• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.3
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• pp.15-21
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• 1996

This study is focused on the prediction of appropriate tool life by clarifying the correlation between progressive tool wear and AE(Acoustic Emission) signals, while cutting stainless steel by end mill on the machining center. The results of this study were that RMSAE tends to increase linearly along with the increase of the cutting speed, and it was more sensitive to depth of cut than to the variation of feed rate at the same cutting conditions, and RMSAE increases around 0.21mm flank wear hereby AE-HIT also increases. AE signals depend upon tool wear and fracture from the above results. Therefore, the AE signals can be utilized in order to monitor the tool condition.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.85-89
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• 1996

This paper was undertaken to analyze the morphology of wear debris for operating condition evaluatio of lubricated machine surfaces. The lubricating wear test was carried out under different experimental conditions using tile wear test device was made in our laboritory and wear testing spcimen of the pin on disk type was rubbed in paraffine series base oil, by varying specimen, applied load, sliding distance. The four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) to describe morphology of wear debris have been developed and are outlined in tile paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology in machine condition monitoring

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.133-140
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• 1998

The neural network was applied to identify wear debris generated from the lubricated machine surface. The wear test was carried out under different experimental conditions. In order to describe characteristics of debris of various shapes and sizes, the four shape 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 characteristics and recognized the friction condition and materials very well by neural network.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1996.04b
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• pp.60-67
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• 1996

This paper was undertaken to analyze the morphology of wear debris on operating condition of lubricated machine surfaces. The lubricating wear test was carried out under different experimental conditions using the wear test device was made in our laboritory and wear testing spcimen of the pin on disk type was rubbed in paraffine series base oil, by varying specimen, applied load, sliding distance. The four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) to describe morphology of wear debris have been developed and are outlined in the paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology for machine condition monitoring.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.143-149
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• 1997

This paper was undertaken to do image analysis of wear debris on operating condition of the lubricated moving surfaces. This lubricating wear test was performed under different experimental conditions using the wear test device was made in our laboratory and wear testing specimen of the pin on dist type was rubbed in paraffine series base oil, by materials, varying applied load, sliding distance. The four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) to describe wear debris have been developed and are outlined in the paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology for machine condition monitoring, this to overcome many of the difficulties with current methods and facilitating wider use of wear particle analysis in machine condition monitouing.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.9
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• pp.983-989
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• 2011

A numerical algorithm for predicting fretting wear was developed using the boundary element method (BEM). A contact analysis was performed numerically using the relation between the elastic displacement and uniformly distributed loading of a rectangular patch on a semi-infinite solid. Geometrical updating based on nodal wear depths was performed. The wear depths were computed using the Archard's equation for sliding wear. In order to investigate the efficiency of BEM for predicting fretting wear, a problem involving a two-dimensional cylinder on a flat contact was analyzed, comparing it with the simulation model proposed by McColl et al. that was based on the finite element method. The developed method was then applied to the analysis of a spherical contact and it was shown that the developed simulation technique could efficiently predict fretting wear. Moreover, the effect of a step cycle on the solution obtained by the developed method was investigated.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 2000.06a
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• pp.31-36
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• 2000

평면연삭은 기계부품의 후가공 공정에 사용되며, 기계부품의 다듬질면은 내마멸성, 피로강도 및 내식성등 품질에 큰 영향을 미친다. 연삭작업중 가장 큰 위험 요소는 고속작업중 연삭숫돌의 파손이다. 연삭숫돌의 파괴되는 주요 원인은 고속 회전중 최고사용 원주속도를 넘어 지나치게 빠를 때 원심력이 결합력보다 커지는 경우와, 숫돌에 균열(crack)이 있을 때이다. 연삭숫돌이 파괴되어 숫돌 파편이 작업자의 머리, 안면등을 강타하여 사망이나 골절등 중대재해가 발생된다. (중략)

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.130-134
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• 1996

The characteristics of AE(Acoustic Emission) signal is related to cutting conditio, tool material, and tool geometry in metal cutting. The relation between AE signal and tool life was investigated experimentally. Experiment is carried out by gear shaping and SCM 420 workpiece. AE RMS voltage were increased according totool wear. It is suggested that maximum value of AE RMS voltage is an effective parameter to monitor tool life.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.140-140
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• 2004

마이크로 기술을 대변하는 Micro-Electro-Mechanical-Systems (MEMS)와 반도체, 각종 micro-sensor 및 actuator 등은 실리콘 위에 박막 코팅한 재료를 주로 사용하고 있다. 따라서 1 Um 이하의 박막코팅에 의해 원하는 성능을 얻으려는 시도가 널리 진행되고 있다 Hard Disk Drive (HDD)의 Head-Disk Interface (HDI)와 MEMS 접촉면에서는 발생하는 마찰 및 마멸에 대한 문제 등은 중요한 고려대상이다. 특히 코팅 층의 표면 파손 현상은 코팅 층의 파손 특성과 코팅 층과 기판 사이의 결합상태가 큰 영향을 미친다.(중략)