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탄소/탄소 복합재료의 마찰 및 마모 거동과 신경회로망에의 적용에 관한 연구
Friction and Wear Behavior of Carbon/carbon Composite Materials and its Application to a Neural Network

류병진   (삼성중공업  ); 윤재륜   (서울대학교 섬유고분자공학과  ); 권익환   (제일모직 화성연구소  );
  • 초록

    Effects of resin contents, number of carbonization, graphitization, sliding speed, and oxidation on friction and wear behavior of carbon/carbon composite materials were investigated. Friction and wear tests were carried out under various sliding conditions. An experimental setup was designed and built in the laboratory. Stainless steel disks were used as the counterface material. Friction coefficient, emperature, and wear factor were measured with a data acquisition system. Wear surfaces were observed by the scanning electron microscope. It has been shown that the average friction coefficient was increased with the sliding speed in the range of 1.43~6.10 m/s, but it as decreased in the range of 6.10~17.35 m/s. Specimens prepared by different numbers of carbonization. showed variations in friction coefficient and friction coefficient of the graphitized specimen was the highest. Friction coefficients depended on contribution of the plowing and adhesive components. As the number of carbonization was increased, wear factor was reduced. Wear factor of the graphitized specimens dropped further. In the case of graphitized specimens, sliding speed had a large influence on wear behavior. When the tribological experiments were conducted in nitrogen atmosphere, the wear factor was decreased to two thirds of the wear factor obtained in air. It is obvious that the difference was affected by oxidation. Results of friction and wear tests were applied to a neural network system based on the backpropagation algorithm. A neural network may be a valuable tool for prediction of tribological behavior of the carbon/carbon composite material if ample data are present.


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