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자동차 경량화를 위한 단섬유강화 복합재료에서의 섬유생존율이 기계적 물성에 미치는 영향에 관한 연구
최영근(Young-Geun Choi),이상협(Sang-Hyoup Lee),이인섭(In-Seob Lee) 한국산업융합학회 2001 한국산업융합학회 논문집 Vol.4 No.3
In this study, the survival rate of fiber is investigated by nozzle size difference in injection/mold sides. The survival rate of fiber is influenced about the nozzle size differ. Also, The mechanical properties of short carbon glass fiber reinforced polypropylene are experimentally measured as functions of fiber volume fraction and nozzle size difference. These mechanical properties are compared with the survival rate of fiber and fiber volume fraction using image analysis after pyrolytic decomposition. The survival rate of fiber as well as fiber volume fraction is influenced by injection processing condition, the used materials, mold conditions and nozzle sides difference, etc, In particular, the survival rate of fiber is great influenced when injection/mold nozzle sides are different more than that of the same. Consequently, the mechanical properties of short carbon/glass firer reinforced polypropylene arc improved as the nozzle sides are the same in injection mold sides.<br/> <br/> <br/>
김면희(Myun-Hee Kim),최영근(Young-Geun Choi),신현승(Hyeon-Seung Shin),이문환(Moon-Hwan Lee),이태영(Tae-Young Lee),이상협(Sang-Hyoup Lee) 한국산업융합학회 2002 한국산업융합학회 논문집 Vol.5 No.2
In GMAW(Gas Metal Are Welding) processes, bead geometry (penetration, bead width and height) is a criterion to estimate welding quality, Bead geometry is affected by welding current, arc voltage and travel speed, shielding gas, CTWD (contact-tip to workpiece distance) and so on. In this paper, welding process variables were selected as welding current, arc voltage and travel speed. And bead geometry was reasoned from the chosen welding process variables using neuro-fuzzy algorithm. Neural networks was applied to design FLC(fuzzy logic control), The parameters of input membership functions and those of consequence functions in FLC were tuned through the method of learning by backpropagation algorithm, Bead geometry could he reasoned from welding current, arc voltage, travel speed on FLC using the results learned by neural networks. On the developed inference system of bead geometry using neuo-fuzzy algorithm, the inference error percent of bead width was within ±4%, that of bead height was within ±3%, and that of penetration was within ±8%, Neural net works came into effect to find the parameters of input membership functions and those of consequence in FLC. Therefore the inference system of welding quality expects to be developed through proposed algorithm.<br/>