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Friction Characteristics of Aluminized Polyester Fabric under Dry- and Water- Lubricated Conditions
변재영,오케추쿠 나에메카 니콜라스,이은숙,박진규,최원식 한국트라이볼로지학회 2019 한국윤활학회지(윤활학회지) Vol.35 No.6
Materials made from plastics are increasingly utilized in constructing greenhouses and setting up shield structures. Polyester fabrics have a wide range of use in horticulture and other fields of agriculture. They are utilized as a greenhouse cover and also help in combating intense climate variation in the field. Over time, these fabrics may experience friction against other surfaces. Owing to this, the surface framework of the material degenerates. This study examines the frictional characteristics of aluminized polyester fabric in both dry- and water-lubricated environments under changing applied loads and sliding speeds. Friction experiments are performed at room temperature by employing a pin on a disk. The experiments reveal that the friction coefficient decreases with increase in applied load in both dry sliding and water-lubricated environment. However, the friction coefficient decreases more under the water-lubricated setting than in the dry state. At the maximum applied load, the highest friction coefficient is discovered in the dry state with a range of 0.282 to 0.237, whereas a friction coefficient of 0.229 to 0.189 is observed in the water-lubricated state. Additionally, it is observed that the friction coefficient increases with an increase in sliding speed under both experimental environments. The examination of specimen surfaces reveals that the abrasion is minor in the water-lubricated setting compared with that in the dry state.
최원식,프라타마 판두 산디,수페노 데스티아니,변재영,이은숙,우지희,양지웅,키프 디마스 하리스 신,크리스타 마이난다 브리기타,오케추쿠 나에메카 니콜라스,이강삼,Choi, Wonsik,Pratama, Pandu Sandi,Supeno, Destiani,Byun, Jaeyoung,Lee, Ensuk,Woo, Jihee,Yang, Jiung,Keefe, Dimas The Korean Society of Industry Convergence 2018 한국산업융합학회 논문집 Vol.21 No.5
In this research, the effect of normal load, sliding velocity, and texture density on thefriction coefficient of surfaces micro-textured on AISI 4140 under paraffin oil lubrication were investigated. The predicted tribological behavior by numerical calculation can be serves as guidance for the designer during the machine development stage. Therefore, in this research friction coefficient prediction model based on response surface methodology (RSM), support vector machine (SVM), and artificial neural network (ANN) were developed. The experimental result shows that the variation of load, speed and texture density were influence the friction coefficient. The RSM, ANN and SVM model was successfully developed based on the experimental data. The ANN model can effectively predict the tribological characteristics of micro-textured AISI 4140 in paraffin oil lubrication condition compare to RSM and SVM.