as input values to identify the moving condition of transmission gear by the neural network.

• Journal of KSNVE
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• v.4 no.3
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• pp.273-277
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• 1994

1990년 7월 이후 #2 베어링에서 발생한 오일 휩 현상을 감지하고서도 그 주원인을 일반적으로 흔히 발생하는 사항에서만 해결방안을 찾으려 노력한 결과 3년 반의 시간이 경과되었고, 뜻하지 않게도 저널 직경의 불균일에 의한 오일 휩 현상임 을 뒤늦게 알게 되었다. 철저한 점검의 필요성을 강조하지 않을 수 없다. 증기터빈 의 Overhaul 작업완료 후 Oil Flusning 절차가 있는데 이 Oil Flusning 방법에 문제 가 있다. 보통은 작업완료후 로터를 정지한 상태에서 베어링 앞에 Oil Strainer(Fine Mesh)를 설치하고 오일 펌프를 기동하여 Flushing을 하는데 이때 Strainer를 통과한 작은 이물질이 베어링내에 축적되었다가 터빈 기동시 이 이물질과 로터가 접촉되어 저널이 손상되게 된다. 인천화력3호기 #2 베어링의 오일 휩을 일으키게 한 저널의 편마모 현상도 이와같은 경우임에 틀림없다. 왜냐하면 '90, O/H시 #2 베어링 저널의 직경은 원통형이었기 때문이다. 따라서 Oil Flusning은 터빈 구조상 불가능한 경우 도 있겠지만 베어링 by-pass Oil Flushing 시스템으로 개조 운영되어야 저널 및 베어링 마멸현상을 제거할 수 있고 이로인한 오일 휩 현상도 예방할 수 있을 것으로 판단된다.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.228-233
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• 2002

In this work, a new non-photolithographic micro-fabrication technique is presented. The motivation of this work is to overcome the demerits of the most commonly used photolithographic techniques. The micro-fabrication technique presented in this work is a two-step process which consists of mechanical scribing followed by chemical etching. This method has many advantages over other micro-fabrication techniques since it is simple, cost-effective, rapid, and flexible. Also, the technique can be used to obtain a metal structure which has sub-micrometer width patterns. In this paper, the concept of this method and its application to microsystem technology are described.

• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.214-219
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• 1997

The mechanical seals, which are installed in rotating machines like pump and compressor, are generally used as sealing devices in the many fields of industries. The failure of mechanical seals such as leakage, crack, breakage, fast and severe wear, excessive torque, and squeaking results in big problems. To identify abnormal phenomena on mechanical seals and to propose the proper monitoring parameter for the failure of mechanical seals, sliding wear experiments were conducted. Acoustic emission, torque, and temperature were measured during experiments. Optical microstructure was observed for the wear processing after every 10 minute sliding at rotation speed of 1750 rpm and scanning electron microscopy was also observed. Except for the initial part of every experiment, the variation of acoustic emission was well coincided with torque variation during the experiments. This study concludes that acoustic emission and torque are proper monitoring parameters for the failure of mechanical seals. The intensity of acoustic emission signals is measured in root mean square voltage. Temperature of sealing face will be used as a parallel parameter for increasing the reliability of monitoring system.