• Tribology and Lubricants
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• v.23 no.6
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• pp.301-305
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• 2007

The wear particle analysis has been known as very effective method to foreknow and decide a moving situation and a damage of machine parts by using the digital computer image processing. But it was not laid down and trusted to calculate shape parameters of wear particle and wear volume. In order to apply image processing method in the foreknowledge and decision of lubricated condition, it needs to verify the reliability of the calculated data by the image processing and to lay down the number of images and the amount of wear particle in one image. In this study, the lubricated friction experiment was carried out in order to establish the optimum image capture with the SM45C specimen under experiment condition. The wear particle data were calculated differently according to the number of image and the amount of wear particle in one image.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.5
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• pp.53-58
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• 2003

Wear debris can be collected from the lubricants of operating machinery and its morphology is directly related to the fiction condition of the interacting materials from which the wear particles originated in lubricated machinery. But in order to predict and estimate working conditions, it is need to analyze the shape characteristics of wear debris and to identify. Therefore, if the shape characteristics of wear debris is identified by computer image analysis and the neural network, The four parameter (50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction. 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 characteristic and recognized the friction condition and materials very well by neural network. We resented how the neural network recognize wear debris on driving condition.

• 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.

• KSTLE International Journal
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• v.10 no.1_2
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• pp.27-32
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• 2009

In this study, fretting wear tests of nuclear fuel rods have been performed by using two kinds of spacer grid springs with a concave and a convex shape in room temperature dry and distilled water conditions. The objectives were to examine the variation of the wear mechanism with increasing fretting cycles and to evaluate the difference of the wear debris detachment behavior at each test environment. From the test results, the wear volume of each spring condition increased with increasing fretting cycles regardless of the test environments. However, the wear rate did not show a regular tendency and apparently changed with increasing fretting cycles. This is because the formation of the wear particle layer and/or the variation of the contact condition between the fuel rod and spring surfaces could affect a critical plastic deformation for detaching the wear debris. Based on the test results, the relationship between the wear behavior of each spring shape and test environment condition, and the variation of the surface characteristics are discussed in detail.

• KSTLE International Journal
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• v.3 no.1
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• pp.68-73
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• 2002

A fretting wear experiment in roam temperature air was performed to evaluate the wear mechanism of fuel rod using a fretting wear tester, which has been developed for experimental study, The main focus was to compare the wear behaviors of fuel rod against support springs with different contact contours (i.e. concave and convex). Wear volume, degree or surface hardening and adhesion tendency of wear particle were examined by the surface roughness tester. The result indicated that with a change of contact condition from contact force of 5 N to 0.1 mm gap, the wear volume of tube increased in the condition of concave spring, but slowly decreased in convex spring. From the results of SEM observation, wear mechanism of each test condition was also dependent on the spring shapes. The wear mechanism of each test condition in room temperature air is discussed.

• Journal of Power System Engineering
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• v.10 no.2
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• pp.111-116
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• 2006

Tribologcal property of the ceramics used in severe condition was investigated and both $Al_2O_3$ ball and Al/SiC composite made by thermal spray process[TSP] were used as a specimen in this study. Four kinds of material couple in ball and disk specimens were tested in the dry condition by using ball-on-disk type tribo-tester. Friction coefficient, surface roughness, wear rate, and photograph of the worn surface were investigated. Generally, High SiC contents[$40{\sim}50%$] specimens showed very low friction coefficient below 0.05 and little wear rate in dry condition. And also, low SiC contents[0%] specimens showed a moderate wear rate and high coefficient of friction at the same condition.

• 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.

• 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.

• 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

• 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.