• Composites Research
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• v.16 no.3
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• pp.75-84
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• 2003

The purpose of this study is to investigate the wear properties of Saffil/Al, Saffil/A12O3/Al and Saffil/SiC/Al hybrid metal matrix composites fabricated by squeeze casting method. Wear tests were done on a pin-on-disk friction and wear tester under both dry and lubricated conditions. The wear properties of the three composites were evaluated in many respects. The effects of Saffil fibers, $\textrm{Al}_2\textrm{O}_3$ particles and SiC particles on the wear behavior of the composites were investigated. Wear mechanisms were analyzed by observing the worn surfaces of the composites. The variation of coefficient of friction(COF) during the wear process was recorded by using a computer. Under dry sliding condition, Saffil/SiC/Al showed the best wear resistance under high temperature and high load, while the wear resistances of Saffil/Al and Saffi1/$\textrm{Al}_2\textrm{O}_3$/Al were very similar. Under dry sliding condition, the dominant wear mechanism was abrasive wear under mild load and room temperature, and the dominant wear mechanism changed to adhesive wear as load or temperature increased. Molten wear occurred at high temperature. Compared with the dry sliding condition, all three composites showed excellent wear resistance when lubricated by liquid paraffin. Under lubricated condition, Saffil/Al showed the best wear resistance among them, and its COF value was the smallest. The dominant wear mechanism of the composites under lubricated condition was microploughing, but microcracking also occurred to them to different extents.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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• pp.83-90
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• 1998

The morphologies of the wear debris are directly indicative of wear processes occuring in machinery and their severity. The neural network was applied to identify friction condition 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 coefficient. 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 between the characteristic of wear debris and the friction coefficient and how the network determines difference in wear debris feature.

• 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.2 no.1
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• pp.35-39
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• 2001

In this paper, statistical approach is undertaken to investigate the classification of wear debris which is the key function of objective assessment of wear debris morphology. Wear tests are run to produce various kinds of wear debris. The images of wear debris from wear tests are captured with image acquisition equipment. By thresholding, two-dimensional binary images of wear debris are made and, then, morphological parameters are used to quantify the images of debris. Parametric and nonparametric discriminant method are employed to classify wear debris into predefined wear conditions. It is demonstrated that classification accuracy of parametric and nonparametric discriminant method is similar. The selected use of morphological parameters by stepwise discriminant analysis can generally improve the classification accuracy of parametric and nonparametric discriminant method.

• Tribology and Lubricants
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• v.19 no.4
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• pp.223-229
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• 2003

The sliding wear characteristics of the crane sheave were investigated using a pin-on-disk rig tester. The experiment was conducted using a high carbon steel wire that was upper material, also carbon steel castings that was disk material. There are various operating conditions in this work. At the room temperature, we carried out the wear test under a grease lubrication and dry condition. The results of wear test showed that an annealed-casted have lower, also the wear curves are linearly increased with increasing of sliding distance. For the specific wear rate of annealed-casted, the wear resistance was increased with decreasing diameter of wire. The wear of a wire and a disk have a different mechanism, the one is the abrasive wear due to fatigue wear under lubrication, another is the adhesion wear under dry condition.

• Asian Journal of Turfgrass Science
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• v.11 no.3
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• pp.205-210
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• 1997

The metal spikes evaluated in this study significantly affected more negative on the turf wear and ball speed of putting green than alternative plastic spikes. 1.The metal spikes caused the most amount of wear compared with plastic spikes, athletic shoes and mountain-climbing shoes. On the other hand, athletic shoes caused the least amount of wear. Plastic spikes caused wear more than athletic shoes, hut apparently wear less than metal spikes. The wear from metal spike repaired later than any other tread types. 2.The wear from all kinds of shoe treads in wetcondition green were higher than in dry-condition green and the wear from metal spikes was more severe compared with plastic spikes in both green condition. 3. Ball speed of heavy compaction area by metal spike was reduced about 9% compared with that of light compaction area, hecause metal spikes made many holes in the putting green surface. On the other hand, plastic spikes did not affect hall speed of heavy and light compaction area in the putting green. Key words: Metal spike, Plastic spike, Wear, Ball speed.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.04a
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• pp.46-49
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• 2003

Aluminum based metal matrix composites(MMCs) are well known for their high specific strength, stiffness and hardness. They are gaining further importance because of their high wear resistance. In this study, Al/Saffil-20%, Al/Saffil-5%/Al2O3(particle type)-15% and Al/Saffil-5%/SiC(particle type)-15% hybird MMCs' wear behavior were characterized by the pin-on-disk test under various normal load The superior wear resistance was exhibited at Al/Saffil-5%/SiC(particle type)-15% MMCs. And this MMCs' predominant wear mechanism is subsurface cracking in the low load wear regime. Others(Al/Saffil-20%, Al/Saffil-5%/Al2O3(particle type)-15%) showed the similar wear resistance with each other at the same test condition. In the low load & room temperature condition, the wear resistance was improved due to the high hardness of the ceramic reinforcements. As the test load increased, the wear properties were governed by the wear properties of matrix.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.11
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• pp.1873-1880
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• 2003

The sliding wear characteristics of the crane sheave were investigated using a pin on disk rig tester. The experiment was conducted using a high carbon steel wire that was upper material, also carbon steel castings that was disk material. There are various operating conditions in this work. At the room temperature, we carried out the wear test under a grease lubrication and dry condition. The results of wear test showed that an annealed-casted have lower, also the wear curves are linearly increased with increasing of sliding distance. For the specific wear rate of annealed-casted, the wear resistance was increased with decreasing diameter of wire. The wear of a wire and a disk have a different mechanism, the one is the abrasive wear due to fatigue wear under lubrication, another is the adhesion wear under dry condition.

• KSTLE International Journal
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• v.4 no.1
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• pp.31-36
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• 2003

Sliding and impact/sliding wear test in room temperature air and water were performed to evaluate the effect of spring shapes on the wear mechanism of a fuel rod. The main focus was to quantitatively compare the wear behavior of a fuel rod with different support springs (i.e. two concaves, a convex and a flat shape) using a ratio of wear volume to worn area (De)-The results indicated that the wear volumes at each spring condition were varied with the change of test environment and loading type. However, the relationship between the wear volume and worn area was determined by only spring shape even though the wear tests were carried out at different test conditions. From the above results, the optimized spring shape which has more wear-resistant could be determined using the analysis results of the relation between the variation of De and worn surface observations in each test condition.

• 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.