• Tribology and Lubricants
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• v.17 no.1
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• pp.16-21
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• 2001

The wear particles is released from the moving surfaces in gear systems of transmission and its morphology is directly related to the damage and failure to gear system from which the particles originated. It is the effective method for damage condition estimation of automobile transmission gear to observe wear debris in gear oil. We tested with new transmission and took out gear oil according to driving distance. To be applied to damage condition of gear system in transmission of automobile,4 shape parameters of wear particles in gear oil were calculated and wear volume were presumed with the image processing system.

• KSTLE International Journal
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• v.3 no.1
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• pp.54-59
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• 2002

It can be effective on failure diagnosis of oil-lubricated tribological system to analyze operating conditions with morphological characteristics of wear debris in a lubricated machine. And it can be recognized that results are processed threshold images of wear debris. But it is needed to analyse and identify a morphology of wear debris in order to predict and estimate a operating condition of the lubricated machine. If the morphological characteristics of wear debris are identified by the computer image analysis and the neural network, it is possible to recognize the friction condition. In this study, wear debris in the lubricating oil are extracted from membrane filter (0.45 ${\mu}m$) and the quantitative value fur shape parameters of wear debris was calculated through the computer image processing. Four shape parameters were investigated and friction condition was recognized very well by the neural network.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.5
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• pp.92-97
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• 1998

The morpholgies of the wear particles are directly indicative of wear processes occuring in machinery and their severity. The neural network was applied to identify wear debris generated from the machine driving system. The four parameters(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 parameters learned. The three kinds of the wear debris had a different patter characteristic and recognized the friction condition and materials very well by artificial neural network. We discussed how the network determines differencee in wear debris feature, and this approach can be applied to foreseeability and decisio for moving condition of the Machine driving system.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.455-456
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• 2002

Wear is one of the main factors causing breakdown and fault of machine, so ferrography technique analyzing wear particles can be an effective way for condition monitoring and fault diagnosis. On the base of the forward multilayer neural network, a nodes self-deleting neural network model is provided in this paper. This network can itself deletes the nodes to optimize its construction. On the basis of the nodes self-deleting neural network, an intelligent ferrography diagnosis expert system (IFDES) for wear particles recognition and wear diagnosis is described. This intelligent expert system can automatically slim lip knowledge by learning from samples and realize basically the entirely automatic processing from wear particles recognition to wear diagnosis.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.245-246
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• 2002

The objective of this study is to evaluate corrosive wear resistance of metals used for bearings and gears in seawater. Sliding wear test of ferrous and copper materials against $Al_2O_3$ were carried out in artificial seawater using an electrochemical potentiostat. As the results, the wear rate and the coefficient of friction of the copper materials are lower than those of the ferrous materials. The corrosive wear of stainless steel is remarkably affected by normal load and sliding speed in view of tribological characteristics including adhesion and corrosion products.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.9
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• pp.146-154
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• 1997

Ion implantation has been used successfully as a surface treatment technology to improve the wear. fatigue and corrosion resistances of materials. A modified surface layer by ion implantation is very thin(under 1 m), but it has different mechanical properties from the substrate. It has also different wear characteristics. Since wear is a dynamic phenomenon on interacting surfaces with relative motion, an effective method for investigtating the wear of a thin layer is the observation of wear process in microscopic detail using in-situ system. The change of wear properties produces the transition of wear mode. To know the microscopic wear mechanism of this thin layer, it is very important to clarify its microscopic wear mode. In this paper, using the SEM and AFM Rribosystems as in-situ system, the microscopic wear of Ti ion-implanted 1C-3Cr steel, a material for roller in the cold working process, was investigated in repeated sliding. The depth of wear groove and the speciffc wear amount were changed with transition of microscopic wear mode. The depth of wear groove with friction cycles in AFM tribosystem and specific wear amount of Ti ion-implanted 1C-3Cr steel were less about 2-3 times than those of non-implanted 1C-3Cr steel. The microscopic wear mechansim of Ti ion-implanted 1C-3Cr steel was also clarified. The microscopic wear property was quantitatively evaluated in terms of microscopic wear mode and specific wear amount.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.3
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• pp.100-107
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• 2011

To evaluate the wear characteristics of very thin ceramic coated layer, it is very important to investigate its wear process in great detail. An effective method for investigating the wear of a thin layer is the observation of wear process in microscopic detail, using in-situ system. In this study, based on the SEM Tribosystem as in-situ system, the microscopic wear mode of TiN coatings was investigated in repeated sliding. Consequently, four modes were revealed for TiN coatings: Ploughing, powder formation, flake formation and coating delimitation. Sc(Severity of contact) can clarify transition condition of those microscopic wear modes.

• Journal of Power System Engineering
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• v.6 no.4
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• pp.56-61
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• 2002

This study is to investigate the wear behaviors of thermally sprayed ceramic coating by a pin-on-disk wear testing machine. The test specimens were plasma sprayed TiO2 coating material on carbon steel substrate(S45C) with Ni-4.5%Al alloy bond coating. Wear characteristics, friction coefficient and wear rates, were conducted at the three kinds of loads and velosities. Wear environments were dry and lubrication friction. The friction coefficients of TiO2 coating specimen in dry friction were almost same according to increase the friction velocity. The wear rate increased when the friction force is high. In lubrication friction, the wear hardly occured and friction coefficient was about 0.1. The adhesiveness of TiO2 in lubrication friction is larger than that in dry one.

• Tribology and Lubricants
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• v.15 no.3
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• pp.265-271
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• 1999

Wherever there are rotating equipment and contact between surface, there is wear and the generation of wear particles. The particles contained in the lubricating oil carry detailed and important information about the condition monitoring of the machine. This information may be deduced from particle shape, composition, size distribution, and concentration. Therefore, This paper was undertaken to Ferrography system of wear debris generated from lubricated moving machine surface. The lubricating wear test was performed under different experimental conditions using the Falex wear test of Pin and V-Block type by Ti(C, N) coated. It was shown from the test results that wear particle concentration (WPC) and wear severity Index( $I_{S}$), size distribution in normal and abnormal wear have come out all the higher value by increases sliding friction time. Wear shape is observed on the Ferrogram it was discovered a thin leaf wear debris as well as ball and plate type wear particles. This kind of large wear shape have an important effect not only metals damage, but also seizure phenomenon.

• Journal of Power System Engineering
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• v.5 no.3
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• pp.73-79
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• 2001

The purpose of this investigation is experimentally to clarify the machinability and tool wear of STS 304 steel pipe material for piping. In order to determine the effects of cutting parameters and tool wear on thrust, torque, AE RMS, drilling is conducted on CNC milling machine. In this experiment, it is measured that thrust, torque, tool wear length, tool wear area and AE RMS during drilling using Hss tool. It has been found that a) During the drilling, the thrust and the torque of the STS 304 pipe are received more the effect of the feed than the spindle speed and the thrust increase with the increase of feed, b) The value of the AE RMS is been larger the effect of the cutting speed than the feed rate, and the value of the AE RMS increase with the increase of spindle speed, c) It has been found that the suitable feed in feed condition of 0.03, 0.05, 0.1, 0.15mm/rev is below 0.05mm/rev, d) The value of the AE RMS was shown a characteristic of the jump value during it was a sudden inrcrease of the tool wear. The increased character of the AE RMS value can be known an effective factor of the tool wear detection, and e) It can be quantitatively evaluated the condition of the tool according to calculate a area of the drill wear image which is obtained by a vision system.